feature/port-to-py3 #11
1
.gitignore
vendored
1
.gitignore
vendored
@ -1,3 +1,4 @@
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*.pyc
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*~
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.idea
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pylot/RELEASE-VERSION
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318
PyLoT.py
318
PyLoT.py
@ -24,30 +24,27 @@ https://www.iconfinder.com/iconsets/flavour
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"""
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import argparse
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import matplotlib
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import json
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import os
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import platform
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import shutil
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import sys
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import traceback
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import json
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from datetime import datetime
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matplotlib.use('Qt4Agg')
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matplotlib.rcParams['backend.qt4'] = 'PySide'
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matplotlib.rcParams['savefig.dpi'] = 300
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import matplotlib
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matplotlib.use('Qt5Agg')
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from PySide import QtGui, QtCore
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from PySide.QtCore import QCoreApplication, QSettings, Signal, QFile, \
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from PySide2 import QtGui, QtCore, QtWidgets
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from PySide2.QtCore import QCoreApplication, QSettings, Signal, QFile, \
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QFileInfo, Qt, QSize
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|
kaan marked this conversation as resolved
Outdated
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from PySide.QtGui import QMainWindow, QInputDialog, QIcon, QFileDialog, \
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QWidget, QHBoxLayout, QVBoxLayout, QStyle, QKeySequence, QLabel, QFrame, QAction, \
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QDialog, QApplication, QPixmap, QMessageBox, QSplashScreen, \
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from PySide2.QtGui import QIcon, QKeySequence, QPixmap, QStandardItem
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from PySide2.QtWidgets import QMainWindow, QInputDialog, QFileDialog, \
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QWidget, QHBoxLayout, QVBoxLayout, QStyle, QLabel, QFrame, QAction, \
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QDialog, QApplication, QMessageBox, QSplashScreen, \
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QActionGroup, QListWidget, QListView, QAbstractItemView, \
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QTreeView, QComboBox, QTabWidget, QPushButton, QGridLayout
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QTreeView, QComboBox, QTabWidget, QPushButton, QGridLayout, QTableWidgetItem, QTableWidget
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import numpy as np
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from obspy import UTCDateTime, Stream
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from obspy.core.event import Magnitude, Origin
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@ -58,9 +55,9 @@ from pylot.core.util.obspyDMT_interface import check_obspydmt_structure
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import pyqtgraph as pg
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try:
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from matplotlib.backends.backend_qt4agg import FigureCanvas
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from matplotlib.backends.backend_qt5agg import FigureCanvas
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except ImportError:
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from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
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from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
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from matplotlib.figure import Figure
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from pylot.core.analysis.magnitude import LocalMagnitude, MomentMagnitude
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@ -68,8 +65,8 @@ from pylot.core.io.data import Data
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from pylot.core.io.inputs import FilterOptions, PylotParameter
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from autoPyLoT import autoPyLoT
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from pylot.core.pick.compare import Comparison
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from pylot.core.pick.utils import symmetrize_error, getQualityFromUncertainty, getPickQuality, get_quality_class
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from pylot.core.io.phases import picksdict_from_picks, picks_from_picksdict
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from pylot.core.pick.utils import getQualityFromUncertainty
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from pylot.core.io.phases import picksdict_from_picks
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import pylot.core.loc.nll as nll
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from pylot.core.util.errors import DatastructureError, \
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OverwriteError
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@ -79,29 +76,28 @@ from pylot.core.util.utils import fnConstructor, getLogin, \
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full_range, readFilterInformation, pick_color_plt, \
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pick_linestyle_plt, identifyPhaseID, excludeQualityClasses, \
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transform_colors_mpl, transform_colors_mpl_str, getAutoFilteroptions, check_all_obspy, \
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check_all_pylot, get_Bool, get_None, SetChannelComponents
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check_all_pylot, get_Bool, get_None
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from pylot.core.util.gui import make_pen
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from pylot.core.util.event import Event
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from pylot.core.io.location import create_creation_info, create_event
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from pylot.core.util.widgets import FilterOptionsDialog, NewEventDlg, \
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PylotCanvas, WaveformWidgetPG, PropertiesDlg, HelpForm, createAction, PickDlg, \
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ComparisonWidget, TuneAutopicker, PylotParaBox, AutoPickDlg, CanvasWidget, AutoPickWidget, \
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CompareEventsWidget, ProgressBarWidget, AddMetadataWidget, SingleTextLineDialog
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CompareEventsWidget, ProgressBarWidget, AddMetadataWidget, SingleTextLineDialog, LogWidget
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from pylot.core.util.array_map import Array_map
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from pylot.core.util.structure import DATASTRUCTURE
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from pylot.core.util.thread import Thread, Worker
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from pylot.core.util.version import get_git_version as _getVersionString
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from pylot.core.io.getEventListFromXML import geteventlistfromxml
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from pylot.core.io.getQualitiesfromxml import getQualitiesfromxml
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from pylot.core.io.phases import getQualitiesfromxml
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from pylot.styles import style_settings
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if sys.version_info.major == 3:
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import icons_rc_3 as icons_rc
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elif sys.version_info.major == 2:
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import icons_rc_2 as icons_rc
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else:
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raise ImportError('Could not determine python version.')
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raise ImportError(f'Python version {sys.version_info.major} of current interpreter not supported.'
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f'\nPlease use Python 3+.')
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# workaround to prevent PyCharm from deleting icons_rc import when optimizing imports
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icons_rc = icons_rc
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@ -116,8 +112,21 @@ class MainWindow(QMainWindow):
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def __init__(self, parent=None, infile=None, reset_qsettings=False):
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super(MainWindow, self).__init__(parent)
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self.init_config_files(infile)
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# check for default pylot.in-file
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if not infile:
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infile = os.path.join(os.path.expanduser('~'), '.pylot', 'pylot.in')
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print('Using default input file {}'.format(infile))
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if os.path.isfile(infile) == False:
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infile = QFileDialog().getOpenFileName(caption='Choose PyLoT-input file')
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if not os.path.exists(infile[0]):
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QMessageBox.warning(self, "PyLoT Warning",
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"No PyLoT-input file declared!")
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sys.exit(0)
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self.infile = infile[0]
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else:
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self.infile = infile
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self._inputs = PylotParameter(infile)
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self._props = None
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self.gain = 1.
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@ -178,6 +187,7 @@ class MainWindow(QMainWindow):
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self.table_headers = ['', 'Event', 'Time', 'Lat', 'Lon', 'Depth', 'Ml', 'Mw', '[N] MP', '[N] AP', 'Tuning Set',
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'Test Set', 'Notes']
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# TODO: refactor rootpath to datapath
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while True:
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try:
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if settings.value("user/FullName", None) is None:
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@ -244,7 +254,7 @@ class MainWindow(QMainWindow):
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self._inputs.export2File(infile)
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self.infile = infile
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def setupUi(self):
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def setupUi(self, use_logwidget=True):
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try:
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self.startTime = min(
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[tr.stats.starttime for tr in self.data.wfdata])
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@ -480,7 +490,8 @@ class MainWindow(QMainWindow):
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self.eventlist_xml_action = self.createAction(parent=self, text='Create Eventlist from XML',
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slot=self.eventlistXml, shortcut='Alt+X',
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icon=eventlist_xml_icon, tip='Create an Eventlist from a XML File')
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icon=eventlist_xml_icon,
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tip='Create an Eventlist from a XML File')
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self.eventlist_xml_action.setEnabled(False)
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printAction = self.createAction(self, "&Print event ...",
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@ -492,11 +503,8 @@ class MainWindow(QMainWindow):
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"""Show either the documentation
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homepage (internet connection available),
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or shipped documentation files.""")
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# phaseToolBar = self.addToolBar("PhaseTools")
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# phaseToolActions = (self.selectPAction, self.selectSAction)
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# phaseToolBar.setObjectName("PhaseTools")
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# self.addActions(phaseToolBar, phaseToolActions)
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logAction = self.createAction(self, "&Show Log", self.showLogWidget,
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tip="""Display Log""")
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# create button group for component selection
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@ -551,7 +559,8 @@ class MainWindow(QMainWindow):
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' the complete project on grid engine.')
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self.auto_pick_sge.setEnabled(False)
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pickActions = (self.auto_tune, self.auto_pick, self.compare_action, self.qualities_action, self.eventlist_xml_action)
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pickActions = (
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self.auto_tune, self.auto_pick, self.compare_action, self.qualities_action, self.eventlist_xml_action)
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# pickToolBar = self.addToolBar("PickTools")
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# pickToolActions = (selectStation, )
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@ -592,11 +601,10 @@ class MainWindow(QMainWindow):
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self.autoPickMenu = self.pickMenu.addMenu(self.autopicksicon_small, 'Automatic picking')
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self.autoPickMenu.setEnabled(False)
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autoPickActions = (self.auto_pick, self.auto_pick_local, self.auto_pick_sge)
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self.helpMenu = self.menuBar().addMenu('&Help')
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helpActions = (helpAction,)
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helpActions = (helpAction, logAction)
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fileToolActions = (self.newProjectAction,
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self.openProjectAction, self.saveProjectAction,
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@ -674,7 +682,7 @@ class MainWindow(QMainWindow):
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self._main_layout.addWidget(self.mainProgressBarWidget)
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# add scroll area used in case number of traces gets too high
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self.wf_scroll_area = QtGui.QScrollArea(self)
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self.wf_scroll_area = QtWidgets.QScrollArea(self)
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self.wf_scroll_area.setVisible(False)
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self.no_data_label = QLabel('No Data')
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self.no_data_label.setStyleSheet('color: red')
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@ -684,14 +692,14 @@ class MainWindow(QMainWindow):
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self.init_wfWidget()
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# init main widgets for main tabs
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wf_tab = QtGui.QWidget(self)
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array_tab = QtGui.QWidget(self)
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events_tab = QtGui.QWidget(self)
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wf_tab = QtWidgets.QWidget(self)
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array_tab = QtWidgets.QWidget(self)
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events_tab = QtWidgets.QWidget(self)
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# init main widgets layouts
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self.wf_layout = QtGui.QVBoxLayout()
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self.array_layout = QtGui.QVBoxLayout()
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self.events_layout = QtGui.QVBoxLayout()
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self.wf_layout = QtWidgets.QVBoxLayout()
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self.array_layout = QtWidgets.QVBoxLayout()
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self.events_layout = QtWidgets.QVBoxLayout()
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wf_tab.setLayout(self.wf_layout)
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array_tab.setLayout(self.array_layout)
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events_tab.setLayout(self.events_layout)
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@ -723,8 +731,16 @@ class MainWindow(QMainWindow):
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_widget.setLayout(self._main_layout)
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_widget.showFullScreen()
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self.setCentralWidget(_widget)
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if use_logwidget:
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self.logwidget = LogWidget(parent=None)
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self.logwidget.show()
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self.stdout = self.logwidget.stdout
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self.stderr = self.logwidget.stderr
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sys.stdout = self.stdout
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sys.stderr = self.stderr
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self.setCentralWidget(_widget)
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def init_wfWidget(self):
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xlab = self.startTime.strftime('seconds since %Y/%m/%d %H:%M:%S (%Z)')
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@ -742,8 +758,8 @@ class MainWindow(QMainWindow):
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'''
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Initiate/create buttons for assigning events containing manual picks to reference or test set.
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'''
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self.ref_event_button = QtGui.QPushButton('Tune')
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self.test_event_button = QtGui.QPushButton('Test')
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self.ref_event_button = QtWidgets.QPushButton('Tune')
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self.test_event_button = QtWidgets.QPushButton('Test')
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self.ref_event_button.setMinimumWidth(100)
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self.test_event_button.setMinimumWidth(100)
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self.ref_event_button.setToolTip('Set manual picks of current ' +
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@ -759,6 +775,10 @@ class MainWindow(QMainWindow):
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self.ref_event_button.setEnabled(False)
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self.test_event_button.setEnabled(False)
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def showLogWidget(self):
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self.logwidget.show()
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self.logwidget.activateWindow()
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def keyPressEvent(self, event):
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if event.key() == QtCore.Qt.Key.Key_Control:
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self._ctrl = True
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@ -771,7 +791,6 @@ class MainWindow(QMainWindow):
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if event.key() == QtCore.Qt.Key.Key_R:
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self.reset_gain()
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def keyReleaseEvent(self, event):
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if event.key() == QtCore.Qt.Key.Key_Control:
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self._ctrl = False
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@ -791,7 +810,7 @@ class MainWindow(QMainWindow):
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def modify_gain(self, direction, factor):
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assert (direction in ['+', '-']), 'unknown direction'
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if self._ctrl:
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factor = factor**3
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factor = factor ** 3
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if direction == '+':
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self.gain *= factor
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elif direction == '-':
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@ -943,7 +962,6 @@ class MainWindow(QMainWindow):
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self.recentProjectsMenu.addAction(action)
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@property
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def inputs(self):
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return self._inputs
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@ -981,7 +999,7 @@ class MainWindow(QMainWindow):
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if not sld.exec_():
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return
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fext = sld.lineEdit.text()
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#fext = '.xml'
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# fext = '.xml'
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for event in events:
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path = event.path
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eventname = path.split('/')[-1] # or event.pylot_id
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@ -1013,7 +1031,7 @@ class MainWindow(QMainWindow):
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data_new = Data(self, evtdata=str(fname))
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# MP MP commented because adding several picks might cause inconsistencies
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data = data_new
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#data += data_new
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# data += data_new
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except ValueError:
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qmb = QMessageBox(self, icon=QMessageBox.Question,
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text='Warning: Missmatch in event identifiers {} and {}. Continue?'.format(
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@ -1162,13 +1180,14 @@ class MainWindow(QMainWindow):
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eventlist_file = os.path.join(basepath, 'eventlist.txt')
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if os.path.isfile(eventlist_file):
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with open(eventlist_file, 'r') as infile:
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eventlist_subset = [os.path.join(basepath, filename.split('\n')[0]) for filename in infile.readlines()]
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eventlist_subset = [os.path.join(basepath, filename.split('\n')[0]) for filename in
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infile.readlines()]
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msg = 'Found file "eventlist.txt" in database path. WILL ONLY USE SELECTED EVENTS out of {} events ' \
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'contained in this subset'
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print(msg.format(len(eventlist_subset)))
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eventlist = [eventname for eventname in eventlist if eventname in eventlist_subset]
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if check_obspydmt_structure(basepath):
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print('Recognized obspyDMT structure in selected files. Settings Datastructure to ObspyDMT')
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print('Recognized obspyDMT structure in selected files. Setting Datastructure to ObspyDMT')
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self.dataStructure = DATASTRUCTURE['obspyDMT']()
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eventlist = check_all_obspy(eventlist)
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else:
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@ -1192,13 +1211,14 @@ class MainWindow(QMainWindow):
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if system_name in ["Linux", "Darwin"]:
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dirs = {
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'database': path.split('/')[-2],
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'datapath': path.split('/')[-3],
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'datapath': os.path.split(path)[0], # path.split('/')[-3],
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'rootpath': '/' + os.path.join(*path.split('/')[:-3])
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}
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elif system_name == "Windows":
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rootpath = path.split('/')[:-3]
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rootpath[0] += '/'
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dirs = {
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# TODO: Arrange path to meet Win standards
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'database': path.split('/')[-2],
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'datapath': path.split('/')[-3],
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'rootpath': os.path.join(*rootpath)
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@ -1212,7 +1232,7 @@ class MainWindow(QMainWindow):
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print('Warning: Could not automatically init folder structure. ({})'.format(e))
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settings = QSettings()
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settings.setValue("data/dataRoot", dirs['rootpath'])
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settings.setValue("data/dataRoot", dirs['datapath']) # d irs['rootpath'])
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settings.sync()
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if not self.project.eventlist:
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@ -1230,14 +1250,16 @@ class MainWindow(QMainWindow):
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if not dirs_box.exec_():
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return
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self.project.rootpath = dirs['rootpath']
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self.project.datapath = dirs['datapath']
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else:
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if hasattr(self.project, 'rootpath'):
|
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if not self.project.rootpath == dirs['rootpath']:
|
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if hasattr(self.project, 'datapath'):
|
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if not self.project.datapath == dirs['datapath']:
|
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QMessageBox.warning(self, "PyLoT Warning",
|
||||
'Rootpath missmatch to current project!')
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||||
'Datapath missmatch to current project!')
|
||||
return
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||||
else:
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||||
self.project.rootpath = dirs['rootpath']
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||||
self.project.datapath = dirs['datapath']
|
||||
|
||||
self.project.add_eventlist(eventlist)
|
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self.init_events()
|
||||
@ -1295,7 +1317,7 @@ class MainWindow(QMainWindow):
|
||||
tabindex = self.tabs.currentIndex()
|
||||
|
||||
def user_modify_path(self, reason=''):
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dialog = QtGui.QInputDialog(parent=self)
|
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dialog = QtWidgets.QInputDialog(parent=self)
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new_path, executed = dialog.getText(self, 'Change Project rootpath',
|
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'{}Rename project path {}:'.format(reason, self.project.rootpath))
|
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return new_path, executed
|
||||
@ -1324,6 +1346,7 @@ class MainWindow(QMainWindow):
|
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return True
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||||
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||||
def modify_project_path(self, new_rootpath):
|
||||
# TODO: change root to datapath
|
||||
self.project.rootpath = new_rootpath
|
||||
for event in self.project.eventlist:
|
||||
event.rootpath = new_rootpath
|
||||
@ -1348,13 +1371,13 @@ class MainWindow(QMainWindow):
|
||||
if not eventBox:
|
||||
eventBox = self.eventBox
|
||||
index = eventBox.currentIndex()
|
||||
tv = QtGui.QTableView()
|
||||
tv = QtWidgets.QTableView()
|
||||
header = tv.horizontalHeader()
|
||||
header.setResizeMode(QtGui.QHeaderView.ResizeToContents)
|
||||
header.setResizeMode(QtWidgets.QHeaderView.ResizeToContents)
|
||||
header.setStretchLastSection(True)
|
||||
header.hide()
|
||||
tv.verticalHeader().hide()
|
||||
tv.setSelectionBehavior(QtGui.QAbstractItemView.SelectRows)
|
||||
tv.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectRows)
|
||||
|
||||
current_event = self.get_current_event()
|
||||
|
||||
@ -1393,18 +1416,25 @@ class MainWindow(QMainWindow):
|
||||
event_ref = event.isRefEvent()
|
||||
event_test = event.isTestEvent()
|
||||
|
||||
time = lat = lon = depth = localmag = momentmag = None
|
||||
time = lat = lon = depth = localmag = None
|
||||
if len(event.origins) == 1:
|
||||
origin = event.origins[0]
|
||||
time = origin.time + 0 # add 0 because there was an exception for time = 0s
|
||||
lat = origin.latitude
|
||||
lon = origin.longitude
|
||||
depth = origin.depth
|
||||
if len(event.magnitudes) > 1:
|
||||
if len(event.magnitudes): # if magnitude information exists, i.e., event.magnitudes has at least 1 entry
|
||||
moment_magnitude = event.magnitudes[0]
|
||||
momentmag = '%4.1f' % moment_magnitude.mag
|
||||
if len(event.magnitudes) > 1:
|
||||
local_magnitude = event.magnitudes[1]
|
||||
localmag = '%4.1f' % local_magnitude.mag
|
||||
momentmag = '%4.1f'% moment_magnitude.mag
|
||||
else:
|
||||
localmag = ' '
|
||||
|
||||
else:
|
||||
momentmag = ' '
|
||||
localmag = ' '
|
||||
|
||||
# text = '{path:{plen}} | manual: [{p:3d}] | auto: [{a:3d}]'
|
||||
# text = text.format(path=event_path,
|
||||
@ -1415,24 +1445,24 @@ class MainWindow(QMainWindow):
|
||||
event_str = '{path:{plen}}'.format(path=event_path, plen=plmax)
|
||||
if event.dirty:
|
||||
event_str += '*'
|
||||
item_path = QtGui.QStandardItem(event_str)
|
||||
item_time = QtGui.QStandardItem('{}'.format(time))
|
||||
item_lat = QtGui.QStandardItem('{}'.format(lat))
|
||||
item_lon = QtGui.QStandardItem('{}'.format(lon))
|
||||
item_depth = QtGui.QStandardItem('{}'.format(depth))
|
||||
item_localmag = QtGui.QStandardItem('{}'.format(localmag))
|
||||
item_momentmag = QtGui.QStandardItem('{}'.format(momentmag))
|
||||
item_nmp = QtGui.QStandardItem('{}({})'.format(ma_count['manual'], ma_count_total['manual']))
|
||||
item_path = QStandardItem(event_str)
|
||||
item_time = QStandardItem('{}'.format(time))
|
||||
item_lat = QStandardItem('{}'.format(lat))
|
||||
item_lon = QStandardItem('{}'.format(lon))
|
||||
item_depth = QStandardItem('{}'.format(depth))
|
||||
item_localmag = QStandardItem('{}'.format(localmag))
|
||||
item_momentmag = QStandardItem('{}'.format(momentmag))
|
||||
item_nmp = QStandardItem('{}({})'.format(ma_count['manual'], ma_count_total['manual']))
|
||||
item_nmp.setIcon(self.manupicksicon_small)
|
||||
item_nap = QtGui.QStandardItem('{}({})'.format(ma_count['auto'], ma_count_total['auto']))
|
||||
item_nap = QStandardItem('{}({})'.format(ma_count['auto'], ma_count_total['auto']))
|
||||
item_nap.setIcon(self.autopicksicon_small)
|
||||
item_ref = QtGui.QStandardItem() # str(event_ref))
|
||||
item_test = QtGui.QStandardItem() # str(event_test))
|
||||
item_ref = QStandardItem() # str(event_ref))
|
||||
item_test = QStandardItem() # str(event_test))
|
||||
if event_ref:
|
||||
item_ref.setBackground(self._ref_test_colors['ref'])
|
||||
if event_test:
|
||||
item_test.setBackground(self._ref_test_colors['test'])
|
||||
item_notes = QtGui.QStandardItem(event.notes)
|
||||
item_notes = QStandardItem(event.notes)
|
||||
|
||||
openIcon = self.style().standardIcon(QStyle.SP_DirOpenIcon)
|
||||
item_path.setIcon(openIcon)
|
||||
@ -1478,7 +1508,7 @@ class MainWindow(QMainWindow):
|
||||
wf_dir = wf_stat[self.data.processed]
|
||||
if wf_dir is not None:
|
||||
wf_path = os.path.join(event_path, wf_dir)
|
||||
if wf_dir is 'processed' and not os.path.exists(wf_path):
|
||||
if wf_dir == 'processed' and not os.path.exists(wf_path):
|
||||
wf_path = os.path.join(event_path, 'raw')
|
||||
else:
|
||||
wf_path = event_path
|
||||
@ -1516,6 +1546,7 @@ class MainWindow(QMainWindow):
|
||||
event = self.get_current_event()
|
||||
if not type(outformats) == list:
|
||||
outformats = [outformats]
|
||||
|
||||
def getSavePath(event, directory, outformats):
|
||||
if not directory:
|
||||
title = 'Save event data as {} to directory ...'.format(outformats)
|
||||
@ -1638,8 +1669,8 @@ class MainWindow(QMainWindow):
|
||||
self.cmpw.show()
|
||||
|
||||
def pickQualities(self):
|
||||
path = self._inputs['rootpath'] + '/' + self._inputs['datapath'] + '/' + self._inputs['database']
|
||||
getQualitiesfromxml(path)
|
||||
path = self.get_current_event_path()
|
||||
getQualitiesfromxml(path, self._inputs.get('timeerrorsP'), self._inputs.get('timeerrorsS'), plotflag=1)
|
||||
return
|
||||
|
||||
def eventlistXml(self):
|
||||
@ -1885,6 +1916,10 @@ class MainWindow(QMainWindow):
|
||||
|
||||
settings = QSettings()
|
||||
curr_event = self.get_current_event()
|
||||
if not curr_event:
|
||||
print('Could not find current event. Try reload?')
|
||||
return
|
||||
|
||||
if len(curr_event.origins) > 0:
|
||||
origin_time = curr_event.origins[0].time
|
||||
tstart = settings.value('tstart') if get_None(settings.value('tstart')) else 0
|
||||
@ -1900,7 +1935,7 @@ class MainWindow(QMainWindow):
|
||||
checkRotated=True,
|
||||
metadata=self.metadata,
|
||||
tstart=tstart,
|
||||
tstop=tstop,)
|
||||
tstop=tstop, )
|
||||
|
||||
def prepareObspyDMT_data(self, eventpath):
|
||||
qcbox_processed = self.dataPlot.qcombo_processed
|
||||
@ -2097,7 +2132,7 @@ class MainWindow(QMainWindow):
|
||||
if self.obspy_dmt:
|
||||
invpath = os.path.join(self.get_current_event_path(), 'resp')
|
||||
if not invpath in self.metadata.inventories:
|
||||
self.metadata.add_inventory(invpath, obspy_dmt_inv = True)
|
||||
self.metadata.add_inventory(invpath, obspy_dmt_inv=True)
|
||||
# check if directory is empty
|
||||
if os.listdir(invpath):
|
||||
self.init_map_button.setEnabled(True)
|
||||
@ -2628,7 +2663,7 @@ class MainWindow(QMainWindow):
|
||||
self.init_fig_dict()
|
||||
# if not self.tap:
|
||||
# init TuneAutopicker object
|
||||
self.tap = TuneAutopicker(self, self.obspy_dmt)
|
||||
self.tap = TuneAutopicker(self)
|
||||
# first call of update to init tabs with empty canvas
|
||||
self.update_autopicker()
|
||||
# connect update signal of TuneAutopicker with update function
|
||||
@ -2670,9 +2705,9 @@ class MainWindow(QMainWindow):
|
||||
# init event selection options for autopick
|
||||
self.pickoptions = [('current event', self.get_current_event, None),
|
||||
('tune events', self.get_ref_events, self._style['ref']['rgba']),
|
||||
('test events', self.get_test_events, self._style['test']['rgba']),]
|
||||
#('all (picked) events', self.get_manu_picked_events, None),
|
||||
#('all events', self.get_all_events, None)]
|
||||
('test events', self.get_test_events, self._style['test']['rgba']), ]
|
||||
# ('all (picked) events', self.get_manu_picked_events, None),
|
||||
# ('all events', self.get_all_events, None)]
|
||||
|
||||
self.listWidget = QListWidget()
|
||||
self.setDirty(True)
|
||||
@ -2894,7 +2929,6 @@ class MainWindow(QMainWindow):
|
||||
event.addPicks(picksdict['manual'])
|
||||
event.addAutopicks(picksdict['auto'])
|
||||
|
||||
|
||||
def drawPicks(self, station=None, picktype=None, stime=None):
|
||||
# if picktype not specified, draw both
|
||||
if not stime:
|
||||
@ -3100,11 +3134,12 @@ class MainWindow(QMainWindow):
|
||||
self.metadata_widget.setLayout(grid_layout)
|
||||
self.array_layout.addWidget(self.metadata_widget)
|
||||
|
||||
def init_array_map(self, index=1):
|
||||
def init_array_map(self, checked=0, index=1):
|
||||
'''
|
||||
Try to init array map widget. If no metadata are given,
|
||||
self.get_metadata will be called.
|
||||
'''
|
||||
if checked: pass # dummy argument for QAction trigger signal
|
||||
self.tabs.setCurrentIndex(1)
|
||||
# if there is no metadata (invetories is an empty list), just initialize the default empty tab
|
||||
if not self.metadata.inventories:
|
||||
@ -3195,24 +3230,24 @@ class MainWindow(QMainWindow):
|
||||
# changes attributes of the corresponding event
|
||||
table = self.project._table
|
||||
event = self.project.getEventFromPath(table[row][1].text().split('*')[0])
|
||||
if column == 9 or column == 10:
|
||||
if column == 10 or column == 11:
|
||||
# toggle checked states (exclusive)
|
||||
item_ref = table[row][9]
|
||||
item_test = table[row][10]
|
||||
if column == 9 and item_ref.checkState():
|
||||
item_ref = table[row][10]
|
||||
item_test = table[row][11]
|
||||
if column == 10 and item_ref.checkState():
|
||||
item_test.setCheckState(QtCore.Qt.Unchecked)
|
||||
event.setRefEvent(True)
|
||||
elif column == 9 and not item_ref.checkState():
|
||||
elif column == 10 and not item_ref.checkState():
|
||||
event.setRefEvent(False)
|
||||
elif column == 10 and item_test.checkState():
|
||||
elif column == 11 and item_test.checkState():
|
||||
item_ref.setCheckState(QtCore.Qt.Unchecked)
|
||||
event.setTestEvent(True)
|
||||
elif column == 10 and not item_test.checkState():
|
||||
elif column == 11 and not item_test.checkState():
|
||||
event.setTestEvent(False)
|
||||
self.fill_eventbox()
|
||||
elif column == 11:
|
||||
elif column == 12:
|
||||
# update event notes
|
||||
notes = table[row][11].text()
|
||||
notes = table[row][12].text()
|
||||
event.addNotes(notes)
|
||||
self.fill_eventbox()
|
||||
|
||||
|
kaan marked this conversation as resolved
Outdated
sebastianw
commented
See above! Remove commented code. See above! Remove commented code.
|
||||
@ -3232,8 +3267,8 @@ class MainWindow(QMainWindow):
|
||||
self.events_layout.removeWidget(self.event_table)
|
||||
|
||||
# init new qtable
|
||||
self.event_table = QtGui.QTableWidget(self)
|
||||
self.event_table.setColumnCount(12)
|
||||
self.event_table = QTableWidget(self)
|
||||
self.event_table.setColumnCount(len(self.table_headers))
|
||||
self.event_table.setRowCount(len(eventlist))
|
||||
self.event_table.setHorizontalHeaderLabels(self.table_headers)
|
||||
|
||||
@ -3247,8 +3282,6 @@ class MainWindow(QMainWindow):
|
||||
'auto': event.pylot_autopicks}
|
||||
ma_count = {'manual': 0,
|
||||
'auto': 0}
|
||||
ma_count_total = {'manual': 0,
|
||||
'auto': 0}
|
||||
|
||||
for ma in ma_props.keys():
|
||||
if ma_props[ma]:
|
||||
@ -3258,25 +3291,24 @@ class MainWindow(QMainWindow):
|
||||
continue
|
||||
if pick.get('spe'):
|
||||
ma_count[ma] += 1
|
||||
ma_count_total[ma] += 1
|
||||
|
||||
# init table items for current row
|
||||
item_delete = QtGui.QTableWidgetItem()
|
||||
item_delete = QTableWidgetItem()
|
||||
item_delete.setIcon(del_icon)
|
||||
item_path = QtGui.QTableWidgetItem()
|
||||
item_time = QtGui.QTableWidgetItem()
|
||||
item_lat = QtGui.QTableWidgetItem()
|
||||
item_lon = QtGui.QTableWidgetItem()
|
||||
item_depth = QtGui.QTableWidgetItem()
|
||||
item_momentmag = QtGui.QTableWidgetItem()
|
||||
item_localmag = QtGui.QTableWidgetItem()
|
||||
item_nmp = QtGui.QTableWidgetItem('{}({})'.format(ma_count['manual'], ma_count_total['manual']))
|
||||
item_path = QTableWidgetItem()
|
||||
item_time = QTableWidgetItem()
|
||||
item_lat = QTableWidgetItem()
|
||||
item_lon = QTableWidgetItem()
|
||||
item_depth = QTableWidgetItem()
|
||||
item_momentmag = QTableWidgetItem()
|
||||
item_localmag = QTableWidgetItem()
|
||||
item_nmp = QTableWidgetItem('{}'.format(ma_count['manual'])) # , ma_count_total['manual']))
|
||||
item_nmp.setIcon(self.manupicksicon_small)
|
||||
item_nap = QtGui.QTableWidgetItem('{}({})'.format(ma_count['auto'], ma_count_total['auto']))
|
||||
item_nap = QTableWidgetItem('{}'.format(ma_count['auto'])) # , ma_count_total['auto']))
|
||||
item_nap.setIcon(self.autopicksicon_small)
|
||||
item_ref = QtGui.QTableWidgetItem()
|
||||
item_test = QtGui.QTableWidgetItem()
|
||||
item_notes = QtGui.QTableWidgetItem()
|
||||
item_ref = QTableWidgetItem()
|
||||
item_test = QTableWidgetItem()
|
||||
item_notes = QTableWidgetItem()
|
||||
|
||||
event_str = event.path
|
||||
if event.dirty:
|
||||
@ -3347,13 +3379,13 @@ class MainWindow(QMainWindow):
|
||||
|
||||
for r_index, row in enumerate(self.project._table):
|
||||
for c_index, item in enumerate(row):
|
||||
if type(item) == QtGui.QTableWidgetItem:
|
||||
if type(item) == QTableWidgetItem:
|
||||
self.event_table.setItem(r_index, c_index, item)
|
||||
elif type(item) in [QtGui.QWidget, QtGui.QPushButton]:
|
||||
elif type(item) in [QWidget, QPushButton]:
|
||||
self.event_table.setCellWidget(r_index, c_index, item)
|
||||
|
||||
header = self.event_table.horizontalHeader()
|
||||
header.setResizeMode(QtGui.QHeaderView.ResizeToContents)
|
||||
header.setResizeMode(QtWidgets.QHeaderView.ResizeToContents)
|
||||
header.setStretchLastSection(True)
|
||||
self.event_table.cellChanged[int, int].connect(cell_changed)
|
||||
self.event_table.cellClicked[int, int].connect(cell_clicked)
|
||||
@ -3373,7 +3405,7 @@ class MainWindow(QMainWindow):
|
||||
return
|
||||
separator = sld.lineEdit.text()
|
||||
|
||||
fd = QtGui.QFileDialog()
|
||||
fd = QtWidgets.QFileDialog()
|
||||
fname = fd.getSaveFileName(self, 'Browse for file.',
|
||||
filter='Table (*.csv)')[0]
|
||||
if not fname: return
|
||||
@ -3390,20 +3422,20 @@ class MainWindow(QMainWindow):
|
||||
|
||||
def exportProjectTable(self, filename, separator=';'):
|
||||
with open(filename, 'w') as outfile:
|
||||
for header in self.table_headers[1:12]:
|
||||
for header in self.table_headers[1:13]:
|
||||
outfile.write('{}{}'.format(header, separator))
|
||||
outfile.write('\n')
|
||||
|
||||
for row in self.project._table:
|
||||
row = row[1:12]
|
||||
event, time, lat, lon, depth, mag, nmp, nap, tune, test, notes = row
|
||||
row = row[1:13]
|
||||
event, time, lat, lon, depth, ml, mw, nmp, nap, tune, test, notes = row
|
||||
row_str = ''
|
||||
for index in range(len(row)):
|
||||
row_str += '{}'+'{}'.format(separator)
|
||||
row_str += '{}' + '{}'.format(separator)
|
||||
|
||||
row_str = row_str.format(event.text(), time.text(), lat.text(), lon.text(), depth.text(), mag.text(),
|
||||
nmp.text(), nap.text(), bool(tune.checkState()), bool(test.checkState()),
|
||||
notes.text())
|
||||
row_str = row_str.format(event.text(), time.text(), lat.text(), lon.text(), depth.text(), ml.text(),
|
||||
mw.text(), nmp.text(), nap.text(), bool(tune.checkState()),
|
||||
bool(test.checkState()), notes.text())
|
||||
outfile.write(row_str + '\n')
|
||||
|
||||
message = 'Wrote table to file: {}'.format(filename)
|
||||
@ -3428,7 +3460,6 @@ class MainWindow(QMainWindow):
|
||||
if event == current_event:
|
||||
set_background_color(item_list, QtGui.QColor(*(0, 143, 143, 255)))
|
||||
|
||||
|
||||
def set_metadata(self):
|
||||
self.project.inventories = self.metadata.inventories
|
||||
if self.metadata.inventories:
|
||||
@ -3440,7 +3471,7 @@ class MainWindow(QMainWindow):
|
||||
self.init_map_button.setEnabled(False)
|
||||
self.initMapAction.setEnabled(False)
|
||||
self.inventory_label.setText("No inventory set...")
|
||||
#self.setDirty(False)
|
||||
# self.setDirty(False)
|
||||
|
||||
def add_metadata(self):
|
||||
self.add_metadata_widget = AddMetadataWidget(self, metadata=self.metadata)
|
||||
@ -3643,7 +3674,7 @@ class MainWindow(QMainWindow):
|
||||
autosaveXML = get_Bool(settings.value('autosaveXML', True))
|
||||
if autosaveXML:
|
||||
self.exportEvents()
|
||||
self.project.save(filename)
|
||||
if not self.project.save(filename): return False
|
||||
self.setDirty(False)
|
||||
self.saveProjectAsAction.setEnabled(True)
|
||||
self.update_status('Saved new project to {}'.format(filename), duration=5000)
|
||||
@ -3667,7 +3698,7 @@ class MainWindow(QMainWindow):
|
||||
autosaveXML = get_Bool(settings.value('autosaveXML', True))
|
||||
if autosaveXML:
|
||||
self.exportEvents()
|
||||
self.project.save()
|
||||
if not self.project.save(): return False
|
||||
self.update_obspy_dmt()
|
||||
if not self.project.dirty:
|
||||
self.setDirty(False)
|
||||
@ -3702,15 +3733,17 @@ class MainWindow(QMainWindow):
|
||||
|
||||
def closeEvent(self, event):
|
||||
if self.okToContinue():
|
||||
self.logwidget.close()
|
||||
event.accept()
|
||||
else:
|
||||
event.ignore()
|
||||
# self.closing.emit()
|
||||
# QMainWindow.closeEvent(self, event)
|
||||
|
||||
def setParameter(self, show=True):
|
||||
def setParameter(self, checked=0, show=True):
|
||||
if checked: pass # dummy argument to receive trigger signal (checked) if called by QAction
|
||||
if not self.paraBox:
|
||||
self.paraBox = PylotParaBox(self._inputs, parent=self, windowflag=1)
|
||||
self.paraBox = PylotParaBox(self._inputs, parent=self, windowflag=Qt.Window)
|
||||
self.paraBox.accepted.connect(self._setDirty)
|
||||
self.paraBox.accepted.connect(self.filterOptionsFromParameter)
|
||||
if show:
|
||||
@ -3733,7 +3766,6 @@ class MainWindow(QMainWindow):
|
||||
self.plotWaveformDataThread()
|
||||
self.refreshTabs()
|
||||
|
||||
|
||||
def PyLoTprefs(self):
|
||||
if not self._props:
|
||||
self._props = PropertiesDlg(self, infile=self.infile,
|
||||
@ -3763,10 +3795,12 @@ class Project(object):
|
||||
Pickable class containing information of a PyLoT project, like event lists and file locations.
|
||||
'''
|
||||
|
||||
# TODO: remove rootpath
|
||||
def __init__(self):
|
||||
self.eventlist = []
|
||||
self.location = None
|
||||
self.rootpath = None
|
||||
self.datapath = None
|
||||
self.dirty = False
|
||||
self.parameter = None
|
||||
self._table = None
|
||||
@ -3855,7 +3889,7 @@ class Project(object):
|
||||
if not event.datapath in datapaths:
|
||||
datapaths.append(event.datapath)
|
||||
for datapath in datapaths:
|
||||
datapath = os.path.join(self.rootpath, datapath)
|
||||
# datapath = os.path.join(self.rootpath, datapath)
|
||||
if os.path.isdir(datapath):
|
||||
for filename in os.listdir(datapath):
|
||||
filename = os.path.join(datapath, filename)
|
||||
@ -3893,34 +3927,38 @@ class Project(object):
|
||||
Can be loaded by using project.load(filename).
|
||||
'''
|
||||
try:
|
||||
import cPickle
|
||||
import pickle
|
||||
except ImportError:
|
||||
import _pickle as cPickle
|
||||
import _pickle as pickle
|
||||
|
||||
if filename:
|
||||
self.location = filename
|
||||
else:
|
||||
filename = self.location
|
||||
|
||||
table = self._table # MP: see below
|
||||
try:
|
||||
outfile = open(filename, 'wb')
|
||||
cPickle.dump(self, outfile, -1)
|
||||
self._table = [] # MP: Workaround as long as table cannot be saved as part of project
|
||||
pickle.dump(self, outfile, protocol=pickle.HIGHEST_PROTOCOL)
|
||||
self.setDirty(False)
|
||||
self._table = table # MP: see above
|
||||
return True
|
||||
except Exception as e:
|
||||
print('Could not pickle PyLoT project. Reason: {}'.format(e))
|
||||
self.setDirty()
|
||||
self._table = table # MP: see above
|
||||
return False
|
||||
|
||||
@staticmethod
|
||||
def load(filename):
|
||||
'''
|
||||
Load project from filename.
|
||||
'''
|
||||
try:
|
||||
import cPickle
|
||||
except ImportError:
|
||||
import _pickle as cPickle
|
||||
import pickle
|
||||
infile = open(filename, 'rb')
|
||||
project = cPickle.load(infile)
|
||||
project = pickle.load(infile)
|
||||
infile.close()
|
||||
project.location = filename
|
||||
print('Loaded %s' % filename)
|
||||
return project
|
||||
|
||||
57
README.md
57
README.md
@ -1,36 +1,54 @@
|
||||
# PyLoT
|
||||
|
||||
version: 0.2
|
||||
version: 0.3
|
||||
|
||||
The Python picking and Localisation Tool
|
||||
|
||||
This python library contains a graphical user interfaces for picking
|
||||
seismic phases. This software needs [ObsPy][ObsPy]
|
||||
and the PySide Qt4 bindings for python to be installed first.
|
||||
This python library contains a graphical user interfaces for picking seismic phases. This software needs [ObsPy][ObsPy]
|
||||
and the PySide2 Qt5 bindings for python to be installed first.
|
||||
|
||||
PILOT has originally been developed in Mathworks' MatLab. In order to
|
||||
distribute PILOT without facing portability problems, it has been decided
|
||||
to redevelop the software package in Python. The great work of the ObsPy
|
||||
group allows easy handling of a bunch of seismic data and PyLoT will
|
||||
benefit a lot compared to the former MatLab version.
|
||||
PILOT has originally been developed in Mathworks' MatLab. In order to distribute PILOT without facing portability
|
||||
problems, it has been decided to redevelop the software package in Python. The great work of the ObsPy group allows easy
|
||||
handling of a bunch of seismic data and PyLoT will benefit a lot compared to the former MatLab version.
|
||||
|
||||
The development of PyLoT is part of the joint research project MAGS2 and AlpArray.
|
||||
|
||||
## Installation
|
||||
|
||||
At the moment there is no automatic installation procedure available for PyLoT.
|
||||
Best way to install is to clone the repository and add the path to your Python path.
|
||||
At the moment there is no automatic installation procedure available for PyLoT. Best way to install is to clone the
|
||||
repository and add the path to your Python path.
|
||||
|
||||
It is highly recommended to use Anaconda for a simple creation of a Python installation using either the *pylot.yml* or the *requirements.txt* file found in the PyLoT root directory. First make sure that the *conda-forge* channel is available in your Anaconda installation:
|
||||
|
||||
conda config --add channels conda-forge
|
||||
|
||||
Afterwards run (from the PyLoT main directory where the files *requirements.txt* and *pylot.yml* are located)
|
||||
|
||||
conda create --name pylot_38 --file requirements.txt
|
||||
or
|
||||
|
||||
conda env create -f pylot.yml
|
||||
|
||||
to create a new Anaconda environment called "pylot_38".
|
||||
|
||||
Afterwards activate the environment by typing
|
||||
|
||||
conda activate pylot_38
|
||||
|
||||
#### Prerequisites:
|
||||
|
||||
In order to run PyLoT you need to install:
|
||||
|
||||
- python 2 or 3
|
||||
- Python 3
|
||||
- obspy
|
||||
- pyside2
|
||||
- pyqtgraph
|
||||
- cartopy
|
||||
|
||||
(the following are already dependencies of the above packages):
|
||||
- scipy
|
||||
- numpy
|
||||
- matplotlib
|
||||
- obspy
|
||||
- pyside
|
||||
- matplotlib <= 3.3.x
|
||||
|
||||
#### Some handwork:
|
||||
|
||||
@ -53,7 +71,8 @@ In the next step you have to copy some files to this directory:
|
||||
|
||||
cp path-to-pylot/inputs/pylot_global.in ~/.pylot/pylot.in
|
||||
|
||||
and some extra information on error estimates (just needed for reading old PILOT data) and the Richter magnitude scaling relation
|
||||
and some extra information on error estimates (just needed for reading old PILOT data) and the Richter magnitude scaling
|
||||
relation
|
||||
|
||||
cp path-to-pylot/inputs/PILOT_TimeErrors.in path-to-pylot/inputs/richter_scaling.data ~/.pylot/
|
||||
|
||||
@ -61,7 +80,6 @@ You may need to do some modifications to these files. Especially folder names sh
|
||||
|
||||
PyLoT has been tested on Mac OSX (10.11), Debian Linux 8 and on Windows 10.
|
||||
|
||||
|
||||
## Release notes
|
||||
|
||||
#### Features:
|
||||
@ -77,16 +95,13 @@ PyLoT has been tested on Mac OSX (10.11), Debian Linux 8 and on Windows 10.
|
||||
|
||||
#### Known issues:
|
||||
|
||||
- Sometimes an error might occur when using Qt
|
||||
|
||||
We hope to solve these with the next release.
|
||||
|
||||
## Staff
|
||||
|
||||
Original author(s): L. Kueperkoch, S. Wehling-Benatelli, M. Bischoff (PILOT)
|
||||
|
||||
Developer(s): S. Wehling-Benatelli, L. Kueperkoch, K. Olbert, M. Bischoff,
|
||||
C. Wollin, M. Rische, M. Paffrath
|
||||
Developer(s): S. Wehling-Benatelli, L. Kueperkoch, K. Olbert, M. Bischoff, C. Wollin, M. Rische, M. Paffrath
|
||||
|
||||
Others: A. Bruestle, T. Meier, W. Friederich
|
||||
|
||||
|
||||
@ -8,6 +8,7 @@ import datetime
|
||||
import glob
|
||||
import os
|
||||
import traceback
|
||||
|
||||
from obspy import read_events
|
||||
from obspy.core.event import ResourceIdentifier
|
||||
|
||||
@ -145,7 +146,7 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
|
||||
|
||||
exf = ['root', 'dpath', 'dbase']
|
||||
|
||||
if parameter['eventID'] is not '*' and fnames == 'None':
|
||||
if parameter['eventID'] != '*' and fnames == 'None':
|
||||
dsfields['eventID'] = parameter['eventID']
|
||||
exf.append('eventID')
|
||||
|
||||
@ -189,12 +190,12 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
|
||||
if not input_dict:
|
||||
# started in production mode
|
||||
datapath = datastructure.expandDataPath()
|
||||
if fnames == 'None' and parameter['eventID'] is '*':
|
||||
if fnames == 'None' and parameter['eventID'] == '*':
|
||||
# multiple event processing
|
||||
# read each event in database
|
||||
events = [event for event in glob.glob(os.path.join(datapath, '*')) if
|
||||
(os.path.isdir(event) and not event.endswith('EVENTS-INFO'))]
|
||||
elif fnames == 'None' and parameter['eventID'] is not '*' and not type(parameter['eventID']) == list:
|
||||
elif fnames == 'None' and parameter['eventID'] != '*' and not type(parameter['eventID']) == list:
|
||||
# single event processing
|
||||
events = glob.glob(os.path.join(datapath, parameter['eventID']))
|
||||
elif fnames == 'None' and type(parameter['eventID']) == list:
|
||||
@ -277,7 +278,7 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
|
||||
if not wfdat:
|
||||
print('Could not find station {}. STOP!'.format(station))
|
||||
return
|
||||
#wfdat = remove_underscores(wfdat)
|
||||
# wfdat = remove_underscores(wfdat)
|
||||
# trim components for each station to avoid problems with different trace starttimes for one station
|
||||
wfdat = check4gapsAndRemove(wfdat)
|
||||
wfdat = check4doubled(wfdat)
|
||||
|
||||
389
docs/gui.md
389
docs/gui.md
@ -44,15 +44,17 @@ This section describes how to use PyLoT graphically to view waveforms and create
|
||||
After opening PyLoT for the first time, the setup routine asks for the following information:
|
||||
|
||||
Questions:
|
||||
|
||||
1. Full Name
|
||||
2. Authority: Enter authority/institution name
|
||||
3. Format: Enter output format (*.xml, *.cnv, *.obs)
|
||||
|
||||
[//]: <> (TODO: explain what these things mean, where they are used)
|
||||
[//]: <> (TODO: explain what these things mean, where they are used)
|
||||
|
||||
## Main Screen
|
||||
|
||||
After entering the [information](#first-start), PyLoTs main window is shown. It defaults to a view of the [Waveform Plot](#waveform-plot), which starts empty.
|
||||
After entering the [information](#first-start), PyLoTs main window is shown. It defaults to a view of
|
||||
the [Waveform Plot](#waveform-plot), which starts empty.
|
||||
|
||||
<img src=images/gui/pylot-main-screen.png alt="Tune autopicks button" title="Tune autopicks button">
|
||||
|
||||
@ -61,24 +63,21 @@ Add trace data by [loading a project](#projects-and-events) or by [adding event
|
||||
### Waveform Plot
|
||||
|
||||
The waveform plot shows a trace list of all stations of an event.
|
||||
Click on any trace to open the stations [picking window](#picking-window), where you can review automatic and manual picks.
|
||||
Click on any trace to open the stations [picking window](#picking-window), where you can review automatic and manual
|
||||
picks.
|
||||
|
||||
<img src=images/gui/pylot-waveform-plot.png alt="A Waveform Plot showing traces of one event">
|
||||
|
||||
Above the traces the currently displayed event can be selected.
|
||||
In the bottom bar information about the trace under the mouse cursor is shown. This information includes the station name (station), the absolute UTC time (T) of the point under the mouse cursor and the relative time since the first trace start in seconds (t) as well as a trace count.
|
||||
Above the traces the currently displayed event can be selected. In the bottom bar information about the trace under the
|
||||
mouse cursor is shown. This information includes the station name (station), the absolute UTC time (T) of the point
|
||||
under the mouse cursor and the relative time since the first trace start in seconds (t) as well as a trace count.
|
||||
|
||||
#### Mouse view controls
|
||||
|
||||
Hold left mouse button and drag to pan view.
|
||||
|
||||
Hold right mouse button and
|
||||
Direction | Result
|
||||
--- | ---
|
||||
Move the mouse up | Increase amplitude scale
|
||||
Move the mouse down | Decrease amplitude scale
|
||||
Move the mouse right | Increase time scale
|
||||
Move the mouse left | Decrease time scale
|
||||
Hold right mouse button and Direction | Result --- | --- Move the mouse up | Increase amplitude scale Move the mouse
|
||||
down | Decrease amplitude scale Move the mouse right | Increase time scale Move the mouse left | Decrease time scale
|
||||
|
||||
Press right mouse button and click "View All" from the context menu to reset the view.
|
||||
|
||||
@ -86,81 +85,100 @@ Press right mouse button and click "View All" from the context menu to reset the
|
||||
|
||||
[//]: <> (Hack: We need these invisible spaces to add space to the first column, otherwise )
|
||||
|
||||
Icon | Description
|
||||
--- | ---
|
||||
<img src="../icons/newfile.png" alt="Create new project" width="64" height="64"> | Create a new project, for more information about projects see [Projects and Events](#projects-and-events).
|
||||
<img src="../icons/openproject.png" alt="Open project" width="64" height="64"> | Load a project file from disk.
|
||||
<img src="../icons/saveproject.png" alt="Save Project" width="64" height="64"> | Save all current events into an associated project file on disk. If there is no project file currently associated, you will be asked to create a new one.
|
||||
<img src="../icons/saveprojectas.png" alt="Save Project as" width="64" height="64"> | Save all current events into a new project file on disk. See [Saving projects](#saving-projects).
|
||||
<img src="../icons/add.png" alt="Add event data" width="64" height="64"> | Add event data by selecting directories containing waveforms. For more information see [Event folder structure](#event-folder-structure).
|
||||
<img src="../icons/openpick.png" alt="Load event information" width="64" height="64"> | Load picks/origins from disk into the currently displayed event. If a pick already exists for a station, the one from file will overwrite the existing one.
|
||||
<img src="../icons/openpicks.png" alt="Load information for all events" width="64" height="64"> | Load picks/origins for all events of the current project. PyLoT searches for files within the directory of the event and tries to load them for that event. For this function to work, the files containing picks/origins have to be named as described in [Event folder structure](#event-folder-structure). If a pick already exists for a station, the one from file will overwrite the existing one.
|
||||
<img src="../icons/savepicks.png" alt="Save picks" width="64" height="64"> | Save event information such as picks and origin to file. You will be asked to select a directory in which this information should be saved.
|
||||
<img src="../icons/openloc.png" alt="Load location information" width="64" height="64"> | Load location information from disk,
|
||||
<img src="../icons/Matlab_PILOT_icon.png" alt="Load legacy information" width="64" height="64"> | Load event information from a previous, MatLab based PILOT version.
|
||||
<img src="../icons/key_Z.png" alt="Display Z" width="64" height="64"> | Display Z component of streams in waveform plot.
|
||||
<img src="../icons/key_N.png" alt="Display N" width="64" height="64"> | Display N component of streams in waveform plot.
|
||||
<img src="../icons/key_E.png" alt="Display E" width="64" height="64"> | Display E component of streams in waveform plot.
|
||||
<img src="../icons/tune.png" alt="Tune Autopicker" width="64" height="64"> | Open the [Tune Autopicker window](#tuning).
|
||||
<img src="../icons/autopylot_button.png" alt="" width="64" height="64"> | Opens a window that allows starting the autopicker for all events ([Production run of the AutoPicker](#production-run-of-the-autopicker)).
|
||||
<img src="../icons/compare_button.png" alt="Comparison" width="64" height="64"> | Compare automatic and manual picks, only available if automatic and manual picks for an event exist. See [Comparison between automatic and manual picks](#comparison-between-automatic-and-manual-picks).
|
||||
<img src="../icons/locate_button.png" alt="Locate event" width="64" height="64"> | Run a location routine (NonLinLoc) as configured in the settings on the picks. See [Location determination](#location-determination).
|
||||
|
||||
| Icon | Description |
|
||||
|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| <img src="../icons/newfile.png" alt="Create new project" width="64" height="64"> | Create a new project, for more information about projects see [Projects and Events](#projects-and-events). |
|
||||
| <img src="../icons/openproject.png" alt="Open project" width="64" height="64"> | Load a project file from disk. |
|
||||
| <img src="../icons/saveproject.png" alt="Save Project" width="64" height="64"> | Save all current events into an associated project file on disk. If there is no project file currently associated, you will be asked to create a new one. |
|
||||
| <img src="../icons/saveprojectas.png" alt="Save Project as" width="64" height="64"> | Save all current events into a new project file on disk. See [Saving projects](#saving-projects). |
|
||||
| <img src="../icons/add.png" alt="Add event data" width="64" height="64"> | Add event data by selecting directories containing waveforms. For more information see [Event folder structure](#event-folder-structure). |
|
||||
| <img src="../icons/openpick.png" alt="Load event information" width="64" height="64"> | Load picks/origins from disk into the currently displayed event. If a pick already exists for a station, the one from file will overwrite the existing one. |
|
||||
| <img src="../icons/openpicks.png" alt="Load information for all events" width="64" height="64"> | Load picks/origins for all events of the current project. PyLoT searches for files within the directory of the event and tries to load them for that event. For this function to work, the files containing picks/origins have to be named as described in [Event folder structure](#event-folder-structure). If a pick already exists for a station, the one from file will overwrite the existing one. |
|
||||
| <img src="../icons/savepicks.png" alt="Save picks" width="64" height="64"> | Save event information such as picks and origin to file. You will be asked to select a directory in which this information should be saved. |
|
||||
| <img src="../icons/openloc.png" alt="Load location information" width="64" height="64"> | Load location information from disk, |
|
||||
| <img src="../icons/Matlab_PILOT_icon.png" alt="Load legacy information" width="64" height="64"> | Load event information from a previous, MatLab based PILOT version. |
|
||||
| <img src="../icons/key_Z.png" alt="Display Z" width="64" height="64"> | Display Z component of streams in waveform plot. |
|
||||
| <img src="../icons/key_N.png" alt="Display N" width="64" height="64"> | Display N component of streams in waveform plot. |
|
||||
| <img src="../icons/key_E.png" alt="Display E" width="64" height="64"> | Display E component of streams in waveform plot. |
|
||||
| <img src="../icons/tune.png" alt="Tune Autopicker" width="64" height="64"> | Open the [Tune Autopicker window](#tuning). |
|
||||
| <img src="../icons/autopylot_button.png" alt="" width="64" height="64"> | Opens a window that allows starting the autopicker for all events ([Production run of the AutoPicker](#production-run-of-the-autopicker)). |
|
||||
| <img src="../icons/compare_button.png" alt="Comparison" width="64" height="64"> | Compare automatic and manual picks, only available if automatic and manual picks for an event exist. See [Comparison between automatic and manual picks](#comparison-between-automatic-and-manual-picks). |
|
||||
| <img src="../icons/locate_button.png" alt="Locate event" width="64" height="64"> | Run a location routine (NonLinLoc) as configured in the settings on the picks. See [Location determination](#location-determination). |
|
||||
|
||||
### Array Map
|
||||
|
||||
The array map will display a color diagram to allow a visual check of the consistency of picks across multiple stations. This works by calculating the time difference of every onset to the earliest onset. Then isolines are drawn between stations with the same time difference and the areas between isolines are colored.
|
||||
The result should resemble a color gradient as the wavefront rolls over the network area. Stations where picks are earlier/later than their neighbours can be reviewed by clicking on them, which opens the [picking window](#picking-window).
|
||||
The array map will display a color diagram to allow a visual check of the consistency of picks across multiple stations.
|
||||
This works by calculating the time difference of every onset to the earliest onset. Then isolines are drawn between
|
||||
stations with the same time difference and the areas between isolines are colored.
|
||||
The result should resemble a color gradient as the wavefront rolls over the network area. Stations where picks are
|
||||
earlier/later than their neighbours can be reviewed by clicking on them, which opens
|
||||
the [picking window](#picking-window).
|
||||
|
||||
Above the Array Map the picks that are used to create the map can be customized.
|
||||
The phase of picks that should be used can be selected, which allows checking the consistency of the P- and S-phase separately.
|
||||
Additionally the pick type can be set to manual, automatic or hybrid, meaning display only manual picks, automatic picks or only display automatic picks for stations where there are no manual ones.
|
||||
Above the Array Map the picks that are used to create the map can be customized. The phase of picks that should be used
|
||||
can be selected, which allows checking the consistency of the P- and S-phase separately. Additionally the pick type can
|
||||
be set to manual, automatic or hybrid, meaning display only manual picks, automatic picks or only display automatic
|
||||
picks for stations where there are no manual ones.
|
||||
|
||||
|
||||
*Array Map for an event at the Northern Mid Atlantic Ridge, between North Africa and Mexico (Lat. 22.58, Lon. -45.11). The wavefront moved from west to east over the network area (Alps and Balcan region), with the earliest onsets in blue in the west.*
|
||||
*Array Map for an event at the Northern Mid Atlantic Ridge, between North Africa and Mexico (Lat. 22.58, Lon. -45.11).
|
||||
The wavefront moved from west to east over the network area (Alps and Balcan region), with the earliest onsets in blue
|
||||
in the west.*
|
||||
|
||||
To be able to display an array map PyLoT needs to load an inventory file, where the metadata of seismic stations is kept. For more information see [Metadata](#adding-metadata). Additionally automatic or manual picks need to exist for the current event.
|
||||
To be able to display an array map PyLoT needs to load an inventory file, where the metadata of seismic stations is
|
||||
kept. For more information see [Metadata](#adding-metadata). Additionally automatic or manual picks need to exist for
|
||||
the current event.
|
||||
|
||||
### Eventlist
|
||||
|
||||
The eventlist displays event parameters. The displayed parameters are saved in the .xml file in the event folder. Events can be deleted from the project by pressing the red X in the leftmost column of the corresponding event.
|
||||
The eventlist displays event parameters. The displayed parameters are saved in the .xml file in the event folder. Events
|
||||
can be deleted from the project by pressing the red X in the leftmost column of the corresponding event.
|
||||
|
||||
<img src="images/gui/eventlist.png" alt="Eventlist">
|
||||
|
||||
Column | Description
|
||||
--- | ---
|
||||
Event | Full path to the events folder.
|
||||
Time | Time of event.
|
||||
Lat | Latitude in degrees of event location.
|
||||
Lon | Longitude in degrees of event location.
|
||||
Depth | Depth in km of event.
|
||||
Mag | Magnitude of event.
|
||||
[N] MP | Number of manual picks.
|
||||
[N] AP | Number of automatic picks.
|
||||
Tuning Set | Select whether this event is a Tuning event. See [Automatic Picking](#automatic-picking).
|
||||
Test Set | Select whether this event is a Test event. See [Automatic Picking](#automatic-picking).
|
||||
Notes | Free form text field for notes regarding this event. Text will be saved in the notes.txt file in the event folder.
|
||||
| Column | Description |
|
||||
|------------|--------------------------------------------------------------------------------------------------------------------|
|
||||
| Event | Full path to the events folder. |
|
||||
| Time | Time of event. |
|
||||
| Lat | Latitude in degrees of event location. |
|
||||
| Lon | Longitude in degrees of event location. |
|
||||
| Depth | Depth in km of event. |
|
||||
| Mag | Magnitude of event. |
|
||||
| [N] MP | Number of manual picks. |
|
||||
| [N] AP | Number of automatic picks. |
|
||||
| Tuning Set | Select whether this event is a Tuning event. See [Automatic Picking](#automatic-picking). |
|
||||
| Test Set | Select whether this event is a Test event. See [Automatic Picking](#automatic-picking). |
|
||||
| Notes | Free form text field for notes regarding this event. Text will be saved in the notes.txt file in the event folder. |
|
||||
|
||||
## Usage
|
||||
|
||||
### Projects and Events
|
||||
|
||||
PyLoT uses projects to categorize different seismic data. A project consists of one or multiple events. Events contain seismic traces from one or multiple stations. An event also contains further information, e.g. origin time, source parameters and automatic as well as manual picks.
|
||||
Projects are used to group events which should be analysed together. A project could contain all events from a specific region within a timeframe of interest or all recorded events of a seismological experiment.
|
||||
PyLoT uses projects to categorize different seismic data. A project consists of one or multiple events. Events contain
|
||||
seismic traces from one or multiple stations. An event also contains further information, e.g. origin time, source
|
||||
parameters and automatic as well as manual picks. Projects are used to group events which should be analysed together. A
|
||||
project could contain all events from a specific region within a timeframe of interest or all recorded events of a
|
||||
seismological experiment.
|
||||
|
||||
### Event folder structure
|
||||
|
||||
PyLoT expects the following folder structure for seismic data:
|
||||
|
||||
* Every event should be in it's own folder with the following naming scheme for the folders:
|
||||
``e[id].[doy].[yy]``, where ``[id]`` is a four-digit numerical id increasing from 0001, ``[doy]`` the three digit day of year and ``[yy]`` the last two digits of the year of the event. This structure has to be created by the user of PyLoT manually.
|
||||
``e[id].[doy].[yy]``, where ``[id]`` is a four-digit numerical id increasing from 0001, ``[doy]`` the three digit day
|
||||
of year and ``[yy]`` the last two digits of the year of the event. This structure has to be created by the user of
|
||||
PyLoT manually.
|
||||
* These folders should contain the seismic data for their event as ``.mseed`` or other supported filetype
|
||||
* All automatic and manual picks should be in an ``.xml`` file in their event folder. PyLoT saves picks in this file. This file does not have to be added manually unless there are picks to be imported. The format used to save picks is QUAKEML.
|
||||
Picks are saved in a file with the same filename as the event folder with ``PyLoT_`` prepended.
|
||||
* The file ``notes.txt`` is used for saving analysts comments. Everything saved here will be displayed in the 'Notes' column of the eventlist.
|
||||
* All automatic and manual picks should be in an ``.xml`` file in their event folder. PyLoT saves picks in this file.
|
||||
This file does not have to be added manually unless there are picks to be imported. The format used to save picks is
|
||||
QUAKEML.
|
||||
Picks are saved in a file with the same filename as the event folder with ``PyLoT_`` prepended.
|
||||
* The file ``notes.txt`` is used for saving analysts comments. Everything saved here will be displayed in the 'Notes'
|
||||
column of the eventlist.
|
||||
|
||||
### Loading event information from CSV file
|
||||
|
||||
Event information can be saved in a ``.csv`` file located in the rootpath. The file is made from one header line, which is followed by one or multiple data lines. Values are separated by comma, while a dot is used as a decimal separator.
|
||||
Event information can be saved in a ``.csv`` file located in the rootpath. The file is made from one header line, which
|
||||
is followed by one or multiple data lines. Values are separated by comma, while a dot is used as a decimal separator.
|
||||
This information is then shown in the table in the [Eventlist tab](#Eventlist).
|
||||
|
||||
One example header and data line is shown below.
|
||||
@ -169,50 +187,63 @@ One example header and data line is shown below.
|
||||
|
||||
The meaning of the header entries is:
|
||||
|
||||
Header | description
|
||||
--- | ---
|
||||
event | Event id, has to be the same as the folder name in which waveform data for this event is kept.
|
||||
Data | Origin date of the event, format DD/MM/YY or DD/MM/YYYY.
|
||||
Time | Origin time of the event. Format HH:MM:SS.
|
||||
Lat, Long | Origin latitude and longitude in decimal degrees.
|
||||
Region | Flinn-Engdahl region name.
|
||||
Basis Lat, Basis Lon | Latitude and longitude of the basis of the station network in decimal degrees.
|
||||
Distance [km] | Distance from origin coordinates to basis coordinates in km.
|
||||
Distance [rad] | Distance from origin coordinates to basis coordinates in rad.
|
||||
|
||||
| Header | description |
|
||||
|----------------------|------------------------------------------------------------------------------------------------|
|
||||
| event | Event id, has to be the same as the folder name in which waveform data for this event is kept. |
|
||||
| Data | Origin date of the event, format DD/MM/YY or DD/MM/YYYY. |
|
||||
| Time | Origin time of the event. Format HH:MM:SS. |
|
||||
| Lat, Long | Origin latitude and longitude in decimal degrees. |
|
||||
| Region | Flinn-Engdahl region name. |
|
||||
| Basis Lat, Basis Lon | Latitude and longitude of the basis of the station network in decimal degrees. |
|
||||
| Distance [km] | Distance from origin coordinates to basis coordinates in km. |
|
||||
| Distance [rad] | Distance from origin coordinates to basis coordinates in rad. |
|
||||
|
||||
### Adding events to project
|
||||
|
||||
PyLoT GUI starts with an empty project. To add events, use the add event data button. Select one or multiple folders containing events.
|
||||
PyLoT GUI starts with an empty project. To add events, use the add event data button. Select one or multiple folders
|
||||
containing events.
|
||||
|
||||
[//]: <> (TODO: explain _Directories: Root path, Data path, Database path_)
|
||||
|
||||
### Saving projects
|
||||
|
||||
Save the current project from the menu with File->Save project or File->Save project as.
|
||||
PyLoT uses ``.plp`` files to save project information. This file format is not interchangeable between different versions of Python interpreters.
|
||||
Saved projects contain the automatic and manual picks. Seismic trace data is not included into the ``.plp`` file, but read from its location used when saving the file.
|
||||
Save the current project from the menu with File->Save project or File->Save project as. PyLoT uses ``.plp`` files to
|
||||
save project information. This file format is not interchangeable between different versions of Python interpreters.
|
||||
Saved projects contain the automatic and manual picks. Seismic trace data is not included into the ``.plp`` file, but
|
||||
read from its location used when saving the file.
|
||||
|
||||
### Adding metadata
|
||||
|
||||
[//]: <> (TODO: Add picture of metadata "manager" when it is done)
|
||||
|
||||
PyLoT can handle ``.dless``, ``.xml``, ``.resp`` and ``.dseed`` file formats for Metadata. Metadata files stored on disk can be added to a project by clicking *Edit*->*Manage Inventories*. This opens up a window where the folders which contain metadata files can be selected. PyLoT will then search these files for the station names when it needs the information.
|
||||
PyLoT can handle ``.dless``, ``.xml``, ``.resp`` and ``.dseed`` file formats for Metadata. Metadata files stored on disk
|
||||
can be added to a project by clicking *Edit*->*Manage Inventories*. This opens up a window where the folders which
|
||||
contain metadata files can be selected. PyLoT will then search these files for the station names when it needs the
|
||||
information.
|
||||
|
||||
# Picking
|
||||
|
||||
PyLoTs automatic and manual pick determination works as following:
|
||||
* Using certain parameters, a first initial/coarse pick is determined. The first manual pick is determined by visual review of the whole waveform and selection of the most likely onset by the analyst. The first automatic pick is determined by calculation of a characteristic function (CF) for the seismic trace. When a wave arrives, the CFs properties change, which is determined as the signals onset.
|
||||
* Afterwards, a refined set of parameters is applied to a small part of the waveform around the initial onset. For manual picks this means a closer view of the trace, for automatic picks this is done by a recalculated CF with different parameters.
|
||||
|
||||
* Using certain parameters, a first initial/coarse pick is determined. The first manual pick is determined by visual
|
||||
review of the whole waveform and selection of the most likely onset by the analyst. The first automatic pick is
|
||||
determined by calculation of a characteristic function (CF) for the seismic trace. When a wave arrives, the CFs
|
||||
properties change, which is determined as the signals onset.
|
||||
* Afterwards, a refined set of parameters is applied to a small part of the waveform around the initial onset. For
|
||||
manual picks this means a closer view of the trace, for automatic picks this is done by a recalculated CF with
|
||||
different parameters.
|
||||
* This second picking phase results in the precise pick, which is treated as the onset time.
|
||||
|
||||
## Manual Picking
|
||||
|
||||
To create manual picks, you will need to open or create a project that contains seismic trace data (see [Adding events to projects](#adding-events-to-project)). Click on a trace to open the [Picking window](#picking-window).
|
||||
To create manual picks, you will need to open or create a project that contains seismic trace data (
|
||||
see [Adding events to projects](#adding-events-to-project)). Click on a trace to open
|
||||
the [Picking window](#picking-window).
|
||||
|
||||
### Picking window
|
||||
|
||||
Open the picking window of a station by leftclicking on any trace in the waveform plot. Here you can create manual picks for the selected station.
|
||||
Open the picking window of a station by leftclicking on any trace in the waveform plot. Here you can create manual picks
|
||||
for the selected station.
|
||||
|
||||
<img src="images/gui/picking/pickwindow.png" alt="Picking window">
|
||||
|
||||
@ -220,24 +251,24 @@ Open the picking window of a station by leftclicking on any trace in the wavefor
|
||||
|
||||
#### Picking Window Settings
|
||||
|
||||
Icon | Shortcut | Menu Alternative | Description
|
||||
---|---|---|---
|
||||
<img src="../icons/filter_p.png" alt="Filter P" width="64" height="64"> | p | Filter->Apply P Filter | Filter all channels according to the options specified in Filter parameter, P Filter section.
|
||||
<img src="../icons/filter_s.png" alt="Filter S" width="64" height="64"> | s | Filter->Apply S Filter | Filter all channels according to the options specified in Filter parameter, S Filter section.
|
||||
<img src="../icons/key_A.png" alt="Filter Automatically" width="64" height="64"> | Ctrl + a | Filter->Automatic Filtering | If enabled, automatically select the correct filter option (P, S) depending on the selected phase to be picked.
|
||||
 | 1 (P) or 5 (S) | Picks->P or S | Select phase to pick. If Automatic Filtering is enabled, this will apply the appropriate filter depending on the phase.
|
||||
 | - | - | Zoom into waveform.
|
||||
 | - | - | Reset zoom to default view.
|
||||
 | - | - | Delete all manual picks on this station.
|
||||
 | - | - | Click this button and then the picked phase to rename it.
|
||||
 | - | - | If checked, after accepting the manual picks for this station with 'OK', the picking window for the next station will be opened. This option is useful for fast manual picking of a complete event.
|
||||
Estimated onsets | - | - | Show the theoretical onsets for this station. Needs metadata and origin information.
|
||||
Compare to channel | - | - | Select a data channel to compare against. The selected channel will be displayed in the picking window behind every channel allowing the analyst to visually compare signal correlation between different channels.
|
||||
Scaling | - | - | Individual means every channel is scaled to its own maximum. If a channel is selected here, all channels will be scaled relatively to this channel.
|
||||
| Icon | Shortcut | Menu Alternative | Description |
|
||||
|----------------------------------------------------------------------------------|----------------|-----------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| <img src="../icons/filter_p.png" alt="Filter P" width="64" height="64"> | p | Filter->Apply P Filter | Filter all channels according to the options specified in Filter parameter, P Filter section. |
|
||||
| <img src="../icons/filter_s.png" alt="Filter S" width="64" height="64"> | s | Filter->Apply S Filter | Filter all channels according to the options specified in Filter parameter, S Filter section. |
|
||||
| <img src="../icons/key_A.png" alt="Filter Automatically" width="64" height="64"> | Ctrl + a | Filter->Automatic Filtering | If enabled, automatically select the correct filter option (P, S) depending on the selected phase to be picked. |
|
||||
|  | 1 (P) or 5 (S) | Picks->P or S | Select phase to pick. If Automatic Filtering is enabled, this will apply the appropriate filter depending on the phase. |
|
||||
|  | - | - | Zoom into waveform. |
|
||||
|  | - | - | Reset zoom to default view. |
|
||||
|  | - | - | Delete all manual picks on this station. |
|
||||
|  | - | - | Click this button and then the picked phase to rename it. |
|
||||
|  | - | - | If checked, after accepting the manual picks for this station with 'OK', the picking window for the next station will be opened. This option is useful for fast manual picking of a complete event. |
|
||||
| Estimated onsets | - | - | Show the theoretical onsets for this station. Needs metadata and origin information. |
|
||||
| Compare to channel | - | - | Select a data channel to compare against. The selected channel will be displayed in the picking window behind every channel allowing the analyst to visually compare signal correlation between different channels. |
|
||||
| Scaling | - | - | Individual means every channel is scaled to its own maximum. If a channel is selected here, all channels will be scaled relatively to this channel. |
|
||||
|
||||
Menu Command | Shortcut | Description
|
||||
---|---|---
|
||||
P Channels and S Channels | - | Select which channels should be treated as P or S channels during picking. When picking a phase, only the corresponding channels will be shown during the precise pick. Normally, the Z channel should be selected for the P phase and the N and E channel for the S phase.
|
||||
| Menu Command | Shortcut | Description |
|
||||
|---------------------------|----------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| P Channels and S Channels | - | Select which channels should be treated as P or S channels during picking. When picking a phase, only the corresponding channels will be shown during the precise pick. Normally, the Z channel should be selected for the P phase and the N and E channel for the S phase. |
|
||||
|
||||
### Filtering
|
||||
|
||||
@ -245,105 +276,167 @@ Access the Filter options by pressing Ctrl+f on the Waveform plot or by the menu
|
||||
|
||||
<img src=images/gui/pylot-filter-options.png>
|
||||
|
||||
Here you are able to select filter type, order and frequencies for the P and S pick separately. These settings are used in the GUI for displaying the filtered waveform data and during manual picking. The values used by PyLoT for automatic picking are displayed next to the manual values. They can be changed in the [Tune Autopicker dialog](#tuning).
|
||||
A green value automatic value means the automatic and manual filter parameter is configured the same, red means they are configured differently.
|
||||
By toggling the "Overwrite filteroptions" checkmark you can set whether the manual precise/second pick uses the filter settings for the automatic picker (unchecked) or whether it uses the filter options in this dialog (checked).
|
||||
To guarantee consistent picking results between automatic and manual picking it is recommended to use the same filter settings for the determination of automatic and manual picks.
|
||||
Here you are able to select filter type, order and frequencies for the P and S pick separately. These settings are used
|
||||
in the GUI for displaying the filtered waveform data and during manual picking. The values used by PyLoT for automatic
|
||||
picking are displayed next to the manual values. They can be changed in the [Tune Autopicker dialog](#tuning).
|
||||
A green value automatic value means the automatic and manual filter parameter is configured the same, red means they are
|
||||
configured differently. By toggling the "Overwrite filteroptions" checkmark you can set whether the manual
|
||||
precise/second pick uses the filter settings for the automatic picker (unchecked) or whether it uses the filter options
|
||||
in this dialog (checked). To guarantee consistent picking results between automatic and manual picking it is recommended
|
||||
to use the same filter settings for the determination of automatic and manual picks.
|
||||
|
||||
### Export and Import of manual picks
|
||||
|
||||
#### Export
|
||||
|
||||
After the creation of manual picks they can either be saved in the project file (see [Saving projects](#saving-projects)). Alternatively the picks can be exported by pressing the <img src="../icons/savepicks.png" alt="Save event information button" title="Save picks button" height=24 width=24> button above the waveform plot or in the menu File->Save event information (shortcut Ctrl+p). Select the event directory in which to save the file. The filename will be ``PyLoT_[event_folder_name].[filetype selected during first startup]``.
|
||||
You can rename and copy this file, but PyLoT will then no longer be able to automatically recognize the correct picks for an event and the file will have to be manually selected when loading.
|
||||
After the creation of manual picks they can either be saved in the project file (
|
||||
see [Saving projects](#saving-projects)). Alternatively the picks can be exported by pressing
|
||||
the <img src="../icons/savepicks.png" alt="Save event information button" title="Save picks button" height=24 width=24>
|
||||
button above the waveform plot or in the menu File->Save event information (shortcut Ctrl+p). Select the event directory
|
||||
in which to save the file. The filename will be ``PyLoT_[event_folder_name].[filetype selected during first startup]``
|
||||
.
|
||||
You can rename and copy this file, but PyLoT will then no longer be able to automatically recognize the correct picks
|
||||
for an event and the file will have to be manually selected when loading.
|
||||
|
||||
#### Import
|
||||
|
||||
To import previously saved picks press the <img src="../icons/openpick.png" alt="Load event information button" width="24" height="24"> button and select the file to load. You will be asked to save the current state of your project if you have not done so before. You can continue without saving by pressing "Discard". This does not delete any information from your project, it just means that no project file is saved before the changes of importing picks are applied.
|
||||
PyLoT will automatically load files named after the scheme it uses when saving picks, described in the paragraph above. If it can't find any matching files, a file dialogue will open and you can select the file you wish to load.
|
||||
To import previously saved picks press
|
||||
the <img src="../icons/openpick.png" alt="Load event information button" width="24" height="24"> button and select the
|
||||
file to load. You will be asked to save the current state of your project if you have not done so before. You can
|
||||
continue without saving by pressing "Discard". This does not delete any information from your project, it just means
|
||||
that no project file is saved before the changes of importing picks are applied. PyLoT will automatically load files
|
||||
named after the scheme it uses when saving picks, described in the paragraph above. If it can't find any matching files,
|
||||
a file dialogue will open and you can select the file you wish to load.
|
||||
|
||||
If you see a warning "Mismatch in event identifiers" and are asked whether to continue loading the picks, this means that PyLoT doesn't recognize the picks in the file as belonging to this specific event. They could have either been saved under a different installation of PyLoT but with the same waveform data, which means they are still compatible and you can continue loading them. Or they could be picks from a different event, in which case loading them is not recommended.
|
||||
If you see a warning "Mismatch in event identifiers" and are asked whether to continue loading the picks, this means
|
||||
that PyLoT doesn't recognize the picks in the file as belonging to this specific event. They could have either been
|
||||
saved under a different installation of PyLoT but with the same waveform data, which means they are still compatible and
|
||||
you can continue loading them. Or they could be picks from a different event, in which case loading them is not
|
||||
recommended.
|
||||
|
||||
## Automatic Picking
|
||||
|
||||
|
||||
The general workflow for automatic picking is as following:
|
||||
- After setting up the project by loading waveforms and optionally metadata, the right parameters for the autopicker have to be determined
|
||||
|
||||
- After setting up the project by loading waveforms and optionally metadata, the right parameters for the autopicker
|
||||
have to be determined
|
||||
- This [tuning](#tuning) is done for single stations with immediate graphical feedback of all picking results
|
||||
- Afterwards the autopicker can be run for all or a subset of events from the project
|
||||
|
||||
For automatic picking PyLoT discerns between tune and test events, which the user has to set as such. Tune events are used to calibrate the autopicking algorithm, test events are then used to test the calibration. The purpose of that is controlling whether the parameters found during tuning are able to reliably pick the "unknown" test events.
|
||||
If this behaviour is not desired and all events should be handled the same, dont mark any events. Since this is just a way to group events to compare the picking results, nothing else will change.
|
||||
For automatic picking PyLoT discerns between tune and test events, which the user has to set as such. Tune events are
|
||||
used to calibrate the autopicking algorithm, test events are then used to test the calibration. The purpose of that is
|
||||
controlling whether the parameters found during tuning are able to reliably pick the "unknown" test events.
|
||||
If this behaviour is not desired and all events should be handled the same, dont mark any events. Since this is just a
|
||||
way to group events to compare the picking results, nothing else will change.
|
||||
|
||||
### Tuning
|
||||
|
||||
Tuning describes the process of adjusting the autopicker settings to the characteristics of your data set. To do this in PyLoT, use the <img src=../icons/tune.png height=24 alt="Tune autopicks button" title="Tune autopicks button"> button to open the Tune Autopicker.
|
||||
Tuning describes the process of adjusting the autopicker settings to the characteristics of your data set. To do this in
|
||||
PyLoT, use the <img src=../icons/tune.png height=24 alt="Tune autopicks button" title="Tune autopicks button"> button to
|
||||
open the Tune Autopicker.
|
||||
|
||||
<img src=images/gui/tuning/tune_autopicker.png>
|
||||
|
||||
View of a station in the Tune Autopicker window.
|
||||
|
||||
1. Select the event to be displayed and processed.
|
||||
2. Select the station from the event.
|
||||
3. To pick the currently displayed trace, click the <img src=images/gui/tuning/autopick_trace_button.png alt="Pick trace button" title="Autopick trace button" height=16> button.
|
||||
4. These tabs are used to select the current view. __Traces Plot__ contains a plot of the stations traces, where manual picks can be created/edited. __Overview__ contains graphical results of the automatic picking process. The __P and S tabs__ contain the automatic picking results of the P and S phase, while __log__ contains a useful text output of automatic picking.
|
||||
5. These buttons are used to load/save/reset settings for automatic picking. The parameters can be saved in PyLoT input files, which have the file ending *.in*. They are human readable text files, which can also be edited by hand. Saving the parameters allows you to load them again later, even on different machines.
|
||||
6. These menus control the behaviour of the creation of manual picks from the Tune Autopicker window. Picks allows to select the phase for which a manual pick should be created, Filter allows to filter waveforms and edit the filter parameters. P-Channels and S-Channels allow to select the channels that should be displayed when creating a manual P or S pick.
|
||||
7. This menu is the same as in the [Picking Window](#picking-window-settings), with the exception of the __Manual Onsets__ options. The __Manual Onsets__ buttons accepts or reject the manual picks created in the Tune Autopicker window, pressing accept adds them to the manual picks for the event, while reject removes them.
|
||||
3. To pick the currently displayed trace, click
|
||||
the <img src=images/gui/tuning/autopick_trace_button.png alt="Pick trace button" title="Autopick trace button" height=16>
|
||||
button.
|
||||
4. These tabs are used to select the current view. __Traces Plot__ contains a plot of the stations traces, where manual
|
||||
picks can be created/edited. __Overview__ contains graphical results of the automatic picking process. The __P and S
|
||||
tabs__ contain the automatic picking results of the P and S phase, while __log__ contains a useful text output of
|
||||
automatic picking.
|
||||
5. These buttons are used to load/save/reset settings for automatic picking. The parameters can be saved in PyLoT input
|
||||
files, which have the file ending *.in*. They are human readable text files, which can also be edited by hand. Saving
|
||||
the parameters allows you to load them again later, even on different machines.
|
||||
6. These menus control the behaviour of the creation of manual picks from the Tune Autopicker window. Picks allows to
|
||||
select the phase for which a manual pick should be created, Filter allows to filter waveforms and edit the filter
|
||||
parameters. P-Channels and S-Channels allow to select the channels that should be displayed when creating a manual P
|
||||
or S pick.
|
||||
7. This menu is the same as in the [Picking Window](#picking-window-settings), with the exception of the __Manual
|
||||
Onsets__ options. The __Manual Onsets__ buttons accepts or reject the manual picks created in the Tune Autopicker
|
||||
window, pressing accept adds them to the manual picks for the event, while reject removes them.
|
||||
8. The traces plot in the centre allows creating manual picks and viewing the waveforms.
|
||||
9. The parameters which influence the autopicking result are in the Main settings and Advanced settings tabs on the left side. For a description of all the parameters see the [tuning documentation](tuning.md).
|
||||
9. The parameters which influence the autopicking result are in the Main settings and Advanced settings tabs on the left
|
||||
side. For a description of all the parameters see the [tuning documentation](tuning.md).
|
||||
|
||||
### Production run of the autopicker
|
||||
|
||||
After the settings used during tuning give the desired results, the autopicker can be used on the complete dataset. To invoke the autopicker on the whole set of events, click the <img src=../icons/autopylot_button.png alt="Autopick" title="Autopick" height=32> button.
|
||||
After the settings used during tuning give the desired results, the autopicker can be used on the complete dataset. To
|
||||
invoke the autopicker on the whole set of events, click
|
||||
the <img src=../icons/autopylot_button.png alt="Autopick" title="Autopick" height=32> button.
|
||||
|
||||
### Evaluation of automatic picks
|
||||
|
||||
PyLoT has two internal consistency checks for automatic picks that were determined for an event:
|
||||
|
||||
1. Jackknife check
|
||||
2. Wadati check
|
||||
|
||||
#### 1. Jackknife check
|
||||
|
||||
The jackknife test in PyLoT checks the consistency of automatically determined P-picks by checking the statistical variance of the picks. The variance of all P-picks is calculated and compared to the variance of subsets, in which one pick is removed.
|
||||
The idea is, that picks that are close together in time should not influence the estimation of the variance much, while picks whose positions deviates from the norm influence the variance to a greater extent. If the estimated variance of a subset with a pick removed differs to much from the estimated variance of all picks, the pick that was removed from the subset will be marked as invalid.
|
||||
The factor by which picks are allowed to skew from the estimation of variance can be configured, it is called *jackfactor*, see [here](tuning.md#Pick-quality-control).
|
||||
The jackknife test in PyLoT checks the consistency of automatically determined P-picks by checking the statistical
|
||||
variance of the picks. The variance of all P-picks is calculated and compared to the variance of subsets, in which one
|
||||
pick is removed.
|
||||
The idea is, that picks that are close together in time should not influence the estimation of the variance much, while
|
||||
picks whose positions deviates from the norm influence the variance to a greater extent. If the estimated variance of a
|
||||
subset with a pick removed differs to much from the estimated variance of all picks, the pick that was removed from the
|
||||
subset will be marked as invalid.
|
||||
The factor by which picks are allowed to skew from the estimation of variance can be configured, it is called *
|
||||
jackfactor*, see [here](tuning.md#Pick-quality-control).
|
||||
|
||||
Additionally, the deviation of picks from the median is checked. For that, the median of all P-picks that passed the Jackknife test is calculated. Picks whose onset times deviate from the mean onset time by more than the *mdttolerance* are marked as invalid.
|
||||
Additionally, the deviation of picks from the median is checked. For that, the median of all P-picks that passed the
|
||||
Jackknife test is calculated. Picks whose onset times deviate from the mean onset time by more than the *mdttolerance*
|
||||
are marked as invalid.
|
||||
|
||||
<img src=images/gui/jackknife_plot.png title="Jackknife/Median test diagram">
|
||||
|
||||
*The result of both tests (Jackknife and Median) is shown in a diagram afterwards. The onset time is plotted against a running number of stations. Picks that failed either the Jackknife or the median test are colored red. The median is plotted as a green line.*
|
||||
*The result of both tests (Jackknife and Median) is shown in a diagram afterwards. The onset time is plotted against a
|
||||
running number of stations. Picks that failed either the Jackknife or the median test are colored red. The median is
|
||||
plotted as a green line.*
|
||||
|
||||
The Jackknife and median check are suitable to check for picks that are outside of the expected time window, for example, when a wrong phase was picked. It won't recognize picks that are in close proximity to the right onset which are just slightly to late/early.
|
||||
The Jackknife and median check are suitable to check for picks that are outside of the expected time window, for
|
||||
example, when a wrong phase was picked. It won't recognize picks that are in close proximity to the right onset which
|
||||
are just slightly to late/early.
|
||||
|
||||
#### 2. Wadati check
|
||||
|
||||
The Wadati check checks the consistency of S picks. For this the SP-time, the time difference between S and P onset is plotted against the P onset time. A line is fitted to the points, which minimizes the error. Then the deviation of single picks to this line is checked. If the deviation in seconds is above the *wdttolerance* parameter ([see here](tuning.md#Pick-quality-control)), the pick is marked as invalid.
|
||||
The Wadati check checks the consistency of S picks. For this the SP-time, the time difference between S and P onset is
|
||||
plotted against the P onset time. A line is fitted to the points, which minimizes the error. Then the deviation of
|
||||
single picks to this line is checked. If the deviation in seconds is above the *wdttolerance*
|
||||
parameter ([see here](tuning.md#Pick-quality-control)), the pick is marked as invalid.
|
||||
|
||||
<img src=images/gui/wadati_plot.png title="Output diagram of Wadati check">
|
||||
|
||||
*The Wadati plot in PyLoT shows the SP onset time difference over the P onset time. A first line is fitted (black). All picks which deviate to much from this line are marked invalid (red). Then a second line is fitted which excludes the invalid picks. From this lines slope, the ratio of P and S wave velocity is determined.*
|
||||
*The Wadati plot in PyLoT shows the SP onset time difference over the P onset time. A first line is fitted (black). All
|
||||
picks which deviate to much from this line are marked invalid (red). Then a second line is fitted which excludes the
|
||||
invalid picks. From this lines slope, the ratio of P and S wave velocity is determined.*
|
||||
|
||||
### Comparison between automatic and manual picks
|
||||
|
||||
Every pick in PyLoT consists of an earliest possible, latest possible and most likely onset time.
|
||||
The earliest and latest possible onset time characterize the uncertainty of a pick.
|
||||
This approach is described in Diel, Kissling and Bormann (2012) - Tutorial for consistent phase picking at local to regional distances.
|
||||
These times are represented as a Probability Density Function (PDF) for every pick.
|
||||
The PDF is implemented as two exponential distributions around the most likely onset as the expected value.
|
||||
Every pick in PyLoT consists of an earliest possible, latest possible and most likely onset time. The earliest and
|
||||
latest possible onset time characterize the uncertainty of a pick. This approach is described in Diel, Kissling and
|
||||
Bormann (2012) - Tutorial for consistent phase picking at local to regional distances. These times are represented as a
|
||||
Probability Density Function (PDF) for every pick. The PDF is implemented as two exponential distributions around the
|
||||
most likely onset as the expected value.
|
||||
|
||||
To compare two single picks, their PDFs are cross correlated to create a new PDF.
|
||||
This corresponds to the subtraction of the automatic pick from the manual pick.
|
||||
To compare two single picks, their PDFs are cross correlated to create a new PDF. This corresponds to the subtraction of
|
||||
the automatic pick from the manual pick.
|
||||
|
||||
<img src=images/gui/comparison/comparison_pdf.png title="Comparison between automatic and manual pick">
|
||||
|
||||
*Comparison between an automatic and a manual pick for a station in PyLoT by comparing their PDFs.*
|
||||
*The upper plot shows the difference between the two single picks that are shown in the lower plot.*
|
||||
*The difference is implemented as a cross correlation between the two PDFs. and results in a new PDF, the comparison PDF.*
|
||||
*The expected value of the comparison PDF corresponds to the time distance between the automatic and manual picks most likely onset.*
|
||||
*The standard deviation corresponds to the combined uncertainty.*
|
||||
*Comparison between an automatic and a manual pick for a station in PyLoT by comparing their PDFs.*
|
||||
*The upper plot shows the difference between the two single picks that are shown in the lower plot.*
|
||||
*The difference is implemented as a cross correlation between the two PDFs. and results in a new PDF, the comparison
|
||||
PDF.*
|
||||
*The expected value of the comparison PDF corresponds to the time distance between the automatic and manual picks most
|
||||
likely onset.*
|
||||
*The standard deviation corresponds to the combined uncertainty.*
|
||||
|
||||
To compare the automatic and manual picks between multiple stations of an event, the properties of all the comparison PDFs are shown in a histogram.
|
||||
To compare the automatic and manual picks between multiple stations of an event, the properties of all the comparison
|
||||
PDFs are shown in a histogram.
|
||||
|
||||
<img src=images/gui/comparison/compare_widget.png title="Comparison between picks of an event">
|
||||
|
||||
@ -352,11 +445,13 @@ To compare the automatic and manual picks between multiple stations of an event,
|
||||
*The bottom left plot shows the expected values of the comparison PDFs for P picks.*
|
||||
*The top right plot shows the standard deviation of the comparison PDFs for S picks.*
|
||||
*The bottom right plot shows the expected values of the comparison PDFs for S picks.*
|
||||
*The standard deviation plots show that most P picks have an uncertainty between 1 and 2 seconds, while S pick uncertainties have a much larger spread between 1 to 15 seconds.*
|
||||
*The standard deviation plots show that most P picks have an uncertainty between 1 and 2 seconds, while S pick
|
||||
uncertainties have a much larger spread between 1 to 15 seconds.*
|
||||
*This means P picks have higher quality classes on average than S picks.*
|
||||
*The expected values are largely negative, meaning that the algorithm tends to pick earlier than the analyst with the applied settings (Manual - Automatic).*
|
||||
*The number of samples mentioned in the plots legends is the amount of stations that have an automatic and a manual P pick.*
|
||||
|
||||
*The expected values are largely negative, meaning that the algorithm tends to pick earlier than the analyst with the
|
||||
applied settings (Manual - Automatic).*
|
||||
*The number of samples mentioned in the plots legends is the amount of stations that have an automatic and a manual P
|
||||
pick.*
|
||||
|
||||
### Export and Import of automatic picks
|
||||
|
||||
@ -369,7 +464,11 @@ To be added.
|
||||
# FAQ
|
||||
|
||||
Q: During manual picking the error "No channel to plot for phase ..." is displayed, and I am unable to create a pick.
|
||||
A: Select a channel that should be used for the corresponding phase in the Pickwindow. For further information read [Picking Window settings](#picking-window-settings).
|
||||
A: Select a channel that should be used for the corresponding phase in the Pickwindow. For further information
|
||||
read [Picking Window settings](#picking-window-settings).
|
||||
|
||||
Q: I see a warning "Mismatch in event identifiers" when loading picks from a file.
|
||||
A: This means that PyLoT doesn't recognize the picks in the file as belonging to this specific event. They could have been saved under a different installation of PyLoT but with the same waveform data, which means they are still compatible and you can continue loading them or they could be the picks of a different event, in which case loading them is not recommended.
|
||||
A: This means that PyLoT doesn't recognize the picks in the file as belonging to this specific event. They could have
|
||||
been saved under a different installation of PyLoT but with the same waveform data, which means they are still
|
||||
compatible and you can continue loading them or they could be the picks of a different event, in which case loading them
|
||||
is not recommended.
|
||||
|
||||
172
docs/tuning.md
172
docs/tuning.md
@ -6,95 +6,145 @@ A description of the parameters used for determining automatic picks.
|
||||
|
||||
Parameters applied to the traces before picking algorithm starts.
|
||||
|
||||
Name | Description
|
||||
--- | ---
|
||||
*P Start*, *P Stop* | Define time interval relative to trace start time for CF calculation on vertical trace. Value is relative to theoretical onset time if 'Use TauPy' option is enabled in main settings of 'Tune Autopicker' dialogue.
|
||||
*S Start*, *S Stop* | Define time interval relative to trace start time for CF calculation on horizontal traces. Value is relative to theoretical onset time if 'Use TauPy' option is enabled in main settings of 'Tune Autopicker' dialogue.
|
||||
*Bandpass Z1* | Filter settings for Butterworth bandpass applied to vertical trace for calculation of initial P pick.
|
||||
*Bandpass Z2* | Filter settings for Butterworth bandpass applied to vertical trace for calculation of precise P pick.
|
||||
*Bandpass H1* | Filter settings for Butterworth bandpass applied to horizontal traces for calculation of initial S pick.
|
||||
*Bandpass H2* | Filter settings for Butterworth bandpass applied to horizontal traces for calculation of precise S pick.
|
||||
| Name | Description |
|
||||
|---------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| *P Start*, *P
|
||||
Stop* | Define time interval relative to trace start time for CF calculation on vertical trace. Value is relative to theoretical onset time if 'Use TauPy' option is enabled in main settings of 'Tune Autopicker' dialogue. |
|
||||
| *S Start*, *S
|
||||
Stop* | Define time interval relative to trace start time for CF calculation on horizontal traces. Value is relative to theoretical onset time if 'Use TauPy' option is enabled in main settings of 'Tune Autopicker' dialogue. |
|
||||
| *Bandpass
|
||||
Z1* | Filter settings for Butterworth bandpass applied to vertical trace for calculation of initial P pick. |
|
||||
| *Bandpass
|
||||
Z2* | Filter settings for Butterworth bandpass applied to vertical trace for calculation of precise P pick. |
|
||||
| *Bandpass
|
||||
H1* | Filter settings for Butterworth bandpass applied to horizontal traces for calculation of initial S pick. |
|
||||
| *Bandpass
|
||||
H2* | Filter settings for Butterworth bandpass applied to horizontal traces for calculation of precise S pick. |
|
||||
|
||||
## Inital P pick
|
||||
|
||||
Parameters used for determination of initial P pick.
|
||||
|
||||
Name | Description
|
||||
--- | ---
|
||||
*tLTA* | Size of gliding LTA window in seconds used for calculation of HOS-CF.
|
||||
*pickwin P* | Size of time window in seconds in which the minimum of the AIC-CF in front of the maximum of the HOS-CF is determined.
|
||||
*AICtsmooth* | Average of samples in this time window will be used for smoothing of the AIC-CF.
|
||||
*checkwinP* | Time in front of the global maximum of the HOS-CF in which to search for a second local extrema.
|
||||
*minfactorP* | Used with *checkwinP*. If a second local maximum is found, it has to be at least as big as the first maximum * *minfactorP*.
|
||||
*tsignal* | Time window in seconds after the initial P pick used for determining signal amplitude.
|
||||
*tnoise* | Time window in seconds in front of initial P pick used for determining noise amplitude.
|
||||
*tsafetey* | Time in seconds between *tsignal* and *tnoise*.
|
||||
*tslope* | Time window in seconds after initial P pick in which the slope of the onset is calculated.
|
||||
| Name | Description |
|
||||
|--------------|------------------------------------------------------------------------------------------------------------------------------|
|
||||
| *
|
||||
tLTA* | Size of gliding LTA window in seconds used for calculation of HOS-CF. |
|
||||
| *pickwin
|
||||
P* | Size of time window in seconds in which the minimum of the AIC-CF in front of the maximum of the HOS-CF is determined. |
|
||||
| *
|
||||
AICtsmooth* | Average of samples in this time window will be used for smoothing of the AIC-CF. |
|
||||
| *
|
||||
checkwinP* | Time in front of the global maximum of the HOS-CF in which to search for a second local extrema. |
|
||||
| *minfactorP* | Used with *
|
||||
checkwinP*. If a second local maximum is found, it has to be at least as big as the first maximum * *minfactorP*. |
|
||||
| *
|
||||
tsignal* | Time window in seconds after the initial P pick used for determining signal amplitude. |
|
||||
| *
|
||||
tnoise* | Time window in seconds in front of initial P pick used for determining noise amplitude. |
|
||||
| *tsafetey* | Time in seconds between *tsignal* and *
|
||||
tnoise*. |
|
||||
| *
|
||||
tslope* | Time window in seconds after initial P pick in which the slope of the onset is calculated. |
|
||||
|
||||
## Inital S pick
|
||||
|
||||
Parameters used for determination of initial S pick
|
||||
|
||||
Name | Description
|
||||
--- | ---
|
||||
*tdet1h* | Length of time window in seconds in which AR params of the waveform are determined.
|
||||
*tpred1h* | Length of time window in seconds in which the waveform is predicted using the AR model.
|
||||
*AICtsmoothS* | Average of samples in this time window is used for smoothing the AIC-CF.
|
||||
*pickwinS* | Time window in which the minimum in the AIC-CF in front of the maximum in the ARH-CF is determined.
|
||||
*checkwinS* | Time in front of the global maximum of the ARH-CF in which to search for a second local extrema.
|
||||
*minfactorP* | Used with *checkwinS*. If a second local maximum is found, it has to be at least as big as the first maximum * *minfactorS*.
|
||||
*tsignal* | Time window in seconds after the initial P pick used for determining signal amplitude.
|
||||
*tnoise* | Time window in seconds in front of initial P pick used for determining noise amplitude.
|
||||
*tsafetey* | Time in seconds between *tsignal* and *tnoise*.
|
||||
*tslope* | Time window in seconds after initial P pick in which the slope of the onset is calculated.
|
||||
| Name | Description |
|
||||
|---------------|------------------------------------------------------------------------------------------------------------------------------|
|
||||
| *
|
||||
tdet1h* | Length of time window in seconds in which AR params of the waveform are determined. |
|
||||
| *
|
||||
tpred1h* | Length of time window in seconds in which the waveform is predicted using the AR model. |
|
||||
| *
|
||||
AICtsmoothS* | Average of samples in this time window is used for smoothing the AIC-CF. |
|
||||
| *
|
||||
pickwinS* | Time window in which the minimum in the AIC-CF in front of the maximum in the ARH-CF is determined. |
|
||||
| *
|
||||
checkwinS* | Time in front of the global maximum of the ARH-CF in which to search for a second local extrema. |
|
||||
| *minfactorP* | Used with *
|
||||
checkwinS*. If a second local maximum is found, it has to be at least as big as the first maximum * *minfactorS*. |
|
||||
| *
|
||||
tsignal* | Time window in seconds after the initial P pick used for determining signal amplitude. |
|
||||
| *
|
||||
tnoise* | Time window in seconds in front of initial P pick used for determining noise amplitude. |
|
||||
| *tsafetey* | Time in seconds between *tsignal* and *
|
||||
tnoise*. |
|
||||
| *
|
||||
tslope* | Time window in seconds after initial P pick in which the slope of the onset is calculated. |
|
||||
|
||||
## Precise P pick
|
||||
|
||||
Parameters used for determination of precise P pick.
|
||||
|
||||
Name | Description
|
||||
--- | ---
|
||||
*Precalcwin* | Time window in seconds for recalculation of the HOS-CF. The new CF will be two times the size of *Precalcwin*, since it will be calculated from the initial pick to +/- *Precalcwin*.
|
||||
*tsmoothP* | Average of samples in this time window will be used for smoothing the second HOS-CF.
|
||||
*ausP* | Controls artificial uplift of samples during precise picking. A common local minimum of the smoothed and unsmoothed HOS-CF is found when the previous sample is larger or equal to the current sample times (1+*ausP*).
|
||||
| Name | Description |
|
||||
|--------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| *Precalcwin* | Time window in seconds for recalculation of the HOS-CF. The new CF will be two times the size of *
|
||||
Precalcwin*, since it will be calculated from the initial pick to +/- *Precalcwin*. |
|
||||
| *
|
||||
tsmoothP* | Average of samples in this time window will be used for smoothing the second HOS-CF. |
|
||||
| *
|
||||
ausP* | Controls artificial uplift of samples during precise picking. A common local minimum of the smoothed and unsmoothed HOS-CF is found when the previous sample is larger or equal to the current sample times (1+*
|
||||
ausP*). |
|
||||
|
||||
## Precise S pick
|
||||
|
||||
Parameters used for determination of precise S pick.
|
||||
|
||||
Name | Description
|
||||
--- | ---
|
||||
*tdet2h* | Time window for determination of AR coefficients.
|
||||
*tpred2h* | Time window in which the waveform is predicted using the determined AR parameters.
|
||||
*Srecalcwin* | Time window for recalculation of ARH-CF. New CF will be calculated from initial pick +/- *Srecalcwin*.
|
||||
*tsmoothS* | Average of samples in this time window will be used for smoothing the second ARH-CF.
|
||||
*ausS* | Controls artificial uplift of samples during precise picking. A common local minimum of the smoothed and unsmoothed ARH-CF is found when the previous sample is larger or equal to the current sample times (1+*ausS*).
|
||||
*pickwinS* | Time window around initial pick in which to look for a precise pick.
|
||||
|
||||
| Name | Description |
|
||||
|--------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| *
|
||||
tdet2h* | Time window for determination of AR coefficients. |
|
||||
| *
|
||||
tpred2h* | Time window in which the waveform is predicted using the determined AR parameters. |
|
||||
| *Srecalcwin* | Time window for recalculation of ARH-CF. New CF will be calculated from initial pick +/- *
|
||||
Srecalcwin*. |
|
||||
| *
|
||||
tsmoothS* | Average of samples in this time window will be used for smoothing the second ARH-CF. |
|
||||
| *
|
||||
ausS* | Controls artificial uplift of samples during precise picking. A common local minimum of the smoothed and unsmoothed ARH-CF is found when the previous sample is larger or equal to the current sample times (1+*
|
||||
ausS*). |
|
||||
| *
|
||||
pickwinS* | Time window around initial pick in which to look for a precise pick. |
|
||||
|
||||
## Pick quality control
|
||||
|
||||
Parameters used for checking quality and integrity of automatic picks.
|
||||
|
||||
Name | Description
|
||||
--- | ---
|
||||
*minAICPslope* | Initial P picks with a slope lower than this value will be discared.
|
||||
*minAICPSNR* | Initial P picks with a SNR below this value will be discarded.
|
||||
*minAICSslope* | Initial S picks with a slope lower than this value will be discarded.
|
||||
*minAICSSNR* | Initial S picks with a SNR below this value will be discarded.
|
||||
*minsiglength*, *noisefacor*. *minpercent* | Parameters for checking signal length. In the time window of size *minsiglength* after the initial P pick *minpercent* of samples have to be larger than the RMS value.
|
||||
*zfac* | To recognize misattributed S picks, the RMS amplitude of vertical and horizontal traces are compared. The RMS amplitude of the vertical traces has to be at least *zfac* higher than the RMS amplitude on the horizontal traces for the pick to be accepted as a valid P pick.
|
||||
*jackfactor* | A P pick is removed if the jackknife pseudo value of the variance of his subgroup is larger than the variance of all picks multiplied with the *jackfactor*.
|
||||
*mdttolerance* | Maximum allowed deviation of P onset times from the median. Value in seconds.
|
||||
*wdttolerance* | Maximum allowed deviation of S onset times from the line during the Wadati test. Value in seconds.
|
||||
| Name | Description |
|
||||
|--------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| *
|
||||
minAICPslope* | Initial P picks with a slope lower than this value will be discared. |
|
||||
| *
|
||||
minAICPSNR* | Initial P picks with a SNR below this value will be discarded. |
|
||||
| *
|
||||
minAICSslope* | Initial S picks with a slope lower than this value will be discarded. |
|
||||
| *
|
||||
minAICSSNR* | Initial S picks with a SNR below this value will be discarded. |
|
||||
| *minsiglength*, *noisefacor*. *minpercent* | Parameters for checking signal length. In the time window of size *
|
||||
minsiglength* after the initial P pick *
|
||||
minpercent* of samples have to be larger than the RMS value. |
|
||||
| *
|
||||
zfac* | To recognize misattributed S picks, the RMS amplitude of vertical and horizontal traces are compared. The RMS amplitude of the vertical traces has to be at least *
|
||||
zfac* higher than the RMS amplitude on the horizontal traces for the pick to be accepted as a valid P pick. |
|
||||
| *
|
||||
jackfactor* | A P pick is removed if the jackknife pseudo value of the variance of his subgroup is larger than the variance of all picks multiplied with the *
|
||||
jackfactor*. |
|
||||
| *
|
||||
mdttolerance* | Maximum allowed deviation of P onset times from the median. Value in seconds. |
|
||||
| *
|
||||
wdttolerance* | Maximum allowed deviation of S onset times from the line during the Wadati test. Value in seconds. |
|
||||
|
||||
## Pick quality determination
|
||||
|
||||
Parameters for discrete quality classes.
|
||||
|
||||
Name | Description
|
||||
--- | ---
|
||||
*timeerrorsP* | Width of the time windows in seconds between earliest and latest possible pick which represent the quality classes 0, 1, 2, 3 for P onsets.
|
||||
*timeerrorsS* | Width of the time windows in seconds between earliest and latest possible pick which represent the quality classes 0, 1, 2, 3 for S onsets.
|
||||
*nfacP*, *nfacS* | For determination of latest possible onset time. The time when the signal reaches an amplitude of *nfac* * mean value of the RMS amplitude in the time window *tnoise* corresponds to the latest possible onset time.
|
||||
| Name | Description |
|
||||
|------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| *
|
||||
timeerrorsP* | Width of the time windows in seconds between earliest and latest possible pick which represent the quality classes 0, 1, 2, 3 for P onsets. |
|
||||
| *
|
||||
timeerrorsS* | Width of the time windows in seconds between earliest and latest possible pick which represent the quality classes 0, 1, 2, 3 for S onsets. |
|
||||
| *nfacP*, *nfacS* | For determination of latest possible onset time. The time when the signal reaches an amplitude of *
|
||||
nfac* * mean value of the RMS amplitude in the time window *tnoise* corresponds to the latest possible onset time. |
|
||||
|
||||
|
||||
@ -6,7 +6,7 @@
|
||||
#
|
||||
# WARNING! All changes made in this file will be lost!
|
||||
|
||||
from PyQt4 import QtCore
|
||||
from PySide2 import QtCore
|
||||
|
||||
qt_resource_data = "\
|
||||
\x00\x00\x9e\x04\
|
||||
|
||||
@ -7,9 +7,9 @@
|
||||
#
|
||||
# WARNING! All changes made in this file will be lost!
|
||||
|
||||
from PySide import QtCore
|
||||
from PySide2 import QtCore
|
||||
|
||||
qt_resource_data = "\
|
||||
qt_resource_data = b"\
|
||||
\x00\x00\x9e\x04\
|
||||
\x89\
|
||||
\x50\x4e\x47\x0d\x0a\x1a\x0a\x00\x00\x00\x0d\x49\x48\x44\x52\x00\
|
||||
@ -109000,7 +109000,7 @@ qt_resource_data = "\
|
||||
\x62\x6f\x64\x79\x3e\x0a\x3c\x2f\x68\x74\x6d\x6c\x3e\x0a\
|
||||
"
|
||||
|
||||
qt_resource_name = "\
|
||||
qt_resource_name = b"\
|
||||
\x00\x04\
|
||||
\x00\x06\xec\x30\
|
||||
\x00\x68\
|
||||
@ -109235,7 +109235,7 @@ qt_resource_name = "\
|
||||
\x00\x6e\x00\x64\x00\x65\x00\x78\x00\x2e\x00\x68\x00\x74\x00\x6d\x00\x6c\
|
||||
"
|
||||
|
||||
qt_resource_struct = "\
|
||||
qt_resource_struct = b"\
|
||||
\x00\x00\x00\x00\x00\x02\x00\x00\x00\x03\x00\x00\x00\x01\
|
||||
\x00\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x3a\
|
||||
\x00\x00\x00\x0e\x00\x02\x00\x00\x00\x35\x00\x00\x00\x05\
|
||||
|
||||
14
pylot.yml
Normal file
14
pylot.yml
Normal file
@ -0,0 +1,14 @@
|
||||
name: pylot_38
|
||||
channels:
|
||||
- conda-forge
|
||||
- defaults
|
||||
dependencies:
|
||||
- cartopy=0.20.2
|
||||
- matplotlib-base=3.3.4
|
||||
- numpy=1.22.3
|
||||
- obspy=1.3.0
|
||||
- pyqtgraph=0.12.4
|
||||
- pyside2=5.13.2
|
||||
- python=3.8.12
|
||||
- qt=5.12.9
|
||||
- scipy=1.8.0
|
||||
@ -223,7 +223,7 @@ class LocalMagnitude(Magnitude):
|
||||
in 'Z3']
|
||||
# checking horizontal count and calculating power_sum accordingly
|
||||
if len(power) == 1:
|
||||
print ('WARNING: Only one horizontal found for station {0}.'.format(st[0].stats.station))
|
||||
print('WARNING: Only one horizontal found for station {0}.'.format(st[0].stats.station))
|
||||
power_sum = power[0]
|
||||
elif len(power) == 2:
|
||||
power_sum = power[0] + power[1]
|
||||
@ -594,13 +594,13 @@ def calcsourcespec(wfstream, onset, vp, delta, azimuth, incidence,
|
||||
|
||||
# fft
|
||||
fny = freq / 2
|
||||
#l = len(xdat) / freq
|
||||
# l = len(xdat) / freq
|
||||
# number of fft bins after Bath
|
||||
#n = freq * l
|
||||
# n = freq * l
|
||||
# find next power of 2 of data length
|
||||
m = pow(2, np.ceil(np.log(len(xdat)) / np.log(2)))
|
||||
N = min(int(np.power(m, 2)), 16384)
|
||||
#N = int(np.power(m, 2))
|
||||
# N = int(np.power(m, 2))
|
||||
y = dt * np.fft.fft(xdat, N)
|
||||
Y = abs(y[: N / 2])
|
||||
L = (N - 1) / freq
|
||||
|
||||
@ -1,18 +1,18 @@
|
||||
#!/usr/bin/env pyth n
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
import copy
|
||||
import os
|
||||
|
||||
from PySide2.QtWidgets import QMessageBox
|
||||
from obspy import read_events
|
||||
from obspy.core import read, Stream, UTCDateTime
|
||||
from obspy.core.event import Event as ObsPyEvent
|
||||
from obspy.io.sac import SacIOError
|
||||
|
||||
from PySide.QtGui import QMessageBox
|
||||
|
||||
import pylot.core.loc.velest as velest
|
||||
import pylot.core.loc.focmec as focmec
|
||||
import pylot.core.loc.hypodd as hypodd
|
||||
import pylot.core.loc.velest as velest
|
||||
from pylot.core.io.phases import readPILOTEvent, picks_from_picksdict, \
|
||||
picksdict_from_pilot, merge_picks, PylotParameter
|
||||
from pylot.core.util.errors import FormatError, OverwriteError
|
||||
@ -21,13 +21,14 @@ from pylot.core.util.obspyDMT_interface import qml_from_obspyDMT
|
||||
from pylot.core.util.utils import fnConstructor, full_range, check4rotated, \
|
||||
check4gapsAndMerge, trim_station_components
|
||||
|
||||
|
||||
class Data(object):
|
||||
"""
|
||||
Data container with attributes wfdata holding ~obspy.core.stream.
|
||||
|
||||
|
kaan marked this conversation as resolved
Outdated
sebastianw
commented
Obsolete since backwards compatibility to 2.x not possible after merge. Obsolete since backwards compatibility to 2.x not possible after merge.
|
||||
:type parent: PySide.QtGui.QWidget object, optional
|
||||
:param parent: A PySide.QtGui.QWidget object utilized when
|
||||
called by a GUI to display a PySide.QtGui.QMessageBox instead of printing
|
||||
:type parent: PySide2.QtWidgets.QWidget object, optional
|
||||
:param parent: A PySide2.QtWidgets.QWidget object utilized when
|
||||
called by a GUI to display a PySide2.QtWidgets.QMessageBox instead of printing
|
||||
to standard out.
|
||||
:type evtdata: ~obspy.core.event.Event object, optional
|
||||
:param evtdata ~obspy.core.event.Event object containing all derived or
|
||||
@ -47,10 +48,10 @@ class Data(object):
|
||||
elif isinstance(evtdata, dict):
|
||||
evt = readPILOTEvent(**evtdata)
|
||||
evtdata = evt
|
||||
elif type(evtdata) in [str, unicode]:
|
||||
elif isinstance(evtdata, str):
|
||||
try:
|
||||
cat = read_events(evtdata)
|
||||
if len(cat) is not 1:
|
||||
if len(cat) != 1:
|
||||
raise ValueError('ambiguous event information for file: '
|
||||
|
kaan marked this conversation as resolved
Outdated
sebastianw
commented
See above! See above!
|
||||
'{file}'.format(file=evtdata))
|
||||
evtdata = cat[0]
|
||||
@ -99,7 +100,7 @@ class Data(object):
|
||||
old_pick.phase_hint == new_pick.phase_hint,
|
||||
old_pick.method_id == new_pick.method_id]
|
||||
if all(comparison):
|
||||
del(old_pick)
|
||||
del (old_pick)
|
||||
old_picks.append(new_pick)
|
||||
elif not other.isNew() and self.isNew():
|
||||
new = other + self
|
||||
@ -162,9 +163,8 @@ class Data(object):
|
||||
|
||||
def checkEvent(self, event, fcheck, forceOverwrite=False):
|
||||
"""
|
||||
Check information in supplied event and own event and replace own
|
||||
information with supplied information if own information not exiisting
|
||||
or forced by forceOverwrite
|
||||
Check information in supplied event and own event and replace with own
|
||||
information if no other information are given or forced by forceOverwrite
|
||||
:param event: Event that supplies information for comparison
|
||||
:type event: pylot.core.util.event.Event
|
||||
:param fcheck: check and delete existing information
|
||||
@ -318,7 +318,7 @@ class Data(object):
|
||||
del picks_copy[k]
|
||||
break
|
||||
lendiff = len(picks) - len(picks_copy)
|
||||
if lendiff is not 0:
|
||||
if lendiff != 0:
|
||||
print("Manual as well as automatic picks available. Prefered the {} manual ones!".format(lendiff))
|
||||
|
||||
if upperErrors:
|
||||
@ -360,13 +360,13 @@ class Data(object):
|
||||
nllocfile = open(fnout + fnext)
|
||||
l = nllocfile.readlines()
|
||||
# Adding A0/Generic Amplitude to .obs file
|
||||
#l2 = []
|
||||
#for li in l:
|
||||
# l2 = []
|
||||
# for li in l:
|
||||
# for amp in evtdata_org.amplitudes:
|
||||
# if amp.waveform_id.station_code == li[0:5].strip():
|
||||
# li = li[0:64] + '{:0.2e}'.format(amp.generic_amplitude) + li[73:-1] + '\n'
|
||||
# l2.append(li)
|
||||
#l = l2
|
||||
# l = l2
|
||||
nllocfile.close()
|
||||
l.insert(0, header)
|
||||
nllocfile = open(fnout + fnext, 'w')
|
||||
@ -503,7 +503,8 @@ class Data(object):
|
||||
real_or_syn_data[synthetic] += read(fname, format='GSE2', starttime=self.tstart, endtime=self.tstop)
|
||||
except Exception as e:
|
||||
try:
|
||||
real_or_syn_data[synthetic] += read(fname, format='SEGY', starttime=self.tstart, endtime=self.tstop)
|
||||
real_or_syn_data[synthetic] += read(fname, format='SEGY', starttime=self.tstart,
|
||||
endtime=self.tstop)
|
||||
except Exception as e:
|
||||
warnmsg += '{0}\n{1}\n'.format(fname, e)
|
||||
except SacIOError as se:
|
||||
@ -794,8 +795,8 @@ class PilotDataStructure(GenericDataStructure):
|
||||
|
||||
def __init__(self, **fields):
|
||||
if not fields:
|
||||
fields = {'database': '2006.01',
|
||||
'root': '/data/Egelados/EVENT_DATA/LOCAL'}
|
||||
fields = {'database': '',
|
||||
'root': ''}
|
||||
|
||||
GenericDataStructure.__init__(self, **fields)
|
||||
|
||||
|
||||
@ -8,14 +8,10 @@
|
||||
Edited for use in PyLoT
|
||||
JG, igem, 01/2022
|
||||
"""
|
||||
import pdb
|
||||
import os
|
||||
import argparse
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
import glob
|
||||
|
||||
from obspy.core.event import read_events
|
||||
from pyproj import Proj
|
||||
import glob
|
||||
|
||||
"""
|
||||
Creates an eventlist file summarizing all events found in a certain folder. Only called by pressing UI Button eventlis_xml_action
|
||||
@ -24,14 +20,15 @@ Creates an eventlist file summarizing all events found in a certain folder. Only
|
||||
:param path: Path to root folder where single Event folder are to found
|
||||
"""
|
||||
|
||||
|
||||
def geteventlistfromxml(path, outpath):
|
||||
p = Proj(proj='utm', zone=32, ellps='WGS84')
|
||||
|
||||
|
||||
# open eventlist file and write header
|
||||
evlist = outpath + '/eventlist'
|
||||
evlistobj = open(evlist, 'w')
|
||||
evlistobj.write('EventID Date To Lat Lon EAST NORTH Dep Ml NoP NoS RMS errH errZ Gap \n')
|
||||
evlistobj.write(
|
||||
'EventID Date To Lat Lon EAST NORTH Dep Ml NoP NoS RMS errH errZ Gap \n')
|
||||
|
||||
# data path
|
||||
dp = path + "/e*/*.xml"
|
||||
@ -52,7 +49,8 @@ def geteventlistfromxml(path, outpath):
|
||||
NoP = []
|
||||
NoS = []
|
||||
except IndexError:
|
||||
print ('Insufficient data found for event (not localised): ' + names.split('/')[-1].split('_')[-1][:-4] + ' Skipping event for eventlist.' )
|
||||
print('Insufficient data found for event (not localised): ' + names.split('/')[-1].split('_')[-1][
|
||||
:-4] + ' Skipping event for eventlist.')
|
||||
continue
|
||||
|
||||
for i in range(len(cat.events[0].origins[0].arrivals)):
|
||||
@ -60,20 +58,22 @@ def geteventlistfromxml(path, outpath):
|
||||
NoP.append(cat.events[0].origins[0].arrivals[i].phase)
|
||||
elif cat.events[0].origins[0].arrivals[i].phase == 'S':
|
||||
NoS.append(cat.events[0].origins[0].arrivals[i].phase)
|
||||
#NoP = cat.events[0].origins[0].quality.used_station_count
|
||||
# NoP = cat.events[0].origins[0].quality.used_station_count
|
||||
errH = cat.events[0].origins[0].origin_uncertainty.max_horizontal_uncertainty
|
||||
errZ = cat.events[0].origins[0].depth_errors.uncertainty
|
||||
Gap = cat.events[0].origins[0].quality.azimuthal_gap
|
||||
#evID = names.split('/')[6]
|
||||
# evID = names.split('/')[6]
|
||||
evID = names.split('/')[-1].split('_')[-1][:-4]
|
||||
Date = str(st.year) + str('%02d' % st.month) + str('%02d' % st.day)
|
||||
To = str('%02d' % st.hour) + str('%02d' % st.minute) + str('%02d' % st.second) + \
|
||||
'.' + str('%06d' % st.microsecond)
|
||||
|
||||
# write into eventlist
|
||||
evlistobj.write('%s %s %s %9.6f %9.6f %13.6f %13.6f %8.6f %3.1f %d %d NaN %d %d %d\n' %(evID, \
|
||||
Date, To, Lat, Lon, EAST, NORTH, Dep, Ml, len(NoP), len(NoS), errH, errZ, Gap))
|
||||
print ('Adding Event ' + names.split('/')[-1].split('_')[-1][:-4] + ' to eventlist')
|
||||
evlistobj.write('%s %s %s %9.6f %9.6f %13.6f %13.6f %8.6f %3.1f %d %d NaN %d %d %d\n' % (evID, \
|
||||
Date, To, Lat, Lon,
|
||||
EAST, NORTH, Dep, Ml,
|
||||
len(NoP), len(NoS),
|
||||
errH, errZ, Gap))
|
||||
print('Adding Event ' + names.split('/')[-1].split('_')[-1][:-4] + ' to eventlist')
|
||||
print('Eventlist created and saved in: ' + outpath)
|
||||
evlistobj.close()
|
||||
|
||||
|
||||
@ -1,139 +0,0 @@
|
||||
#!/usr/bin/python
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
"""
|
||||
Script to get onset uncertainties from Quakeml.xml files created by PyLoT.
|
||||
Uncertainties are tranformed into quality classes and visualized via histogram if desired.
|
||||
Ludger Küperkoch, BESTEC GmbH, 07/2017
|
||||
rev.: Ludger Küperkoch, igem, 10/2020
|
||||
Edited for usage in PyLoT: Jeldrik Gaal, igem, 01/2022
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
from obspy.core.event import read_events
|
||||
import glob
|
||||
|
||||
def getQualitiesfromxml(path):
|
||||
|
||||
# uncertainties
|
||||
ErrorsP = [0.02, 0.04, 0.08, 0.16]
|
||||
ErrorsS = [0.04, 0.08, 0.16, 0.32]
|
||||
|
||||
Pw0 = []
|
||||
Pw1 = []
|
||||
Pw2 = []
|
||||
Pw3 = []
|
||||
Pw4 = []
|
||||
Sw0 = []
|
||||
Sw1 = []
|
||||
Sw2 = []
|
||||
Sw3 = []
|
||||
Sw4 = []
|
||||
|
||||
# data path
|
||||
dp = path + '/e*/*.xml'
|
||||
# list of all available xml-files
|
||||
xmlnames = glob.glob(dp)
|
||||
|
||||
# read all onset weights
|
||||
for names in xmlnames:
|
||||
print("Getting onset weights from {}".format(names))
|
||||
cat = read_events(names)
|
||||
arrivals = cat.events[0].picks
|
||||
for Pick in arrivals:
|
||||
if Pick.phase_hint[0] == 'P':
|
||||
if Pick.time_errors.uncertainty <= ErrorsP[0]:
|
||||
Pw0.append(Pick.time_errors.uncertainty)
|
||||
elif Pick.time_errors.uncertainty > ErrorsP[0] and \
|
||||
Pick.time_errors.uncertainty <= ErrorsP[1]:
|
||||
Pw1.append(Pick.time_errors.uncertainty)
|
||||
elif Pick.time_errors.uncertainty > ErrorsP[1] and \
|
||||
Pick.time_errors.uncertainty <= ErrorsP[2]:
|
||||
Pw2.append(Pick.time_errors.uncertainty)
|
||||
elif Pick.time_errors.uncertainty > ErrorsP[2] and \
|
||||
Pick.time_errors.uncertainty <= ErrorsP[3]:
|
||||
Pw3.append(Pick.time_errors.uncertainty)
|
||||
elif Pick.time_errors.uncertainty > ErrorsP[3]:
|
||||
Pw4.append(Pick.time_errors.uncertainty)
|
||||
else:
|
||||
pass
|
||||
elif Pick.phase_hint[0] == 'S':
|
||||
if Pick.time_errors.uncertainty <= ErrorsS[0]:
|
||||
Sw0.append(Pick.time_errors.uncertainty)
|
||||
elif Pick.time_errors.uncertainty > ErrorsS[0] and \
|
||||
Pick.time_errors.uncertainty <= ErrorsS[1]:
|
||||
Sw1.append(Pick.time_errors.uncertainty)
|
||||
elif Pick.time_errors.uncertainty > ErrorsS[1] and \
|
||||
Pick.time_errors.uncertainty <= ErrorsS[2]:
|
||||
Sw2.append(Pick.time_errors.uncertainty)
|
||||
elif Pick.time_errors.uncertainty > ErrorsS[2] and \
|
||||
Pick.time_errors.uncertainty <= ErrorsS[3]:
|
||||
Sw3.append(Pick.time_errors.uncertainty)
|
||||
elif Pick.time_errors.uncertainty > ErrorsS[3]:
|
||||
Sw4.append(Pick.time_errors.uncertainty)
|
||||
else:
|
||||
pass
|
||||
else:
|
||||
print("Phase hint not defined for picking!")
|
||||
pass
|
||||
# get percentage of weights
|
||||
numPweights = np.sum([len(Pw0), len(Pw1), len(Pw2), len(Pw3), len(Pw4)])
|
||||
numSweights = np.sum([len(Sw0), len(Sw1), len(Sw2), len(Sw3), len(Sw4)])
|
||||
try:
|
||||
P0perc = 100.0 / numPweights * len(Pw0)
|
||||
except:
|
||||
P0perc = 0
|
||||
try:
|
||||
P1perc = 100.0 / numPweights * len(Pw1)
|
||||
except:
|
||||
P1perc = 0
|
||||
try:
|
||||
P2perc = 100.0 / numPweights * len(Pw2)
|
||||
except:
|
||||
P2perc = 0
|
||||
try:
|
||||
P3perc = 100.0 / numPweights * len(Pw3)
|
||||
except:
|
||||
P3perc = 0
|
||||
try:
|
||||
P4perc = 100.0 / numPweights * len(Pw4)
|
||||
except:
|
||||
P4perc = 0
|
||||
try:
|
||||
S0perc = 100.0 / numSweights * len(Sw0)
|
||||
except:
|
||||
Soperc = 0
|
||||
try:
|
||||
S1perc = 100.0 / numSweights * len(Sw1)
|
||||
except:
|
||||
S1perc = 0
|
||||
try:
|
||||
S2perc = 100.0 / numSweights * len(Sw2)
|
||||
except:
|
||||
S2perc = 0
|
||||
try:
|
||||
S3perc = 100.0 / numSweights * len(Sw3)
|
||||
except:
|
||||
S3perc = 0
|
||||
try:
|
||||
S4perc = 100.0 / numSweights * len(Sw4)
|
||||
except:
|
||||
S4perc = 0
|
||||
|
||||
weights = ('0', '1', '2', '3', '4')
|
||||
y_pos = np.arange(len(weights))
|
||||
width = 0.34
|
||||
p1, = plt.bar(0 - width, P0perc, width, color='black')
|
||||
p2, = plt.bar(0, S0perc, width, color='red')
|
||||
plt.bar(y_pos - width, [P0perc, P1perc, P2perc, P3perc, P4perc], width, color='black')
|
||||
plt.bar(y_pos, [S0perc, S1perc, S2perc, S3perc, S4perc], width, color='red')
|
||||
plt.ylabel('%')
|
||||
plt.xticks(y_pos, weights)
|
||||
plt.xlim([-0.5, 4.5])
|
||||
plt.xlabel('Qualities')
|
||||
plt.title('{0} P-Qualities, {1} S-Qualities'.format(numPweights, numSweights))
|
||||
plt.legend([p1, p2], ['P-Weights', 'S-Weights'])
|
||||
plt.show()
|
||||
|
||||
@ -1,13 +1,13 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
import pdb
|
||||
import glob
|
||||
import os
|
||||
import warnings
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import obspy.core.event as ope
|
||||
import os
|
||||
import scipy.io as sio
|
||||
import warnings
|
||||
from obspy.core import UTCDateTime
|
||||
from obspy.core.event import read_events
|
||||
from obspy.core.util import AttribDict
|
||||
@ -17,7 +17,7 @@ from pylot.core.io.location import create_event, \
|
||||
create_magnitude
|
||||
from pylot.core.pick.utils import select_for_phase, get_quality_class
|
||||
from pylot.core.util.utils import getOwner, full_range, four_digits, transformFilterString4Export, \
|
||||
backtransformFilterString
|
||||
backtransformFilterString, loopIdentifyPhase, identifyPhase
|
||||
|
||||
|
||||
def add_amplitudes(event, amplitudes):
|
||||
@ -232,7 +232,7 @@ def picksdict_from_picks(evt):
|
||||
for pick in evt.picks:
|
||||
phase = {}
|
||||
station = pick.waveform_id.station_code
|
||||
if pick.waveform_id.channel_code == None:
|
||||
if pick.waveform_id.channel_code is None:
|
||||
channel = ''
|
||||
else:
|
||||
channel = pick.waveform_id.channel_code
|
||||
@ -375,8 +375,7 @@ def picks_from_picksdict(picks, creation_info=None):
|
||||
|
||||
|
||||
def reassess_pilot_db(root_dir, db_dir, out_dir=None, fn_param=None, verbosity=0):
|
||||
import glob
|
||||
|
||||
# TODO: change root to datapath
|
||||
db_root = os.path.join(root_dir, db_dir)
|
||||
evt_list = glob.glob1(db_root, 'e????.???.??')
|
||||
|
||||
@ -391,9 +390,7 @@ def reassess_pilot_event(root_dir, db_dir, event_id, out_dir=None, fn_param=None
|
||||
|
||||
from pylot.core.io.inputs import PylotParameter
|
||||
from pylot.core.pick.utils import earllatepicker
|
||||
|
||||
if fn_param is None:
|
||||
fn_param = defaults.AUTOMATIC_DEFAULTS
|
||||
# TODO: change root to datapath
|
||||
|
||||
default = PylotParameter(fn_param, verbosity)
|
||||
|
||||
@ -483,7 +480,6 @@ def reassess_pilot_event(root_dir, db_dir, event_id, out_dir=None, fn_param=None
|
||||
os.makedirs(out_dir)
|
||||
fnout_prefix = os.path.join(out_dir, 'PyLoT_{0}.'.format(event_id))
|
||||
evt.write(fnout_prefix + 'xml', format='QUAKEML')
|
||||
# evt.write(fnout_prefix + 'cnv', format='VELEST')
|
||||
|
||||
|
||||
def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
|
||||
@ -518,7 +514,7 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
|
||||
# write header
|
||||
fid.write('# EQEVENT: %s Label: EQ%s Loc: X 0.00 Y 0.00 Z 10.00 OT 0.00 \n' %
|
||||
(parameter.get('database'), parameter.get('eventID')))
|
||||
arrivals = chooseArrivals(arrivals)
|
||||
arrivals = chooseArrivals(arrivals) # MP MP what is chooseArrivals? It is not defined anywhere
|
||||
for key in arrivals:
|
||||
# P onsets
|
||||
if arrivals[key].has_key('P'):
|
||||
@ -575,7 +571,7 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
|
||||
Ao = arrivals[key]['S']['Ao'] # peak-to-peak amplitude
|
||||
if Ao == None:
|
||||
Ao = 0.0
|
||||
#fid.write('%s ? ? ? S %s %d%02d%02d %02d%02d %7.4f GAU 0 0 0 0 %d \n' % (key,
|
||||
# fid.write('%s ? ? ? S %s %d%02d%02d %02d%02d %7.4f GAU 0 0 0 0 %d \n' % (key,
|
||||
fid.write('%s ? ? ? S %s %d%02d%02d %02d%02d %7.4f GAU 0 %9.2f 0 0 %d \n' % (key,
|
||||
fm,
|
||||
year,
|
||||
@ -594,7 +590,7 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
|
||||
# write header
|
||||
fid.write(' %s\n' %
|
||||
parameter.get('eventID'))
|
||||
arrivals = chooseArrivals(arrivals)
|
||||
arrivals = chooseArrivals(arrivals) # MP MP what is chooseArrivals? It is not defined anywhere
|
||||
for key in arrivals:
|
||||
if arrivals[key]['P']['weight'] < 4:
|
||||
stat = key
|
||||
@ -671,7 +667,7 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
|
||||
fid = open("%s" % filename, 'w')
|
||||
# write header
|
||||
fid.write('%s, event %s \n' % (parameter.get('database'), parameter.get('eventID')))
|
||||
arrivals = chooseArrivals(arrivals)
|
||||
arrivals = chooseArrivals(arrivals) # MP MP what is chooseArrivals? It is not defined anywhere
|
||||
for key in arrivals:
|
||||
# P onsets
|
||||
if arrivals[key].has_key('P') and arrivals[key]['P']['mpp'] is not None:
|
||||
@ -769,7 +765,7 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
|
||||
arrivals = picksdict_from_picks(evt)
|
||||
# check for automatic and manual picks
|
||||
# prefer manual picks
|
||||
usedarrivals = chooseArrival(arrivals)
|
||||
usedarrivals = chooseArrivals(arrivals)
|
||||
for key in usedarrivals:
|
||||
# P onsets
|
||||
if usedarrivals[key].has_key('P'):
|
||||
@ -781,7 +777,7 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
|
||||
Ponset = usedarrivals[key]['P']['mpp']
|
||||
Pweight = usedarrivals[key]['P']['weight']
|
||||
Prt = Ponset - stime # onset time relative to source time
|
||||
if n % 6 is not 0:
|
||||
if n % 6 != 0:
|
||||
fid.write('%-4sP%d%6.2f' % (stat, Pweight, Prt))
|
||||
else:
|
||||
fid.write('%-4sP%d%6.2f\n' % (stat, Pweight, Prt))
|
||||
@ -795,7 +791,7 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
|
||||
Sonset = usedarrivals[key]['S']['mpp']
|
||||
Sweight = usedarrivals[key]['S']['weight']
|
||||
Srt = Ponset - stime # onset time relative to source time
|
||||
if n % 6 is not 0:
|
||||
if n % 6 != 0:
|
||||
fid.write('%-4sS%d%6.2f' % (stat, Sweight, Srt))
|
||||
else:
|
||||
fid.write('%-4sS%d%6.2f\n' % (stat, Sweight, Srt))
|
||||
@ -815,7 +811,7 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
|
||||
event = eventinfo['pylot_id']
|
||||
hddID = event.split('.')[0][1:5]
|
||||
except:
|
||||
print ("Error 1111111!")
|
||||
print("Error 1111111!")
|
||||
hddID = "00000"
|
||||
# write header
|
||||
fid.write('# %d %d %d %d %d %5.2f %7.4f +%6.4f %7.4f %4.2f 0.1 0.5 %4.2f %s\n' % (
|
||||
@ -830,7 +826,7 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
|
||||
arrivals = picksdict_from_picks(evt)
|
||||
# check for automatic and manual picks
|
||||
# prefer manual picks
|
||||
usedarrivals = chooseArrival(arrivals)
|
||||
usedarrivals = chooseArrivals(arrivals)
|
||||
for key in usedarrivals:
|
||||
if usedarrivals[key].has_key('P'):
|
||||
# P onsets
|
||||
@ -881,7 +877,7 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
|
||||
arrivals = picksdict_from_picks(evt)
|
||||
# check for automatic and manual picks
|
||||
# prefer manual picks
|
||||
usedarrivals = chooseArrival(arrivals)
|
||||
usedarrivals = chooseArrivals(arrivals)
|
||||
for key in usedarrivals:
|
||||
if usedarrivals[key].has_key('P'):
|
||||
if usedarrivals[key]['P']['weight'] < 4 and usedarrivals[key]['P']['fm'] is not None:
|
||||
@ -962,7 +958,7 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
|
||||
erh, erz, eventinfo.magnitudes[0]['mag'],
|
||||
hashID))
|
||||
# Prefer Manual Picks over automatic ones if possible
|
||||
arrivals = chooseArrivals(arrivals)
|
||||
arrivals = chooseArrivals(arrivals) # MP MP what is chooseArrivals? It is not defined anywhere
|
||||
# write phase lines
|
||||
for key in arrivals:
|
||||
if arrivals[key].has_key('P'):
|
||||
@ -1009,7 +1005,8 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
|
||||
fid1.close()
|
||||
fid2.close()
|
||||
|
||||
def chooseArrival(arrivals):
|
||||
|
||||
def chooseArrivals(arrivals):
|
||||
"""
|
||||
takes arrivals and returns the manual picks if manual and automatic ones are there
|
||||
returns automatic picks if only automatic picks are there
|
||||
@ -1058,37 +1055,63 @@ def merge_picks(event, picks):
|
||||
return event
|
||||
|
||||
|
||||
def getQualitiesfromxml(xmlnames, ErrorsP, ErrorsS, plotflag=1):
|
||||
def getQualitiesfromxml(path, errorsP, errorsS, plotflag=1, figure=None, verbosity=0):
|
||||
"""
|
||||
Script to get onset uncertainties from Quakeml.xml files created by PyLoT.
|
||||
Uncertainties are tranformed into quality classes and visualized via histogram if desired.
|
||||
Ludger Küperkoch, BESTEC GmbH, 07/2017
|
||||
:param xmlnames: list of xml obspy event files containing picks
|
||||
:type xmlnames: list
|
||||
:param ErrorsP: time errors of P waves for the four discrete quality classes
|
||||
:type ErrorsP:
|
||||
:param ErrorsS: time errors of S waves for the four discrete quality classes
|
||||
:type ErrorsS:
|
||||
:param path: path containing xml files
|
||||
:type path: str
|
||||
:param errorsP: time errors of P waves for the four discrete quality classes
|
||||
:type errorsP:
|
||||
:param errorsS: time errors of S waves for the four discrete quality classes
|
||||
:type errorsS:
|
||||
:param plotflag:
|
||||
:type plotflag:
|
||||
:return:
|
||||
:rtype:
|
||||
"""
|
||||
|
||||
from pylot.core.pick.utils import get_quality_class
|
||||
from pylot.core.util.utils import loopIdentifyPhase, identifyPhase
|
||||
def calc_perc(uncertainties, ntotal):
|
||||
''' simple function that calculates percentage of number of uncertainties (list length)'''
|
||||
if len(uncertainties) == 0:
|
||||
return 0
|
||||
else:
|
||||
return 100. / ntotal * len(uncertainties)
|
||||
|
||||
def calc_weight_perc(psweights, weight_ids):
|
||||
''' calculate percentages of different weights (pick classes!?) of total number of uncertainties of a phase'''
|
||||
# count total number of list items for this phase
|
||||
numWeights = np.sum([len(weight) for weight in psweights.values()])
|
||||
|
||||
# iterate over all available weights to return a list with percentages for plotting
|
||||
plot_list = []
|
||||
for weight_id in weight_ids:
|
||||
plot_list.append(calc_perc(psweights[weight_id], numWeights))
|
||||
|
||||
return plot_list, numWeights
|
||||
|
||||
# get all xmlfiles in path (maybe this should be changed to one xml file for this function, selectable via GUI?)
|
||||
xmlnames = glob.glob(os.path.join(path, '*.xml'))
|
||||
if len(xmlnames) == 0:
|
||||
print(f'No files found in path {path}.')
|
||||
return False
|
||||
|
||||
# first define possible phases here
|
||||
phases = ['P', 'S']
|
||||
|
||||
# define possible weights (0-4)
|
||||
weight_ids = list(range(5))
|
||||
|
||||
# put both error lists in a dictionary with P/S key so that amount of code can be halfed by simply using P/S as key
|
||||
errors = dict(P=errorsP, S=errorsS)
|
||||
|
||||
# create dictionaries for each phase (P/S) with a dictionary of empty list for each weight defined in weights
|
||||
# tuple above
|
||||
weights = {}
|
||||
for phase in phases:
|
||||
weights[phase] = {weight_id: [] for weight_id in weight_ids}
|
||||
|
||||
# read all onset weights
|
||||
Pw0 = []
|
||||
Pw1 = []
|
||||
Pw2 = []
|
||||
Pw3 = []
|
||||
Pw4 = []
|
||||
Sw0 = []
|
||||
Sw1 = []
|
||||
Sw2 = []
|
||||
Sw3 = []
|
||||
Sw4 = []
|
||||
for names in xmlnames:
|
||||
print("Getting onset weights from {}".format(names))
|
||||
cat = read_events(names)
|
||||
@ -1096,117 +1119,60 @@ def getQualitiesfromxml(xmlnames, ErrorsP, ErrorsS, plotflag=1):
|
||||
arrivals = cat.events[0].picks
|
||||
arrivals_copy = cat_copy.events[0].picks
|
||||
# Prefere manual picks if qualities are sufficient!
|
||||
for Pick in arrivals:
|
||||
if Pick.method_id.id.split('/')[1] == 'manual':
|
||||
mstation = Pick.waveform_id.station_code
|
||||
for pick in arrivals:
|
||||
if pick.method_id.id.split('/')[1] == 'manual':
|
||||
mstation = pick.waveform_id.station_code
|
||||
mstation_ext = mstation + '_'
|
||||
for mpick in arrivals_copy:
|
||||
phase = identifyPhase(loopIdentifyPhase(Pick.phase_hint))
|
||||
if phase == 'P':
|
||||
phase = identifyPhase(loopIdentifyPhase(pick.phase_hint)) # MP MP catch if this fails?
|
||||
if ((mpick.waveform_id.station_code == mstation) or
|
||||
(mpick.waveform_id.station_code == mstation_ext)) and \
|
||||
(mpick.method_id.split('/')[1] == 'auto') and \
|
||||
(mpick.time_errors['uncertainty'] <= ErrorsP[3]):
|
||||
del mpick
|
||||
break
|
||||
elif phase == 'S':
|
||||
if ((mpick.waveform_id.station_code == mstation) or
|
||||
(mpick.waveform_id.station_code == mstation_ext)) and \
|
||||
(mpick.method_id.split('/')[1] == 'auto') and \
|
||||
(mpick.time_errors['uncertainty'] <= ErrorsS[3]):
|
||||
(mpick.method_id.id.split('/')[1] == 'auto') and \
|
||||
(mpick.time_errors['uncertainty'] <= errors[phase][3]):
|
||||
del mpick
|
||||
break
|
||||
lendiff = len(arrivals) - len(arrivals_copy)
|
||||
if lendiff is not 0:
|
||||
if lendiff != 0:
|
||||
print("Found manual as well as automatic picks, prefered the {} manual ones!".format(lendiff))
|
||||
|
||||
for Pick in arrivals_copy:
|
||||
phase = identifyPhase(loopIdentifyPhase(Pick.phase_hint))
|
||||
if phase == 'P':
|
||||
Pqual = get_quality_class(Pick.time_errors.uncertainty, ErrorsP)
|
||||
if Pqual == 0:
|
||||
Pw0.append(Pick.time_errors.uncertainty)
|
||||
elif Pqual == 1:
|
||||
Pw1.append(Pick.time_errors.uncertainty)
|
||||
elif Pqual == 2:
|
||||
Pw2.append(Pick.time_errors.uncertainty)
|
||||
elif Pqual == 3:
|
||||
Pw3.append(Pick.time_errors.uncertainty)
|
||||
elif Pqual == 4:
|
||||
Pw4.append(Pick.time_errors.uncertainty)
|
||||
elif phase == 'S':
|
||||
Squal = get_quality_class(Pick.time_errors.uncertainty, ErrorsS)
|
||||
if Squal == 0:
|
||||
Sw0.append(Pick.time_errors.uncertainty)
|
||||
elif Squal == 1:
|
||||
Sw1.append(Pick.time_errors.uncertainty)
|
||||
elif Squal == 2:
|
||||
Sw2.append(Pick.time_errors.uncertainty)
|
||||
elif Squal == 3:
|
||||
Sw3.append(Pick.time_errors.uncertainty)
|
||||
elif Squal == 4:
|
||||
Sw4.append(Pick.time_errors.uncertainty)
|
||||
else:
|
||||
for pick in arrivals_copy:
|
||||
phase = identifyPhase(loopIdentifyPhase(pick.phase_hint))
|
||||
uncertainty = pick.time_errors.uncertainty
|
||||
if not uncertainty:
|
||||
if verbosity > 0:
|
||||
print('No uncertainty, pick {} invalid!'.format(pick.method_id.id))
|
||||
continue
|
||||
# check P/S phase
|
||||
if phase not in phases:
|
||||
print("Phase hint not defined for picking!")
|
||||
pass
|
||||
continue
|
||||
|
||||
qual = get_quality_class(uncertainty, errors[phase])
|
||||
weights[phase][qual].append(uncertainty)
|
||||
|
||||
if plotflag == 0:
|
||||
Punc = [Pw0, Pw1, Pw2, Pw3, Pw4]
|
||||
Sunc = [Sw0, Sw1, Sw2, Sw3, Sw4]
|
||||
return Punc, Sunc
|
||||
p_unc = [weights['P'][weight_id] for weight_id in weight_ids]
|
||||
s_unc = [weights['S'][weight_id] for weight_id in weight_ids]
|
||||
return p_unc, s_unc
|
||||
else:
|
||||
if not figure:
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111)
|
||||
# get percentage of weights
|
||||
numPweights = np.sum([len(Pw0), len(Pw1), len(Pw2), len(Pw3), len(Pw4)])
|
||||
numSweights = np.sum([len(Sw0), len(Sw1), len(Sw2), len(Sw3), len(Sw4)])
|
||||
if len(Pw0) > 0:
|
||||
P0perc = 100 / numPweights * len(Pw0)
|
||||
else:
|
||||
P0perc = 0
|
||||
if len(Pw1) > 0:
|
||||
P1perc = 100 / numPweights * len(Pw1)
|
||||
else:
|
||||
P1perc = 0
|
||||
if len(Pw2) > 0:
|
||||
P2perc = 100 / numPweights * len(Pw2)
|
||||
else:
|
||||
P2perc = 0
|
||||
if len(Pw3) > 0:
|
||||
P3perc = 100 / numPweights * len(Pw3)
|
||||
else:
|
||||
P3perc = 0
|
||||
if len(Pw4) > 0:
|
||||
P4perc = 100 / numPweights * len(Pw4)
|
||||
else:
|
||||
P4perc = 0
|
||||
if len(Sw0) > 0:
|
||||
S0perc = 100 / numSweights * len(Sw0)
|
||||
else:
|
||||
S0perc = 0
|
||||
if len(Sw1) > 0:
|
||||
S1perc = 100 / numSweights * len(Sw1)
|
||||
else:
|
||||
S1perc = 0
|
||||
if len(Sw2) > 0:
|
||||
S2perc = 100 / numSweights * len(Sw2)
|
||||
else:
|
||||
S2perc = 0
|
||||
if len(Sw3) > 0:
|
||||
S3perc = 100 / numSweights * len(Sw3)
|
||||
else:
|
||||
S3perc = 0
|
||||
if len(Sw4) > 0:
|
||||
S4perc = 100 / numSweights * len(Sw4)
|
||||
else:
|
||||
S4perc = 0
|
||||
listP, numPweights = calc_weight_perc(weights['P'], weight_ids)
|
||||
listS, numSweights = calc_weight_perc(weights['S'], weight_ids)
|
||||
|
||||
weights = ('0', '1', '2', '3', '4')
|
||||
y_pos = np.arange(len(weights))
|
||||
y_pos = np.arange(len(weight_ids))
|
||||
width = 0.34
|
||||
plt.bar(y_pos - width, [P0perc, P1perc, P2perc, P3perc, P4perc], width, color='black')
|
||||
plt.bar(y_pos, [S0perc, S1perc, S2perc, S3perc, S4perc], width, color='red')
|
||||
plt.ylabel('%')
|
||||
plt.xticks(y_pos, weights)
|
||||
plt.xlim([-0.5, 4.5])
|
||||
plt.xlabel('Qualities')
|
||||
plt.title('{0} P-Qualities, {1} S-Qualities'.format(numPweights, numSweights))
|
||||
plt.show()
|
||||
ax.bar(y_pos - width, listP, width, color='black')
|
||||
ax.bar(y_pos, listS, width, color='red')
|
||||
ax.set_ylabel('%')
|
||||
ax.set_xticks(y_pos, weight_ids)
|
||||
ax.set_xlim([-0.5, 4.5])
|
||||
ax.set_xlabel('Qualities')
|
||||
ax.set_title('{0} P-Qualities, {1} S-Qualities'.format(numPweights, numSweights))
|
||||
|
||||
if not figure:
|
||||
fig.show()
|
||||
|
||||
return listP, listS
|
||||
|
||||
@ -4,11 +4,12 @@
|
||||
import glob
|
||||
import os
|
||||
import subprocess
|
||||
|
||||
from obspy import read_events
|
||||
|
||||
from pylot.core.io.phases import writephases
|
||||
from pylot.core.util.utils import getPatternLine, runProgram
|
||||
from pylot.core.util.gui import which
|
||||
from pylot.core.util.utils import getPatternLine, runProgram
|
||||
from pylot.core.util.version import get_git_version as _getVersionString
|
||||
|
||||
__version__ = _getVersionString()
|
||||
|
||||
@ -9,21 +9,21 @@ function conglomerate utils.
|
||||
:author: MAGS2 EP3 working group / Ludger Kueperkoch
|
||||
"""
|
||||
import copy
|
||||
import traceback
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import traceback
|
||||
from obspy import Trace
|
||||
from obspy.taup import TauPyModel
|
||||
|
||||
from pylot.core.pick.charfuns import CharacteristicFunction
|
||||
from pylot.core.pick.charfuns import HOScf, AICcf, ARZcf, ARHcf, AR3Ccf
|
||||
from pylot.core.pick.picker import AICPicker, PragPicker
|
||||
from pylot.core.pick.utils import checksignallength, checkZ4S, earllatepicker, \
|
||||
getSNR, fmpicker, checkPonsets, wadaticheck, get_pickparams, get_quality_class
|
||||
from pylot.core.util.utils import getPatternLine, gen_Pool,\
|
||||
getSNR, fmpicker, checkPonsets, wadaticheck, get_quality_class
|
||||
from pylot.core.util.utils import getPatternLine, gen_Pool, \
|
||||
get_Bool, identifyPhaseID, get_None, correct_iplot
|
||||
|
||||
from obspy.taup import TauPyModel
|
||||
from obspy import Trace
|
||||
|
||||
def autopickevent(data, param, iplot=0, fig_dict=None, fig_dict_wadatijack=None, ncores=0, metadata=None, origin=None):
|
||||
"""
|
||||
@ -337,7 +337,8 @@ class AutopickStation(object):
|
||||
for key in self.channelorder:
|
||||
waveform_data[key] = self.wfstream.select(component=key) # try ZNE first
|
||||
if len(waveform_data[key]) == 0:
|
||||
waveform_data[key] = self.wfstream.select(component=str(self.channelorder[key])) # use 123 as second option
|
||||
waveform_data[key] = self.wfstream.select(
|
||||
component=str(self.channelorder[key])) # use 123 as second option
|
||||
return waveform_data['Z'], waveform_data['N'], waveform_data['E']
|
||||
|
||||
def get_traces_from_streams(self):
|
||||
@ -474,13 +475,9 @@ class AutopickStation(object):
|
||||
# TODO here the pickparams is modified, instead of a copy
|
||||
self.pickparams["pstart"] = 0
|
||||
|
||||
if self.pickparams["use_taup"] is False or not self.origin or not self.metadata:
|
||||
if self.pickparams["use_taup"] is False:
|
||||
# correct user mistake where a relative cuttime is selected (pstart < 0) but use of taupy is disabled/ has
|
||||
# not the required parameters
|
||||
if not self.origin:
|
||||
print('Requested use_taup but no origin given. Exit taupy.')
|
||||
if not self.metadata:
|
||||
print('Requested use_taup but no metadata given. Exit taupy.')
|
||||
exit_taupy()
|
||||
return
|
||||
|
||||
@ -528,7 +525,7 @@ class AutopickStation(object):
|
||||
|
||||
self.plot_pick_results()
|
||||
self.finish_picking()
|
||||
return [{'P': self.p_results, 'S':self.s_results}, self.ztrace.stats.station]
|
||||
return [{'P': self.p_results, 'S': self.s_results}, self.ztrace.stats.station]
|
||||
|
||||
def finish_picking(self):
|
||||
|
||||
@ -592,12 +589,14 @@ class AutopickStation(object):
|
||||
plt_flag = 0
|
||||
fig._tight = True
|
||||
ax1 = fig.add_subplot(311)
|
||||
tdata = np.linspace(start=0, stop=self.ztrace.stats.endtime-self.ztrace.stats.starttime, num=self.ztrace.stats.npts)
|
||||
tdata = np.linspace(start=0, stop=self.ztrace.stats.endtime - self.ztrace.stats.starttime,
|
||||
num=self.ztrace.stats.npts)
|
||||
# plot tapered trace filtered with bpz2 filter settings
|
||||
ax1.plot(tdata, self.tr_filt_z_bpz2.data/max(self.tr_filt_z_bpz2.data), color=linecolor, linewidth=0.7, label='Data')
|
||||
ax1.plot(tdata, self.tr_filt_z_bpz2.data / max(self.tr_filt_z_bpz2.data), color=linecolor, linewidth=0.7,
|
||||
label='Data')
|
||||
if self.p_results.weight < 4:
|
||||
# plot CF of initial onset (HOScf or ARZcf)
|
||||
ax1.plot(self.cf1.getTimeArray(), self.cf1.getCF()/max(self.cf1.getCF()), 'b', label='CF1')
|
||||
ax1.plot(self.cf1.getTimeArray(), self.cf1.getCF() / max(self.cf1.getCF()), 'b', label='CF1')
|
||||
if self.p_data.p_aic_plot_flag == 1:
|
||||
aicpick = self.p_data.aicpick
|
||||
refPpick = self.p_data.refPpick
|
||||
@ -635,23 +634,28 @@ class AutopickStation(object):
|
||||
if self.horizontal_traces_exist() and self.s_data.Sflag == 1:
|
||||
# plot E trace
|
||||
ax2 = fig.add_subplot(3, 1, 2, sharex=ax1)
|
||||
th1data = np.linspace(0, self.etrace.stats.endtime-self.etrace.stats.starttime, self.etrace.stats.npts)
|
||||
th1data = np.linspace(0, self.etrace.stats.endtime - self.etrace.stats.starttime,
|
||||
self.etrace.stats.npts)
|
||||
# plot filtered and tapered waveform
|
||||
ax2.plot(th1data, self.etrace.data / max(self.etrace.data), color=linecolor, linewidth=0.7, label='Data')
|
||||
ax2.plot(th1data, self.etrace.data / max(self.etrace.data), color=linecolor, linewidth=0.7,
|
||||
label='Data')
|
||||
if self.p_results.weight < 4:
|
||||
# plot initial CF (ARHcf or AR3Ccf)
|
||||
ax2.plot(self.arhcf1.getTimeArray(), self.arhcf1.getCF() / max(self.arhcf1.getCF()), 'b', label='CF1')
|
||||
ax2.plot(self.arhcf1.getTimeArray(), self.arhcf1.getCF() / max(self.arhcf1.getCF()), 'b',
|
||||
label='CF1')
|
||||
if self.s_data.aicSflag == 1 and self.s_results.weight <= 4:
|
||||
aicarhpick = self.aicarhpick
|
||||
refSpick = self.refSpick
|
||||
# plot second cf, used for determing precise onset (ARHcf or AR3Ccf)
|
||||
ax2.plot(self.arhcf2.getTimeArray(), self.arhcf2.getCF() / max(self.arhcf2.getCF()), 'm', label='CF2')
|
||||
ax2.plot(self.arhcf2.getTimeArray(), self.arhcf2.getCF() / max(self.arhcf2.getCF()), 'm',
|
||||
label='CF2')
|
||||
# plot preliminary onset time, calculated from CF1
|
||||
ax2.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'g', label='Initial S Onset')
|
||||
ax2.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [1, 1], 'g')
|
||||
ax2.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [-1, -1], 'g')
|
||||
# plot precise onset time, calculated from CF2
|
||||
ax2.plot([refSpick.getpick(), refSpick.getpick()], [-1.3, 1.3], 'g', linewidth=2, label='Final S Pick')
|
||||
ax2.plot([refSpick.getpick(), refSpick.getpick()], [-1.3, 1.3], 'g', linewidth=2,
|
||||
label='Final S Pick')
|
||||
ax2.plot([refSpick.getpick() - 0.5, refSpick.getpick() + 0.5], [1.3, 1.3], 'g', linewidth=2)
|
||||
ax2.plot([refSpick.getpick() - 0.5, refSpick.getpick() + 0.5], [-1.3, -1.3], 'g', linewidth=2)
|
||||
ax2.plot([self.s_results.lpp, self.s_results.lpp], [-1.1, 1.1], 'g--', label='lpp')
|
||||
@ -671,15 +675,19 @@ class AutopickStation(object):
|
||||
|
||||
# plot N trace
|
||||
ax3 = fig.add_subplot(3, 1, 3, sharex=ax1)
|
||||
th2data= np.linspace(0, self.ntrace.stats.endtime-self.ntrace.stats.starttime, self.ntrace.stats.npts)
|
||||
th2data = np.linspace(0, self.ntrace.stats.endtime - self.ntrace.stats.starttime,
|
||||
self.ntrace.stats.npts)
|
||||
# plot trace
|
||||
ax3.plot(th2data, self.ntrace.data / max(self.ntrace.data), color=linecolor, linewidth=0.7, label='Data')
|
||||
ax3.plot(th2data, self.ntrace.data / max(self.ntrace.data), color=linecolor, linewidth=0.7,
|
||||
label='Data')
|
||||
if self.p_results.weight < 4:
|
||||
p22, = ax3.plot(self.arhcf1.getTimeArray(), self.arhcf1.getCF() / max(self.arhcf1.getCF()), 'b', label='CF1')
|
||||
p22, = ax3.plot(self.arhcf1.getTimeArray(), self.arhcf1.getCF() / max(self.arhcf1.getCF()), 'b',
|
||||
label='CF1')
|
||||
if self.s_data.aicSflag == 1:
|
||||
aicarhpick = self.aicarhpick
|
||||
refSpick = self.refSpick
|
||||
ax3.plot(self.arhcf2.getTimeArray(), self.arhcf2.getCF() / max(self.arhcf2.getCF()), 'm', label='CF2')
|
||||
ax3.plot(self.arhcf2.getTimeArray(), self.arhcf2.getCF() / max(self.arhcf2.getCF()), 'm',
|
||||
label='CF2')
|
||||
ax3.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'g', label='Initial S Onset')
|
||||
ax3.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [1, 1], 'g')
|
||||
ax3.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [-1, -1], 'g')
|
||||
@ -720,7 +728,8 @@ class AutopickStation(object):
|
||||
if aicpick.getpick() is None:
|
||||
msg = "Bad initial (AIC) P-pick, skipping this onset!\nAIC-SNR={0}, AIC-Slope={1}counts/s\n " \
|
||||
"(min. AIC-SNR={2}, min. AIC-Slope={3}counts/s)"
|
||||
msg = msg.format(aicpick.getSNR(), aicpick.getSlope(), self.pickparams["minAICPSNR"], self.pickparams["minAICPslope"])
|
||||
msg = msg.format(aicpick.getSNR(), aicpick.getSlope(), self.pickparams["minAICPSNR"],
|
||||
self.pickparams["minAICPslope"])
|
||||
self.vprint(msg)
|
||||
return 0
|
||||
# Quality check initial pick with minimum signal length
|
||||
@ -730,14 +739,16 @@ class AutopickStation(object):
|
||||
if len(self.nstream) == 0 or len(self.estream) == 0:
|
||||
msg = 'One or more horizontal component(s) missing!\n' \
|
||||
'Signal length only checked on vertical component!\n' \
|
||||
'Decreasing minsiglengh from {0} to {1}'\
|
||||
'Decreasing minsiglengh from {0} to {1}' \
|
||||
.format(minsiglength, minsiglength / 2)
|
||||
self.vprint(msg)
|
||||
minsiglength = minsiglength / 2
|
||||
else:
|
||||
# filter, taper other traces as well since signal length is compared on all traces
|
||||
trH1_filt, _ = self.prepare_wfstream(self.estream, freqmin=self.pickparams["bph1"][0], freqmax=self.pickparams["bph1"][1])
|
||||
trH2_filt, _ = self.prepare_wfstream(self.nstream, freqmin=self.pickparams["bph1"][0], freqmax=self.pickparams["bph1"][1])
|
||||
trH1_filt, _ = self.prepare_wfstream(self.estream, freqmin=self.pickparams["bph1"][0],
|
||||
freqmax=self.pickparams["bph1"][1])
|
||||
trH2_filt, _ = self.prepare_wfstream(self.nstream, freqmin=self.pickparams["bph1"][0],
|
||||
freqmax=self.pickparams["bph1"][1])
|
||||
zne += trH1_filt
|
||||
zne += trH2_filt
|
||||
minsiglength = minsiglength
|
||||
@ -823,15 +834,18 @@ class AutopickStation(object):
|
||||
# get preliminary onset time from AIC-CF
|
||||
self.set_current_figure('aicFig')
|
||||
aicpick = AICPicker(aiccf, self.pickparams["tsnrz"], self.pickparams["pickwinP"], self.iplot,
|
||||
Tsmooth=self.pickparams["aictsmooth"], fig=self.current_figure, linecolor=self.current_linecolor)
|
||||
Tsmooth=self.pickparams["aictsmooth"], fig=self.current_figure,
|
||||
linecolor=self.current_linecolor)
|
||||
# save aicpick for plotting later
|
||||
self.p_data.aicpick = aicpick
|
||||
# add pstart and pstop to aic plot
|
||||
if self.current_figure:
|
||||
# TODO remove plotting from picking, make own plot function
|
||||
for ax in self.current_figure.axes:
|
||||
ax.vlines(self.pickparams["pstart"], ax.get_ylim()[0], ax.get_ylim()[1], color='c', linestyles='dashed', label='P start')
|
||||
ax.vlines(self.pickparams["pstop"], ax.get_ylim()[0], ax.get_ylim()[1], color='c', linestyles='dashed', label='P stop')
|
||||
ax.vlines(self.pickparams["pstart"], ax.get_ylim()[0], ax.get_ylim()[1], color='c', linestyles='dashed',
|
||||
label='P start')
|
||||
ax.vlines(self.pickparams["pstop"], ax.get_ylim()[0], ax.get_ylim()[1], color='c', linestyles='dashed',
|
||||
label='P stop')
|
||||
ax.legend(loc=1)
|
||||
|
||||
Pflag = self._pick_p_quality_control(aicpick, z_copy, tr_filt)
|
||||
@ -845,7 +859,8 @@ class AutopickStation(object):
|
||||
error_msg = 'AIC P onset slope to small: got {}, min {}'.format(slope, self.pickparams["minAICPslope"])
|
||||
raise PickingFailedException(error_msg)
|
||||
if aicpick.getSNR() < self.pickparams["minAICPSNR"]:
|
||||
error_msg = 'AIC P onset SNR to small: got {}, min {}'.format(aicpick.getSNR(), self.pickparams["minAICPSNR"])
|
||||
error_msg = 'AIC P onset SNR to small: got {}, min {}'.format(aicpick.getSNR(),
|
||||
self.pickparams["minAICPSNR"])
|
||||
raise PickingFailedException(error_msg)
|
||||
|
||||
self.p_data.p_aic_plot_flag = 1
|
||||
@ -853,7 +868,8 @@ class AutopickStation(object):
|
||||
'autopickstation: re-filtering vertical trace...'.format(aicpick.getSlope(), aicpick.getSNR())
|
||||
self.vprint(msg)
|
||||
# refilter waveform with larger bandpass
|
||||
tr_filt, z_copy = self.prepare_wfstream(self.zstream, freqmin=self.pickparams["bpz2"][0], freqmax=self.pickparams["bpz2"][1])
|
||||
tr_filt, z_copy = self.prepare_wfstream(self.zstream, freqmin=self.pickparams["bpz2"][0],
|
||||
freqmax=self.pickparams["bpz2"][1])
|
||||
# save filtered trace in instance for later plotting
|
||||
self.tr_filt_z_bpz2 = tr_filt
|
||||
# determine new times around initial onset
|
||||
@ -868,22 +884,26 @@ class AutopickStation(object):
|
||||
'corrupted'.format(self.pickparams["algoP"])
|
||||
self.set_current_figure('refPpick')
|
||||
# get refined onset time from CF2
|
||||
refPpick = PragPicker(self.cf2, self.pickparams["tsnrz"], self.pickparams["pickwinP"], self.iplot, self.pickparams["ausP"],
|
||||
self.pickparams["tsmoothP"], aicpick.getpick(), self.current_figure, self.current_linecolor)
|
||||
refPpick = PragPicker(self.cf2, self.pickparams["tsnrz"], self.pickparams["pickwinP"], self.iplot,
|
||||
self.pickparams["ausP"],
|
||||
self.pickparams["tsmoothP"], aicpick.getpick(), self.current_figure,
|
||||
self.current_linecolor)
|
||||
# save PragPicker result for plotting
|
||||
self.p_data.refPpick = refPpick
|
||||
self.p_results.mpp = refPpick.getpick()
|
||||
if self.p_results.mpp is None:
|
||||
msg = 'Bad initial (AIC) P-pick, skipping this onset!\n AIC-SNR={}, AIC-Slope={}counts/s\n' \
|
||||
'(min. AIC-SNR={}, min. AIC-Slope={}counts/s)'
|
||||
msg.format(aicpick.getSNR(), aicpick.getSlope(), self.pickparams["minAICPSNR"], self.pickparams["minAICPslope"])
|
||||
msg.format(aicpick.getSNR(), aicpick.getSlope(), self.pickparams["minAICPSNR"],
|
||||
self.pickparams["minAICPslope"])
|
||||
self.vprint(msg)
|
||||
self.s_data.Sflag = 0
|
||||
raise PickingFailedException(msg)
|
||||
# quality assessment, get earliest/latest pick and symmetrized uncertainty
|
||||
#todo quality assessment in own function
|
||||
# todo quality assessment in own function
|
||||
self.set_current_figure('el_Ppick')
|
||||
elpicker_results = earllatepicker(z_copy, self.pickparams["nfacP"], self.pickparams["tsnrz"], self.p_results.mpp,
|
||||
elpicker_results = earllatepicker(z_copy, self.pickparams["nfacP"], self.pickparams["tsnrz"],
|
||||
self.p_results.mpp,
|
||||
self.iplot, fig=self.current_figure, linecolor=self.current_linecolor)
|
||||
self.p_results.epp, self.p_results.lpp, self.p_results.spe = elpicker_results
|
||||
snr_results = getSNR(z_copy, self.pickparams["tsnrz"], self.p_results.mpp)
|
||||
@ -891,7 +911,8 @@ class AutopickStation(object):
|
||||
|
||||
# weight P-onset using symmetric error
|
||||
self.p_results.weight = get_quality_class(self.p_results.spe, self.pickparams["timeerrorsP"])
|
||||
if self.p_results.weight <= self.pickparams["minfmweight"] and self.p_results.snr >= self.pickparams["minFMSNR"]:
|
||||
if self.p_results.weight <= self.pickparams["minfmweight"] and self.p_results.snr >= self.pickparams[
|
||||
"minFMSNR"]:
|
||||
# if SNR is high enough, try to determine first motion of onset
|
||||
self.set_current_figure('fm_picker')
|
||||
self.p_results.fm = fmpicker(self.zstream, z_copy, self.pickparams["fmpickwin"], self.p_results.mpp,
|
||||
@ -964,7 +985,7 @@ class AutopickStation(object):
|
||||
trH1_filt, _ = self.prepare_wfstream(self.zstream, filter_freq_min, filter_freq_max)
|
||||
trH2_filt, _ = self.prepare_wfstream(self.estream, filter_freq_min, filter_freq_max)
|
||||
trH3_filt, _ = self.prepare_wfstream(self.nstream, filter_freq_min, filter_freq_max)
|
||||
h_copy =self. hdat.copy()
|
||||
h_copy = self.hdat.copy()
|
||||
h_copy[0].data = trH1_filt.data
|
||||
h_copy[1].data = trH2_filt.data
|
||||
h_copy[2].data = trH3_filt.data
|
||||
@ -1119,7 +1140,8 @@ class AutopickStation(object):
|
||||
# get preliminary onset time from AIC cf
|
||||
self.set_current_figure('aicARHfig')
|
||||
aicarhpick = AICPicker(haiccf, self.pickparams["tsnrh"], self.pickparams["pickwinS"], self.iplot,
|
||||
Tsmooth=self.pickparams["aictsmoothS"], fig=self.current_figure, linecolor=self.current_linecolor)
|
||||
Tsmooth=self.pickparams["aictsmoothS"], fig=self.current_figure,
|
||||
linecolor=self.current_linecolor)
|
||||
# save pick for later plotting
|
||||
self.aicarhpick = aicarhpick
|
||||
|
||||
@ -1130,8 +1152,10 @@ class AutopickStation(object):
|
||||
|
||||
# get refined onset time from CF2
|
||||
self.set_current_figure('refSpick')
|
||||
refSpick = PragPicker(arhcf2, self.pickparams["tsnrh"], self.pickparams["pickwinS"], self.iplot, self.pickparams["ausS"],
|
||||
self.pickparams["tsmoothS"], aicarhpick.getpick(), self.current_figure, self.current_linecolor)
|
||||
refSpick = PragPicker(arhcf2, self.pickparams["tsnrh"], self.pickparams["pickwinS"], self.iplot,
|
||||
self.pickparams["ausS"],
|
||||
self.pickparams["tsmoothS"], aicarhpick.getpick(), self.current_figure,
|
||||
self.current_linecolor)
|
||||
# save refSpick for later plotitng
|
||||
self.refSpick = refSpick
|
||||
self.s_results.mpp = refSpick.getpick()
|
||||
@ -1155,7 +1179,6 @@ class AutopickStation(object):
|
||||
self.current_linecolor = plot_style['linecolor']['rgba_mpl']
|
||||
|
||||
|
||||
|
||||
def autopickstation(wfstream, pickparam, verbose=False, iplot=0, fig_dict=None, metadata=None, origin=None):
|
||||
"""
|
||||
Main function to calculate picks for the station.
|
||||
|
||||
@ -18,8 +18,8 @@ autoregressive prediction: application ot local and regional distances, Geophys.
|
||||
"""
|
||||
|
||||
import numpy as np
|
||||
from scipy import signal
|
||||
from obspy.core import Stream
|
||||
from scipy import signal
|
||||
|
||||
|
||||
class CharacteristicFunction(object):
|
||||
@ -150,7 +150,7 @@ class CharacteristicFunction(object):
|
||||
if self.cut[0] == 0 and self.cut[1] == 0:
|
||||
start = 0
|
||||
stop = len(self.orig_data[0])
|
||||
elif self.cut[0] == 0 and self.cut[1] is not 0:
|
||||
elif self.cut[0] == 0 and self.cut[1] != 0:
|
||||
start = 0
|
||||
stop = self.cut[1] / self.dt
|
||||
else:
|
||||
@ -167,7 +167,7 @@ class CharacteristicFunction(object):
|
||||
if self.cut[0] == 0 and self.cut[1] == 0:
|
||||
start = 0
|
||||
stop = min([len(self.orig_data[0]), len(self.orig_data[1])])
|
||||
elif self.cut[0] == 0 and self.cut[1] is not 0:
|
||||
elif self.cut[0] == 0 and self.cut[1] != 0:
|
||||
start = 0
|
||||
stop = min([self.cut[1] / self.dt, len(self.orig_data[0]),
|
||||
len(self.orig_data[1])])
|
||||
@ -187,7 +187,7 @@ class CharacteristicFunction(object):
|
||||
start = 0
|
||||
stop = min([self.cut[1] / self.dt, len(self.orig_data[0]),
|
||||
len(self.orig_data[1]), len(self.orig_data[2])])
|
||||
elif self.cut[0] == 0 and self.cut[1] is not 0:
|
||||
elif self.cut[0] == 0 and self.cut[1] != 0:
|
||||
start = 0
|
||||
stop = self.cut[1] / self.dt
|
||||
else:
|
||||
@ -313,7 +313,8 @@ class HOScf(CharacteristicFunction):
|
||||
class ARZcf(CharacteristicFunction):
|
||||
|
||||
def __init__(self, data, cut, t1, t2, pickparams):
|
||||
super(ARZcf, self).__init__(data, cut, t1=t1, t2=t2, order=pickparams["Parorder"], fnoise=pickparams["addnoise"])
|
||||
super(ARZcf, self).__init__(data, cut, t1=t1, t2=t2, order=pickparams["Parorder"],
|
||||
fnoise=pickparams["addnoise"])
|
||||
|
||||
def calcCF(self, data):
|
||||
"""
|
||||
@ -448,7 +449,8 @@ class ARZcf(CharacteristicFunction):
|
||||
class ARHcf(CharacteristicFunction):
|
||||
|
||||
def __init__(self, data, cut, t1, t2, pickparams):
|
||||
super(ARHcf, self).__init__(data, cut, t1=t1, t2=t2, order=pickparams["Sarorder"], fnoise=pickparams["addnoise"])
|
||||
super(ARHcf, self).__init__(data, cut, t1=t1, t2=t2, order=pickparams["Sarorder"],
|
||||
fnoise=pickparams["addnoise"])
|
||||
|
||||
def calcCF(self, data):
|
||||
"""
|
||||
@ -600,7 +602,8 @@ class ARHcf(CharacteristicFunction):
|
||||
class AR3Ccf(CharacteristicFunction):
|
||||
|
||||
def __init__(self, data, cut, t1, t2, pickparams):
|
||||
super(AR3Ccf, self).__init__(data, cut, t1=t1, t2=t2, order=pickparams["Sarorder"], fnoise=pickparams["addnoise"])
|
||||
super(AR3Ccf, self).__init__(data, cut, t1=t1, t2=t2, order=pickparams["Sarorder"],
|
||||
fnoise=pickparams["addnoise"])
|
||||
|
||||
def calcCF(self, data):
|
||||
"""
|
||||
|
||||
@ -2,10 +2,11 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
import copy
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import operator
|
||||
import os
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
from obspy.core import AttribDict
|
||||
|
||||
from pylot.core.util.pdf import ProbabilityDensityFunction
|
||||
@ -401,6 +402,8 @@ class PDFstatistics(object):
|
||||
Takes a path as argument.
|
||||
"""
|
||||
|
||||
# TODO: change root to datapath
|
||||
|
||||
def __init__(self, directory):
|
||||
"""Initiates some values needed when dealing with pdfs later"""
|
||||
self._rootdir = directory
|
||||
|
||||
@ -19,9 +19,10 @@ calculated after Diehl & Kissling (2009).
|
||||
:author: MAGS2 EP3 working group / Ludger Kueperkoch
|
||||
"""
|
||||
|
||||
import warnings
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import warnings
|
||||
from scipy.signal import argrelmax, argrelmin
|
||||
|
||||
from pylot.core.pick.charfuns import CharacteristicFunction
|
||||
@ -476,7 +477,7 @@ class PragPicker(AutoPicker):
|
||||
cfpick_r = 0
|
||||
cfpick_l = 0
|
||||
lpickwindow = int(round(self.PickWindow / self.dt))
|
||||
#for i in range(max(np.insert(ipick, 0, 2)), min([ipick1 + lpickwindow + 1, len(self.cf) - 1])):
|
||||
# for i in range(max(np.insert(ipick, 0, 2)), min([ipick1 + lpickwindow + 1, len(self.cf) - 1])):
|
||||
# # local minimum
|
||||
# if self.cf[i + 1] > self.cf[i] <= self.cf[i - 1]:
|
||||
# if cfsmooth[i - 1] * (1 + aus1) >= cfsmooth[i]:
|
||||
|
||||
@ -9,10 +9,11 @@
|
||||
"""
|
||||
|
||||
import warnings
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
from scipy.signal import argrelmax
|
||||
from obspy.core import Stream, UTCDateTime
|
||||
from scipy.signal import argrelmax
|
||||
|
||||
from pylot.core.util.utils import get_Bool, get_None, SetChannelComponents
|
||||
|
||||
@ -536,9 +537,10 @@ def getslopewin(Tcf, Pick, tslope):
|
||||
:rtype: `numpy.ndarray`
|
||||
"""
|
||||
# TODO: fill out docstring
|
||||
slope = np.where( (Tcf <= min(Pick + tslope, Tcf[-1])) & (Tcf >= Pick) )
|
||||
slope = np.where((Tcf <= min(Pick + tslope, Tcf[-1])) & (Tcf >= Pick))
|
||||
return slope[0]
|
||||
|
||||
|
||||
def getResolutionWindow(snr, extent):
|
||||
"""
|
||||
Produce the half of the time resolution window width from given SNR value
|
||||
@ -1318,6 +1320,7 @@ def get_quality_class(uncertainty, weight_classes):
|
||||
:return: quality of pick (0-4)
|
||||
:rtype: int
|
||||
"""
|
||||
if not uncertainty: return len(weight_classes)
|
||||
try:
|
||||
# create generator expression containing all indices of values in weight classes that are >= than uncertainty.
|
||||
# call next on it once to receive first value
|
||||
@ -1328,6 +1331,7 @@ def get_quality_class(uncertainty, weight_classes):
|
||||
quality = len(weight_classes)
|
||||
return quality
|
||||
|
||||
|
||||
def set_NaNs_to(data, nan_value):
|
||||
"""
|
||||
Replace all NaNs in data with nan_value
|
||||
@ -1343,6 +1347,7 @@ def set_NaNs_to(data, nan_value):
|
||||
data[nn] = nan_value
|
||||
return data
|
||||
|
||||
|
||||
def taper_cf(cf):
|
||||
"""
|
||||
Taper cf data to get rid off of side maximas
|
||||
@ -1354,6 +1359,7 @@ def taper_cf(cf):
|
||||
tap = np.hanning(len(cf))
|
||||
return tap * cf
|
||||
|
||||
|
||||
def cf_positive(cf):
|
||||
"""
|
||||
Shifts cf so that all values are positive
|
||||
@ -1364,6 +1370,7 @@ def cf_positive(cf):
|
||||
"""
|
||||
return cf + max(abs(cf))
|
||||
|
||||
|
||||
def smooth_cf(cf, t_smooth, delta):
|
||||
"""
|
||||
Smooth cf by taking samples over t_smooth length
|
||||
@ -1392,6 +1399,7 @@ def smooth_cf(cf, t_smooth, delta):
|
||||
cf_smooth -= offset # remove offset from smoothed function
|
||||
return cf_smooth
|
||||
|
||||
|
||||
def check_counts_ms(data):
|
||||
"""
|
||||
check if data is in counts or m/s
|
||||
@ -1474,8 +1482,10 @@ def get_pickparams(pickparam):
|
||||
:rtype: (dict, dict, dict, dict)
|
||||
"""
|
||||
# Define names of all parameters in different groups
|
||||
p_parameter_names = 'algoP pstart pstop use_taup taup_model tlta tsnrz hosorder bpz1 bpz2 pickwinP aictsmooth tsmoothP ausP nfacP tpred1z tdet1z Parorder addnoise Precalcwin minAICPslope minAICPSNR timeerrorsP checkwindowP minfactorP'.split(' ')
|
||||
s_parameter_names = 'algoS sstart sstop bph1 bph2 tsnrh pickwinS tpred1h tdet1h tpred2h tdet2h Sarorder aictsmoothS tsmoothS ausS minAICSslope minAICSSNR Srecalcwin nfacS timeerrorsS zfac checkwindowS minfactorS'.split(' ')
|
||||
p_parameter_names = 'algoP pstart pstop use_taup taup_model tlta tsnrz hosorder bpz1 bpz2 pickwinP aictsmooth tsmoothP ausP nfacP tpred1z tdet1z Parorder addnoise Precalcwin minAICPslope minAICPSNR timeerrorsP checkwindowP minfactorP'.split(
|
||||
' ')
|
||||
s_parameter_names = 'algoS sstart sstop bph1 bph2 tsnrh pickwinS tpred1h tdet1h tpred2h tdet2h Sarorder aictsmoothS tsmoothS ausS minAICSslope minAICSSNR Srecalcwin nfacS timeerrorsS zfac checkwindowS minfactorS'.split(
|
||||
' ')
|
||||
first_motion_names = 'minFMSNR fmpickwin minfmweight'.split(' ')
|
||||
signal_length_names = 'minsiglength minpercent noisefactor'.split(' ')
|
||||
# Get list of values from pickparam by name
|
||||
@ -1493,6 +1503,7 @@ def get_pickparams(pickparam):
|
||||
|
||||
return p_params, s_params, first_motion_params, signal_length_params
|
||||
|
||||
|
||||
def getQualityFromUncertainty(uncertainty, Errors):
|
||||
# set initial quality to 4 (worst) and change only if one condition is hit
|
||||
quality = 4
|
||||
@ -1516,6 +1527,7 @@ def getQualityFromUncertainty(uncertainty, Errors):
|
||||
|
||||
return quality
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
import doctest
|
||||
|
||||
|
||||
@ -1,38 +1,51 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
import os
|
||||
import traceback
|
||||
|
||||
import cartopy.crs as ccrs
|
||||
import cartopy.feature as cf
|
||||
import matplotlib
|
||||
import matplotlib.patheffects as PathEffects
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import obspy
|
||||
import traceback
|
||||
from PySide import QtGui
|
||||
from matplotlib.figure import Figure
|
||||
from PySide2 import QtWidgets
|
||||
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
|
||||
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
|
||||
from mpl_toolkits.basemap import Basemap
|
||||
from scipy.interpolate import griddata
|
||||
|
||||
from pylot.core.util.widgets import PickDlg, PylotCanvas
|
||||
from pylot.core.pick.utils import get_quality_class
|
||||
from pylot.core.util.widgets import PickDlg
|
||||
|
||||
plt.interactive(False)
|
||||
matplotlib.use('Qt5Agg')
|
||||
|
||||
|
||||
class Array_map(QtGui.QWidget):
|
||||
def __init__(self, parent, metadata, parameter=None, figure=None, annotate=True, pointsize=25.,
|
||||
class MplCanvas(FigureCanvas):
|
||||
|
||||
def __init__(self, parent=None, extern_axes=None, width=5, height=4, dpi=100):
|
||||
if extern_axes is None:
|
||||
self.fig = plt.figure(figsize=(width, height), dpi=dpi)
|
||||
self.axes = self.fig.add_subplot(111)
|
||||
else:
|
||||
self.fig = extern_axes.figure
|
||||
self.axes = extern_axes
|
||||
|
||||
super(MplCanvas, self).__init__(self.fig)
|
||||
|
||||
|
||||
class Array_map(QtWidgets.QWidget):
|
||||
def __init__(self, parent, metadata, parameter=None, axes=None, annotate=True, pointsize=25.,
|
||||
linewidth=1.5, width=5e6, height=2e6):
|
||||
'''
|
||||
Create a map of the array.
|
||||
:param parent: object of PyLoT Mainwindow class
|
||||
:param parameter: object of PyLoT parameter class
|
||||
:param figure:
|
||||
'''
|
||||
QtGui.QWidget.__init__(self)
|
||||
assert (parameter != None or parent != None), 'either parent or parameter has to be set'
|
||||
QtWidgets.QWidget.__init__(self, parent=parent)
|
||||
|
||||
assert (parameter is not None or parent is not None), 'either parent or parameter has to be set'
|
||||
# set properties
|
||||
self._parent = parent
|
||||
self.metadata = metadata
|
||||
self.pointsize = pointsize
|
||||
self.linewidth = linewidth
|
||||
self.extern_plot_axes = axes
|
||||
self.width = width
|
||||
self.height = height
|
||||
self.annotate = annotate
|
||||
@ -43,34 +56,228 @@ class Array_map(QtGui.QWidget):
|
||||
self.hybrids_dict = None
|
||||
self.eventLoc = None
|
||||
self.parameter = parameter if parameter else parent._inputs
|
||||
self.figure = figure
|
||||
|
||||
self.picks_rel = {}
|
||||
self.marked_stations = []
|
||||
self.highlighted_stations = []
|
||||
|
||||
# call functions to draw everything
|
||||
self.init_graphics()
|
||||
self.init_stations()
|
||||
self.init_basemap(resolution='l')
|
||||
self.init_crtpyMap()
|
||||
self.init_map()
|
||||
self._style = None if not hasattr(parent, '_style') else parent._style
|
||||
# self.show()
|
||||
# set original map limits to fall back on when home button is pressed
|
||||
self.org_xlim = self.canvas.axes.get_xlim()
|
||||
self.org_ylim = self.canvas.axes.get_ylim()
|
||||
# initial map without event
|
||||
self.canvas.axes.set_xlim(self.org_xlim[0], self.org_xlim[1])
|
||||
self.canvas.axes.set_ylim(self.org_ylim[0], self.org_ylim[1])
|
||||
|
||||
def update_hybrids_dict(self):
|
||||
self.hybrids_dict = self.picks_dict.copy()
|
||||
for station, pick in self.autopicks_dict.items():
|
||||
if not station in self.hybrids_dict.keys():
|
||||
self.hybrids_dict[station] = pick
|
||||
return self.hybrids_dict
|
||||
self._style = None if not hasattr(parent, '_style') else parent._style
|
||||
|
||||
self.show()
|
||||
|
||||
def init_map(self):
|
||||
self.init_colormap()
|
||||
self.connectSignals()
|
||||
self.draw_everything()
|
||||
self.canvas.setZoomBorders2content()
|
||||
|
||||
def init_graphics(self):
|
||||
"""
|
||||
Initializes all GUI components and figure elements to be populated by other functions
|
||||
"""
|
||||
# initialize figure elements
|
||||
|
||||
if self.extern_plot_axes is None:
|
||||
self.canvas = MplCanvas(self)
|
||||
self.plotWidget = FigureCanvas(self.canvas.fig)
|
||||
else:
|
||||
self.canvas = MplCanvas(self, extern_axes=self.extern_plot_axes)
|
||||
self.plotWidget = FigureCanvas(self.canvas.fig)
|
||||
|
||||
# initialize GUI elements
|
||||
|
kaan marked this conversation as resolved
Outdated
sebastianw
commented
Typo: populated Typo: populated
|
||||
self.status_label = QtWidgets.QLabel()
|
||||
self.map_reset_button = QtWidgets.QPushButton('Reset Map View')
|
||||
self.save_map_button = QtWidgets.QPushButton('Save Map')
|
||||
self.go2eq_button = QtWidgets.QPushButton('Go to Event Location')
|
||||
|
||||
self.main_box = QtWidgets.QVBoxLayout()
|
||||
self.setLayout(self.main_box)
|
||||
|
||||
self.top_row = QtWidgets.QHBoxLayout()
|
||||
self.main_box.addLayout(self.top_row, 1)
|
||||
|
kaan marked this conversation as resolved
Outdated
sebastianw
commented
see above, commented code see above, commented code
|
||||
|
||||
self.comboBox_phase = QtWidgets.QComboBox()
|
||||
self.comboBox_phase.insertItem(0, 'P')
|
||||
self.comboBox_phase.insertItem(1, 'S')
|
||||
|
||||
self.comboBox_am = QtWidgets.QComboBox()
|
||||
self.comboBox_am.insertItem(0, 'hybrid (prefer manual)')
|
||||
self.comboBox_am.insertItem(1, 'manual')
|
||||
self.comboBox_am.insertItem(2, 'auto')
|
||||
|
||||
self.annotations_box = QtWidgets.QCheckBox('Annotate')
|
||||
self.annotations_box.setChecked(True)
|
||||
self.auto_refresh_box = QtWidgets.QCheckBox('Automatic refresh')
|
||||
self.auto_refresh_box.setChecked(True)
|
||||
self.refresh_button = QtWidgets.QPushButton('Refresh')
|
||||
self.cmaps_box = QtWidgets.QComboBox()
|
||||
self.cmaps_box.setMaxVisibleItems(20)
|
||||
[self.cmaps_box.addItem(map_name) for map_name in sorted(plt.colormaps())]
|
||||
# try to set to hsv as default
|
||||
self.cmaps_box.setCurrentIndex(self.cmaps_box.findText('hsv'))
|
||||
|
||||
self.top_row.addWidget(QtWidgets.QLabel('Select a phase: '))
|
||||
self.top_row.addWidget(self.comboBox_phase)
|
||||
self.top_row.setStretch(1, 1) # set stretch of item 1 to 1
|
||||
self.top_row.addWidget(QtWidgets.QLabel('Pick type: '))
|
||||
self.top_row.addWidget(self.comboBox_am)
|
||||
self.top_row.setStretch(3, 1) # set stretch of item 1 to 1
|
||||
self.top_row.addWidget(self.cmaps_box)
|
||||
self.top_row.addWidget(self.annotations_box)
|
||||
self.top_row.addWidget(self.auto_refresh_box)
|
||||
self.top_row.addWidget(self.refresh_button)
|
||||
|
||||
self.main_box.addWidget(self.plotWidget, 1)
|
||||
|
||||
self.bot_row = QtWidgets.QHBoxLayout()
|
||||
self.main_box.addLayout(self.bot_row, 0.3)
|
||||
self.bot_row.addWidget(QtWidgets.QLabel(''), 5)
|
||||
self.bot_row.addWidget(self.map_reset_button, 2)
|
||||
self.bot_row.addWidget(self.go2eq_button, 2)
|
||||
self.bot_row.addWidget(self.save_map_button, 2)
|
||||
self.bot_row.addWidget(self.status_label, 5)
|
||||
|
||||
def init_colormap(self):
|
||||
self.init_lat_lon_dimensions()
|
||||
self.init_lat_lon_grid()
|
||||
self.init_x_y_dimensions()
|
||||
|
||||
def init_crtpyMap(self):
|
||||
self.canvas.axes.cla()
|
||||
self.canvas.axes = plt.axes(projection=ccrs.PlateCarree())
|
||||
self.canvas.axes.add_feature(cf.LAND)
|
||||
self.canvas.axes.add_feature(cf.OCEAN)
|
||||
self.canvas.axes.add_feature(cf.COASTLINE, linewidth=1, edgecolor='gray')
|
||||
self.canvas.axes.add_feature(cf.BORDERS, alpha=0.7)
|
||||
self.canvas.axes.add_feature(cf.LAKES, alpha=0.7)
|
||||
self.canvas.axes.add_feature(cf.RIVERS, linewidth=1)
|
||||
|
||||
# parallels and meridians
|
||||
self.add_merid_paral()
|
||||
|
||||
self.canvas.fig.tight_layout()
|
||||
|
||||
def add_merid_paral(self):
|
||||
self.gridlines = self.canvas.axes.gridlines(draw_labels=False, alpha=0.6, color='gray',
|
||||
linewidth=self.linewidth / 2, zorder=7)
|
||||
# TODO: current cartopy version does not support label removal. Devs are working on it.
|
||||
# Should be fixed in coming cartopy versions
|
||||
# self.gridlines.xformatter = LONGITUDE_FORMATTER
|
||||
# self.gridlines.yformatter = LATITUDE_FORMATTER
|
||||
|
||||
def remove_merid_paral(self):
|
||||
if len(self.gridlines.xline_artists):
|
||||
self.gridlines.xline_artists[0].remove()
|
||||
self.gridlines.yline_artists[0].remove()
|
||||
|
||||
def org_map_view(self):
|
||||
self.canvas.axes.set_xlim(self.org_xlim[0], self.org_xlim[1])
|
||||
self.canvas.axes.set_ylim(self.org_ylim[0], self.org_ylim[1])
|
||||
# parallels and meridians
|
||||
self.remove_merid_paral()
|
||||
self.add_merid_paral()
|
||||
|
||||
self.canvas.axes.figure.canvas.draw_idle()
|
||||
|
||||
|
kaan marked this conversation as resolved
sebastianw
commented
consider adding "TODO:" comment for future releases of cartopy consider adding "TODO:" comment for future releases of cartopy
|
||||
def go2eq(self):
|
||||
if self.eventLoc:
|
||||
lats, lons = self.eventLoc
|
||||
self.canvas.axes.set_xlim(lons - 10, lons + 10)
|
||||
self.canvas.axes.set_ylim(lats - 5, lats + 5)
|
||||
# parallels and meridians
|
||||
self.remove_merid_paral()
|
||||
self.add_merid_paral()
|
||||
|
||||
self.canvas.axes.figure.canvas.draw_idle()
|
||||
|
||||
else:
|
||||
self.status_label.setText('No event information available')
|
||||
|
||||
def connectSignals(self):
|
||||
self.comboBox_phase.currentIndexChanged.connect(self._refresh_drawings)
|
||||
self.comboBox_am.currentIndexChanged.connect(self._refresh_drawings)
|
||||
self.cmaps_box.currentIndexChanged.connect(self._refresh_drawings)
|
||||
self.annotations_box.stateChanged.connect(self.switch_annotations)
|
||||
self.refresh_button.clicked.connect(self._refresh_drawings)
|
||||
self.map_reset_button.clicked.connect(self.org_map_view)
|
||||
self.go2eq_button.clicked.connect(self.go2eq)
|
||||
self.save_map_button.clicked.connect(self.saveFigure)
|
||||
|
||||
self.plotWidget.mpl_connect('motion_notify_event', self.mouse_moved)
|
||||
self.plotWidget.mpl_connect('scroll_event', self.mouse_scroll)
|
||||
self.plotWidget.mpl_connect('button_press_event', self.mouseLeftPress)
|
||||
self.plotWidget.mpl_connect('button_release_event', self.mouseLeftRelease)
|
||||
|
||||
# set mouse events -----------------------------------------------------
|
||||
def mouse_moved(self, event):
|
||||
if not event.inaxes == self.canvas.axes:
|
||||
return
|
||||
lat = event.ydata
|
||||
lon = event.xdata
|
||||
self.status_label.setText('Latitude: {:3.5f}, Longitude: {:3.5f}'.format(lat, lon))
|
||||
|
||||
def mouse_scroll(self, event):
|
||||
if not event.inaxes == self.canvas.axes:
|
||||
return
|
||||
|
||||
zoom = {'up': 1. / 2., 'down': 2.}
|
||||
|
||||
if event.button in zoom:
|
||||
xlim = self.canvas.axes.get_xlim()
|
||||
ylim = self.canvas.axes.get_ylim()
|
||||
|
||||
x, y = event.xdata, event.ydata
|
||||
|
||||
factor = zoom[event.button]
|
||||
xdiff = (xlim[1] - xlim[0]) * factor
|
||||
xl = x - 0.5 * xdiff
|
||||
xr = x + 0.5 * xdiff
|
||||
ydiff = (ylim[1] - ylim[0]) * factor
|
||||
yb = y - 0.5 * ydiff
|
||||
yt = y + 0.5 * ydiff
|
||||
|
||||
self.canvas.axes.set_xlim(xl, xr)
|
||||
self.canvas.axes.set_ylim(yb, yt)
|
||||
# parallels and meridians
|
||||
self.remove_merid_paral()
|
||||
self.add_merid_paral()
|
||||
|
||||
self.canvas.axes.figure.canvas.draw_idle()
|
||||
|
||||
def mouseLeftPress(self, event):
|
||||
if not event.inaxes == self.canvas.axes:
|
||||
return
|
||||
self.map_x = event.xdata
|
||||
self.map_y = event.ydata
|
||||
self.map_xlim = self.canvas.axes.get_xlim()
|
||||
self.map_ylim = self.canvas.axes.get_ylim()
|
||||
|
||||
def mouseLeftRelease(self, event):
|
||||
if not event.inaxes == self.canvas.axes:
|
||||
return
|
||||
new_x = event.xdata
|
||||
new_y = event.ydata
|
||||
|
||||
dx = new_x - self.map_x
|
||||
dy = new_y - self.map_y
|
||||
|
||||
self.canvas.axes.set_xlim((self.map_xlim[0] - dx, self.map_xlim[1] - dx))
|
||||
self.canvas.axes.set_ylim(self.map_ylim[0] - dy, self.map_ylim[1] - dy)
|
||||
# parallels and meridians
|
||||
self.remove_merid_paral()
|
||||
self.add_merid_paral()
|
||||
|
||||
self.canvas.axes.figure.canvas.draw_idle()
|
||||
|
||||
def onpick(self, event):
|
||||
ind = event.ind
|
||||
@ -84,6 +291,14 @@ class Array_map(QtGui.QWidget):
|
||||
elif button == 3:
|
||||
self.pickInfo(ind)
|
||||
|
||||
# data handling -----------------------------------------------------
|
||||
def update_hybrids_dict(self):
|
||||
self.hybrids_dict = self.picks_dict.copy()
|
||||
for station, pick in self.autopicks_dict.items():
|
||||
if not station in self.hybrids_dict.keys():
|
||||
self.hybrids_dict[station] = pick
|
||||
return self.hybrids_dict
|
||||
|
||||
def deletePick(self, ind):
|
||||
self.update_hybrids_dict()
|
||||
for index in ind:
|
||||
@ -117,15 +332,6 @@ class Array_map(QtGui.QWidget):
|
||||
except Exception as e:
|
||||
print('Could not delete pick for station {}.{}: {}'.format(network, station, e))
|
||||
|
||||
def highlight_station(self, network, station, color):
|
||||
stat_dict = self.stations_dict['{}.{}'.format(network, station)]
|
||||
lat = stat_dict['latitude']
|
||||
lon = stat_dict['longitude']
|
||||
self.highlighted_stations.append(self.basemap.scatter(lon, lat, s=self.pointsize, edgecolors=color,
|
||||
facecolors='none', latlon=True,
|
||||
zorder=12, label='deleted'))
|
||||
self.canvas.draw()
|
||||
|
||||
def pickInfo(self, ind):
|
||||
self.update_hybrids_dict()
|
||||
for index in ind:
|
||||
@ -139,57 +345,6 @@ class Array_map(QtGui.QWidget):
|
||||
for key, info in picks.items():
|
||||
print('{}: {}'.format(key, info))
|
||||
|
||||
def openPickDlg(self, ind):
|
||||
data = self._parent.get_data().getWFData()
|
||||
for index in ind:
|
||||
network, station = self._station_onpick_ids[index].split('.')[:2]
|
||||
pyl_mw = self._parent
|
||||
try:
|
||||
data = data.select(station=station)
|
||||
if not data:
|
||||
self._warn('No data for station {}'.format(station))
|
||||
return
|
||||
pickDlg = PickDlg(self._parent, parameter=self.parameter,
|
||||
data=data, network=network, station=station,
|
||||
picks=self._parent.get_current_event().getPick(station),
|
||||
autopicks=self._parent.get_current_event().getAutopick(station),
|
||||
filteroptions=self._parent.filteroptions, metadata=self.metadata,
|
||||
event=pyl_mw.get_current_event())
|
||||
except Exception as e:
|
||||
message = 'Could not generate Plot for station {st}.\n {er}'.format(st=station, er=e)
|
||||
self._warn(message)
|
||||
print(message, e)
|
||||
print(traceback.format_exc())
|
||||
return
|
||||
try:
|
||||
if pickDlg.exec_():
|
||||
pyl_mw.setDirty(True)
|
||||
pyl_mw.update_status('picks accepted ({0})'.format(station))
|
||||
pyl_mw.addPicks(station, pickDlg.getPicks(picktype='manual'), type='manual')
|
||||
pyl_mw.addPicks(station, pickDlg.getPicks(picktype='auto'), type='auto')
|
||||
if self.auto_refresh_box.isChecked():
|
||||
self._refresh_drawings()
|
||||
else:
|
||||
self.highlight_station(network, station, color='yellow')
|
||||
pyl_mw.drawPicks(station)
|
||||
pyl_mw.draw()
|
||||
else:
|
||||
pyl_mw.update_status('picks discarded ({0})'.format(station))
|
||||
except Exception as e:
|
||||
message = 'Could not save picks for station {st}.\n{er}'.format(st=station, er=e)
|
||||
self._warn(message)
|
||||
print(message, e)
|
||||
print(traceback.format_exc())
|
||||
|
||||
def connectSignals(self):
|
||||
self.comboBox_phase.currentIndexChanged.connect(self._refresh_drawings)
|
||||
self.comboBox_am.currentIndexChanged.connect(self._refresh_drawings)
|
||||
self.cmaps_box.currentIndexChanged.connect(self._refresh_drawings)
|
||||
self.annotations_box.stateChanged.connect(self.switch_annotations)
|
||||
self.refresh_button.clicked.connect(self._refresh_drawings)
|
||||
self.canvas.mpl_connect('motion_notify_event', self.mouse_moved)
|
||||
# self.zoom_id = self.basemap.ax.figure.canvas.mpl_connect('scroll_event', self.zoom)
|
||||
|
||||
def _from_dict(self, function, key):
|
||||
return function(self.stations_dict.values(), key=lambda x: x[key])[key]
|
||||
|
||||
@ -205,14 +360,6 @@ class Array_map(QtGui.QWidget):
|
||||
def get_max_from_picks(self):
|
||||
return max(self.picks_rel.values())
|
||||
|
||||
def mouse_moved(self, event):
|
||||
if not event.inaxes == self.main_ax:
|
||||
return
|
||||
x = event.xdata
|
||||
y = event.ydata
|
||||
lat, lon = self.basemap(x, y, inverse=True)
|
||||
self.status_label.setText('Latitude: {}, Longitude: {}'.format(lat, lon))
|
||||
|
||||
def current_picks_dict(self):
|
||||
picktype = self.comboBox_am.currentText().split(' ')[0]
|
||||
auto_manu = {'auto': self.autopicks_dict,
|
||||
@ -220,57 +367,6 @@ class Array_map(QtGui.QWidget):
|
||||
'hybrid': self.hybrids_dict}
|
||||
return auto_manu[picktype]
|
||||
|
||||
def init_graphics(self):
|
||||
if not self.figure:
|
||||
self.figure = Figure()
|
||||
|
||||
self.status_label = QtGui.QLabel()
|
||||
|
||||
self.main_ax = self.figure.add_subplot(111)
|
||||
#self.main_ax.set_facecolor('0.7')
|
||||
self.canvas = PylotCanvas(self.figure, parent=self._parent, multicursor=True,
|
||||
panZoomX=False, panZoomY=False)
|
||||
|
||||
self.main_box = QtGui.QVBoxLayout()
|
||||
self.setLayout(self.main_box)
|
||||
|
||||
self.top_row = QtGui.QHBoxLayout()
|
||||
self.main_box.addLayout(self.top_row, 1)
|
||||
|
||||
self.comboBox_phase = QtGui.QComboBox()
|
||||
self.comboBox_phase.insertItem(0, 'P')
|
||||
self.comboBox_phase.insertItem(1, 'S')
|
||||
|
||||
self.comboBox_am = QtGui.QComboBox()
|
||||
self.comboBox_am.insertItem(0, 'hybrid (prefer manual)')
|
||||
self.comboBox_am.insertItem(1, 'manual')
|
||||
self.comboBox_am.insertItem(2, 'auto')
|
||||
|
||||
self.annotations_box = QtGui.QCheckBox('Annotate')
|
||||
self.annotations_box.setChecked(True)
|
||||
self.auto_refresh_box = QtGui.QCheckBox('Automatic refresh')
|
||||
self.auto_refresh_box.setChecked(True)
|
||||
self.refresh_button = QtGui.QPushButton('Refresh')
|
||||
self.cmaps_box = QtGui.QComboBox()
|
||||
self.cmaps_box.setMaxVisibleItems(20)
|
||||
[self.cmaps_box.addItem(map_name) for map_name in sorted(plt.colormaps())]
|
||||
# try to set to hsv as default
|
||||
self.cmaps_box.setCurrentIndex(self.cmaps_box.findText('hsv'))
|
||||
|
||||
self.top_row.addWidget(QtGui.QLabel('Select a phase: '))
|
||||
self.top_row.addWidget(self.comboBox_phase)
|
||||
self.top_row.setStretch(1, 1) # set stretch of item 1 to 1
|
||||
self.top_row.addWidget(QtGui.QLabel('Pick type: '))
|
||||
self.top_row.addWidget(self.comboBox_am)
|
||||
self.top_row.setStretch(3, 1) # set stretch of item 1 to 1
|
||||
self.top_row.addWidget(self.cmaps_box)
|
||||
self.top_row.addWidget(self.annotations_box)
|
||||
self.top_row.addWidget(self.auto_refresh_box)
|
||||
self.top_row.addWidget(self.refresh_button)
|
||||
|
||||
self.main_box.addWidget(self.canvas, 1)
|
||||
self.main_box.addWidget(self.status_label, 0)
|
||||
|
||||
def init_stations(self):
|
||||
self.stations_dict = self.metadata.get_all_coordinates()
|
||||
self.latmin = self.get_min_from_stations('latitude')
|
||||
@ -323,41 +419,6 @@ class Array_map(QtGui.QWidget):
|
||||
self.londim = self.lonmax - self.lonmin
|
||||
self.latdim = self.latmax - self.latmin
|
||||
|
||||
def init_x_y_dimensions(self):
|
||||
# transformation of lat/lon to ax coordinate system
|
||||
for st_id, coords in self.stations_dict.items():
|
||||
lat, lon = coords['latitude'], coords['longitude']
|
||||
coords['x'], coords['y'] = self.basemap(lon, lat)
|
||||
|
||||
self.xdim = self.get_max_from_stations('x') - self.get_min_from_stations('x')
|
||||
self.ydim = self.get_max_from_stations('y') - self.get_min_from_stations('y')
|
||||
|
||||
def init_basemap(self, resolution='l'):
|
||||
# basemap = Basemap(projection=projection, resolution = resolution, ax=self.main_ax)
|
||||
basemap = Basemap(projection='lcc', resolution=resolution, ax=self.main_ax,
|
||||
width=self.width, height=self.height,
|
||||
lat_0=(self.latmin + self.latmax) / 2.,
|
||||
lon_0=(self.lonmin + self.lonmax) / 2.)
|
||||
|
||||
# basemap.fillcontinents(color=None, lake_color='aqua',zorder=1)
|
||||
basemap.drawmapboundary(zorder=2) # fill_color='darkblue')
|
||||
basemap.shadedrelief(zorder=3)
|
||||
basemap.drawcountries(zorder=4)
|
||||
basemap.drawstates(zorder=5)
|
||||
basemap.drawcoastlines(zorder=6)
|
||||
# labels = [left,right,top,bottom]
|
||||
parallels = np.arange(-90, 90, 5.)
|
||||
parallels_small = np.arange(-90, 90, 2.5)
|
||||
basemap.drawparallels(parallels_small, linewidth=0.5, zorder=7)
|
||||
basemap.drawparallels(parallels, zorder=7)#, labels=[1, 1, 0, 0])
|
||||
meridians = np.arange(-180, 180, 5.)
|
||||
meridians_small = np.arange(-180, 180, 2.5)
|
||||
basemap.drawmeridians(meridians_small, linewidth=0.5, zorder=7)
|
||||
basemap.drawmeridians(meridians, zorder=7)#, labels=[0, 0, 1, 1])
|
||||
self.basemap = basemap
|
||||
self.figure._tight = True
|
||||
self.figure.tight_layout()
|
||||
|
||||
def init_lat_lon_grid(self, nstep=250):
|
||||
# create a regular grid to display colormap
|
||||
lataxis = np.linspace(self.latmin, self.latmax, nstep)
|
||||
@ -367,8 +428,7 @@ class Array_map(QtGui.QWidget):
|
||||
def init_picksgrid(self):
|
||||
picks, uncertainties, lats, lons = self.get_picks_lat_lon()
|
||||
try:
|
||||
self.picksgrid_active = griddata((lats, lons), picks, (self.latgrid, self.longrid),
|
||||
method='linear')
|
||||
self.picksgrid_active = griddata((lats, lons), picks, (self.latgrid, self.longrid), method='linear')
|
||||
except Exception as e:
|
||||
self._warn('Could not init picksgrid: {}'.format(e))
|
||||
|
||||
@ -382,16 +442,6 @@ class Array_map(QtGui.QWidget):
|
||||
longitudes.append(coords['longitude'])
|
||||
return stations, latitudes, longitudes
|
||||
|
||||
def get_st_x_y_for_plot(self):
|
||||
stations = []
|
||||
xs = []
|
||||
ys = []
|
||||
for st_id, coords in self.stations_dict.items():
|
||||
stations.append(st_id)
|
||||
xs.append(coords['x'])
|
||||
ys.append(coords['y'])
|
||||
return stations, xs, ys
|
||||
|
||||
def get_picks_lat_lon(self):
|
||||
picks = []
|
||||
uncertainties = []
|
||||
@ -404,65 +454,82 @@ class Array_map(QtGui.QWidget):
|
||||
longitudes.append(self.stations_dict[st_id]['longitude'])
|
||||
return picks, uncertainties, latitudes, longitudes
|
||||
|
||||
def draw_contour_filled(self, nlevel='100'):
|
||||
# self.test_gradient()
|
||||
# plotting -----------------------------------------------------
|
||||
def highlight_station(self, network, station, color):
|
||||
stat_dict = self.stations_dict['{}.{}'.format(network, station)]
|
||||
lat = stat_dict['latitude']
|
||||
lon = stat_dict['longitude']
|
||||
self.highlighted_stations.append(self.canvas.axes.scatter(lon, lat, s=self.pointsize, edgecolors=color,
|
||||
facecolors='none', zorder=12,
|
||||
transform=ccrs.PlateCarree(), label='deleted'))
|
||||
|
||||
def openPickDlg(self, ind):
|
||||
data = self._parent.get_data().getWFData()
|
||||
for index in ind:
|
||||
network, station = self._station_onpick_ids[index].split('.')[:2]
|
||||
pyl_mw = self._parent
|
||||
try:
|
||||
data = data.select(station=station)
|
||||
if not data:
|
||||
self._warn('No data for station {}'.format(station))
|
||||
return
|
||||
pickDlg = PickDlg(self._parent, parameter=self.parameter,
|
||||
data=data, network=network, station=station,
|
||||
picks=self._parent.get_current_event().getPick(station),
|
||||
autopicks=self._parent.get_current_event().getAutopick(station),
|
||||
filteroptions=self._parent.filteroptions, metadata=self.metadata,
|
||||
event=pyl_mw.get_current_event())
|
||||
except Exception as e:
|
||||
message = 'Could not generate Plot for station {st}.\n {er}'.format(st=station, er=e)
|
||||
self._warn(message)
|
||||
print(message, e)
|
||||
print(traceback.format_exc())
|
||||
return
|
||||
try:
|
||||
if pickDlg.exec_():
|
||||
pyl_mw.setDirty(True)
|
||||
pyl_mw.update_status('picks accepted ({0})'.format(station))
|
||||
pyl_mw.addPicks(station, pickDlg.getPicks(picktype='manual'), type='manual')
|
||||
pyl_mw.addPicks(station, pickDlg.getPicks(picktype='auto'), type='auto')
|
||||
if self.auto_refresh_box.isChecked():
|
||||
self._refresh_drawings()
|
||||
else:
|
||||
self.highlight_station(network, station, color='yellow')
|
||||
pyl_mw.drawPicks(station)
|
||||
pyl_mw.draw()
|
||||
else:
|
||||
pyl_mw.update_status('picks discarded ({0})'.format(station))
|
||||
except Exception as e:
|
||||
message = 'Could not save picks for station {st}.\n{er}'.format(st=station, er=e)
|
||||
self._warn(message)
|
||||
print(message, e)
|
||||
print(traceback.format_exc())
|
||||
|
||||
def draw_contour_filled(self, nlevel=50):
|
||||
levels = np.linspace(self.get_min_from_picks(), self.get_max_from_picks(), nlevel)
|
||||
self.contourf = self.basemap.contour(self.longrid, self.latgrid, self.picksgrid_active, levels,
|
||||
linewidths=self.linewidth, latlon=True, zorder=8, alpha=0.7,
|
||||
cmap=self.get_colormap())
|
||||
|
||||
self.contourf = self.canvas.axes.contourf(self.longrid, self.latgrid, self.picksgrid_active, levels,
|
||||
linewidths=self.linewidth * 5, transform=ccrs.PlateCarree(),
|
||||
alpha=0.4, zorder=8, cmap=self.get_colormap())
|
||||
|
||||
def get_colormap(self):
|
||||
return plt.get_cmap(self.cmaps_box.currentText())
|
||||
|
||||
def test_gradient(self):
|
||||
st_ids = self.picks_rel.keys()
|
||||
x, y = np.gradient(self.picksgrid_active)
|
||||
gradient_modulus = np.sqrt(x ** 2 + y ** 2)
|
||||
global_mean_gradient = np.nanmean(gradient_modulus)
|
||||
delta_gradient = []
|
||||
for st_id in st_ids:
|
||||
pick_item = self.picks_rel.pop(st_id)
|
||||
self.init_picksgrid()
|
||||
x, y = np.gradient(self.picksgrid_active)
|
||||
gradient_modulus = np.sqrt(x ** 2 + y ** 2)
|
||||
mean_gradient = np.nanmean(gradient_modulus)
|
||||
dgradient = global_mean_gradient - mean_gradient
|
||||
# print('station: {}, mean gradient: {}'.format(st_id, dgradient))
|
||||
delta_gradient.append(dgradient)
|
||||
self.picks_rel[st_id] = pick_item
|
||||
global_std_gradient = np.nanstd(delta_gradient)
|
||||
marked_stations = []
|
||||
for st_id, dg in zip(st_ids, delta_gradient):
|
||||
if abs(dg) > global_std_gradient:
|
||||
marked_stations.append(st_id)
|
||||
self.marked_stations = marked_stations
|
||||
self.init_picksgrid()
|
||||
|
||||
# fig = plt.figure()
|
||||
# x = list(range(len(st_ids)))
|
||||
# gradients = zip(x, delta_gradient)
|
||||
# gradients.sort(key=lambda a: a[1])
|
||||
# plt.plot(gradients[0], gradients[1])
|
||||
|
||||
# global_var_gradient = np.nanvar(delta_gradient)
|
||||
# plt.plot(x, delta_gradient)
|
||||
# plt.axhline(global_std_gradient, color='green')
|
||||
# plt.axhline(2 * global_std_gradient, color='blue')
|
||||
# plt.axhline(global_var_gradient, color='red')
|
||||
# plt.xticks(x, st_ids)
|
||||
# plt.show()
|
||||
|
||||
def scatter_all_stations(self):
|
||||
stations, lats, lons = self.get_st_lat_lon_for_plot()
|
||||
self.sc = self.basemap.scatter(lons, lats, s=self.pointsize, facecolor='none', latlon=True, marker='.',
|
||||
zorder=10, picker=True, edgecolor='0.5', label='Not Picked')
|
||||
self.cid = self.canvas.mpl_connect('pick_event', self.onpick)
|
||||
|
||||
self.sc = self.canvas.axes.scatter(lons, lats, s=self.pointsize * 3, facecolor='none', marker='.',
|
||||
zorder=10, picker=True, edgecolor='0.5', label='Not Picked',
|
||||
transform=ccrs.PlateCarree())
|
||||
|
||||
self.cid = self.plotWidget.mpl_connect('pick_event', self.onpick)
|
||||
self._station_onpick_ids = stations
|
||||
if self.eventLoc:
|
||||
lats, lons = self.eventLoc
|
||||
self.sc_event = self.basemap.scatter(lons, lats, s=2*self.pointsize, facecolor='red',
|
||||
latlon=True, zorder=11, label='Event (might be outside map region)')
|
||||
self.sc_event = self.canvas.axes.scatter(lons, lats, s=5 * self.pointsize, facecolor='red', zorder=11,
|
||||
label='Event (might be outside map region)', marker='*',
|
||||
edgecolors='black',
|
||||
transform=ccrs.PlateCarree())
|
||||
|
||||
def scatter_picked_stations(self):
|
||||
picks, uncertainties, lats, lons = self.get_picks_lat_lon()
|
||||
@ -471,24 +538,16 @@ class Array_map(QtGui.QWidget):
|
||||
|
||||
phase = self.comboBox_phase.currentText()
|
||||
timeerrors = self.parameter['timeerrors{}'.format(phase)]
|
||||
sizes = np.array([self.pointsize * ((5. - get_quality_class(uncertainty, timeerrors)))
|
||||
sizes = np.array([self.pointsize * (5. - get_quality_class(uncertainty, timeerrors))
|
||||
for uncertainty in uncertainties])
|
||||
|
||||
cmap = self.get_colormap()
|
||||
# workaround because of an issue with latlon transformation of arrays with len <3
|
||||
if len(lons) <= 2 and len(lats) <= 2:
|
||||
self.sc_picked = self.basemap.scatter(lons[0], lats[0], s=sizes, edgecolors='white', cmap=cmap,
|
||||
c=picks[0], latlon=True, zorder=11)
|
||||
if len(lons) == 2 and len(lats) == 2:
|
||||
self.sc_picked = self.basemap.scatter(lons[1], lats[1], s=sizes, edgecolors='white', cmap=cmap,
|
||||
c=picks[1], latlon=True, zorder=11)
|
||||
if len(lons) > 2 and len(lats) > 2:
|
||||
self.sc_picked = self.basemap.scatter(lons, lats, s=sizes, edgecolors='white', cmap=cmap,
|
||||
c=picks, latlon=True, zorder=11, label='Picked')
|
||||
self.sc_picked = self.canvas.axes.scatter(lons, lats, s=sizes, edgecolors='white', cmap=cmap,
|
||||
c=picks, zorder=11, label='Picked', transform=ccrs.PlateCarree())
|
||||
|
||||
def annotate_ax(self):
|
||||
self.annotations = []
|
||||
stations, xs, ys = self.get_st_x_y_for_plot()
|
||||
stations, ys, xs = self.get_st_lat_lon_for_plot()
|
||||
# MP MP testing station highlighting if they have high impact on mean gradient of color map
|
||||
# if self.picks_rel:
|
||||
# self.test_gradient()
|
||||
@ -501,16 +560,21 @@ class Array_map(QtGui.QWidget):
|
||||
color = 'lightgrey'
|
||||
if st in self.marked_stations:
|
||||
color = 'red'
|
||||
self.annotations.append(self.main_ax.annotate(' %s' % st, xy=(x, y),
|
||||
fontsize=self.pointsize/4., fontweight='semibold',
|
||||
color=color, zorder=14))
|
||||
self.legend = self.main_ax.legend(loc=1)
|
||||
self.legend.get_frame().set_facecolor((1, 1, 1, 0.75))
|
||||
self.annotations.append(
|
||||
self.canvas.axes.annotate(' %s' % st, xy=(x + 0.003, y + 0.003), fontsize=self.pointsize / 4.,
|
||||
fontweight='semibold', color=color, alpha=0.8,
|
||||
transform=ccrs.PlateCarree(), zorder=14,
|
||||
path_effects=[PathEffects.withStroke(
|
||||
linewidth=self.pointsize / 15., foreground='k')]))
|
||||
|
||||
self.legend = self.canvas.axes.legend(loc=1, framealpha=1)
|
||||
self.legend.set_zorder(100)
|
||||
self.legend.get_frame().set_facecolor((1, 1, 1, 0.95))
|
||||
|
||||
def add_cbar(self, label):
|
||||
self.cbax_bg = inset_axes(self.main_ax, width="6%", height="75%", loc=5)
|
||||
cbax = inset_axes(self.main_ax, width='2%', height='70%', loc=5)
|
||||
cbar = self.main_ax.figure.colorbar(self.sc_picked, cax=cbax)
|
||||
self.cbax_bg = inset_axes(self.canvas.axes, width="6%", height="75%", loc=5)
|
||||
cbax = inset_axes(self.canvas.axes, width='2%', height='70%', loc=5)
|
||||
cbar = self.canvas.axes.figure.colorbar(self.sc_picked, cax=cbax)
|
||||
cbar.set_label(label)
|
||||
cbax.yaxis.tick_left()
|
||||
cbax.yaxis.set_label_position('left')
|
||||
@ -521,6 +585,7 @@ class Array_map(QtGui.QWidget):
|
||||
self.cbax_bg.patch.set_facecolor((1, 1, 1, 0.75))
|
||||
return cbar
|
||||
|
||||
# handle drawings -----------------------------------------------------
|
||||
def refresh_drawings(self, picks=None, autopicks=None):
|
||||
self.picks_dict = picks
|
||||
self.autopicks_dict = autopicks
|
||||
@ -560,7 +625,7 @@ class Array_map(QtGui.QWidget):
|
||||
self.comboBox_phase.setEnabled(False)
|
||||
if self.annotate:
|
||||
self.annotate_ax()
|
||||
self.canvas.draw()
|
||||
self.plotWidget.draw_idle()
|
||||
|
||||
def remove_drawings(self):
|
||||
self.remove_annotations()
|
||||
@ -584,7 +649,7 @@ class Array_map(QtGui.QWidget):
|
||||
self.remove_contourf()
|
||||
del self.contourf
|
||||
if hasattr(self, 'cid'):
|
||||
self.canvas.mpl_disconnect(self.cid)
|
||||
self.plotWidget.mpl_disconnect(self.cid)
|
||||
del self.cid
|
||||
try:
|
||||
self.sc.remove()
|
||||
@ -594,7 +659,7 @@ class Array_map(QtGui.QWidget):
|
||||
self.legend.remove()
|
||||
except Exception as e:
|
||||
print('Warning: could not remove legend. Reason: {}'.format(e))
|
||||
self.canvas.draw()
|
||||
self.plotWidget.draw_idle()
|
||||
|
||||
def remove_contourf(self):
|
||||
for item in self.contourf.collections:
|
||||
@ -605,34 +670,16 @@ class Array_map(QtGui.QWidget):
|
||||
annotation.remove()
|
||||
self.annotations = []
|
||||
|
||||
def zoom(self, event):
|
||||
map = self.basemap
|
||||
xlim = map.ax.get_xlim()
|
||||
ylim = map.ax.get_ylim()
|
||||
x, y = event.xdata, event.ydata
|
||||
zoom = {'up': 1. / 2.,
|
||||
'down': 2.}
|
||||
|
||||
if not event.xdata or not event.ydata:
|
||||
def saveFigure(self):
|
||||
if self.canvas.fig:
|
||||
fd = QtWidgets.QFileDialog()
|
||||
fname, filter = fd.getSaveFileName(self.parent(), filter='Images (*.png *.svg *.jpg)')
|
||||
if not fname:
|
||||
return
|
||||
|
||||
if event.button in zoom:
|
||||
factor = zoom[event.button]
|
||||
xdiff = (xlim[1] - xlim[0]) * factor
|
||||
xl = x - 0.5 * xdiff
|
||||
xr = x + 0.5 * xdiff
|
||||
ydiff = (ylim[1] - ylim[0]) * factor
|
||||
yb = y - 0.5 * ydiff
|
||||
yt = y + 0.5 * ydiff
|
||||
|
||||
if xl < map.xmin or yb < map.ymin or xr > map.xmax or yt > map.ymax:
|
||||
xl, xr = map.xmin, map.xmax
|
||||
yb, yt = map.ymin, map.ymax
|
||||
map.ax.set_xlim(xl, xr)
|
||||
map.ax.set_ylim(yb, yt)
|
||||
map.ax.figure.canvas.draw()
|
||||
if not any([fname.endswith(item) for item in ['.png', '.svg', '.jpg']]):
|
||||
fname += '.png'
|
||||
self.canvas.fig.savefig(fname)
|
||||
|
||||
def _warn(self, message):
|
||||
self.qmb = QtGui.QMessageBox(QtGui.QMessageBox.Icon.Warning,
|
||||
'Warning', message)
|
||||
self.qmb = QtWidgets.QMessageBox(QtWidgets.QMessageBox.Icon.Warning, 'Warning', message)
|
||||
self.qmb.show()
|
||||
|
||||
@ -2,12 +2,13 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
try:
|
||||
# noinspection PyUnresolvedReferences
|
||||
from urllib2 import urlopen
|
||||
except:
|
||||
from urllib.request import urlopen
|
||||
|
||||
|
||||
def checkurl(url='https://ariadne.geophysik.ruhr-uni-bochum.de/trac/PyLoT/'):
|
||||
def checkurl(url='https://git.geophysik.ruhr-uni-bochum.de/marcel/pylot/'):
|
||||
"""
|
||||
check if URL is available
|
||||
:param url: url
|
||||
|
||||
@ -2,9 +2,10 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
import glob
|
||||
import numpy as np
|
||||
import os
|
||||
import sys
|
||||
|
||||
import numpy as np
|
||||
from obspy import UTCDateTime, read_inventory, read
|
||||
from obspy.io.xseed import Parser
|
||||
|
||||
@ -46,7 +47,7 @@ class Metadata(object):
|
||||
def __repr__(self):
|
||||
return self.__str__()
|
||||
|
||||
def add_inventory(self, path_to_inventory, obspy_dmt_inv = False):
|
||||
def add_inventory(self, path_to_inventory, obspy_dmt_inv=False):
|
||||
"""
|
||||
Add path to list of inventories.
|
||||
:param path_to_inventory: Path to a folder
|
||||
@ -83,10 +84,10 @@ class Metadata(object):
|
||||
print('Path {} not in inventories list.'.format(path_to_inventory))
|
||||
return
|
||||
self.inventories.remove(path_to_inventory)
|
||||
for filename in self.inventory_files.keys():
|
||||
for filename in list(self.inventory_files.keys()):
|
||||
if filename.startswith(path_to_inventory):
|
||||
del (self.inventory_files[filename])
|
||||
for seed_id in self.seed_ids.keys():
|
||||
for seed_id in list(self.seed_ids.keys()):
|
||||
if self.seed_ids[seed_id].startswith(path_to_inventory):
|
||||
del (self.seed_ids[seed_id])
|
||||
# have to clean self.stations_dict as well
|
||||
@ -211,6 +212,7 @@ class Metadata(object):
|
||||
self.stations_dict[st_id] = {'latitude': station[0].latitude,
|
||||
'longitude': station[0].longitude,
|
||||
'elevation': station[0].elevation}
|
||||
|
||||
read_stat = {'xml': stat_info_from_inventory,
|
||||
'dless': stat_info_from_parser}
|
||||
|
||||
@ -351,25 +353,25 @@ def check_time(datetime):
|
||||
:type datetime: list
|
||||
:return: returns True if Values are in supposed range, returns False otherwise
|
||||
|
||||
>>> check_time([1999, 01, 01, 23, 59, 59, 999000])
|
||||
>>> check_time([1999, 1, 1, 23, 59, 59, 999000])
|
||||
True
|
||||
>>> check_time([1999, 01, 01, 23, 59, 60, 999000])
|
||||
>>> check_time([1999, 1, 1, 23, 59, 60, 999000])
|
||||
False
|
||||
>>> check_time([1999, 01, 01, 23, 59, 59, 1000000])
|
||||
>>> check_time([1999, 1, 1, 23, 59, 59, 1000000])
|
||||
False
|
||||
>>> check_time([1999, 01, 01, 23, 60, 59, 999000])
|
||||
>>> check_time([1999, 1, 1, 23, 60, 59, 999000])
|
||||
False
|
||||
>>> check_time([1999, 01, 01, 23, 60, 59, 999000])
|
||||
>>> check_time([1999, 1, 1, 23, 60, 59, 999000])
|
||||
False
|
||||
>>> check_time([1999, 01, 01, 24, 59, 59, 999000])
|
||||
>>> check_time([1999, 1, 1, 24, 59, 59, 999000])
|
||||
False
|
||||
>>> check_time([1999, 01, 31, 23, 59, 59, 999000])
|
||||
>>> check_time([1999, 1, 31, 23, 59, 59, 999000])
|
||||
True
|
||||
>>> check_time([1999, 02, 30, 23, 59, 59, 999000])
|
||||
>>> check_time([1999, 2, 30, 23, 59, 59, 999000])
|
||||
False
|
||||
>>> check_time([1999, 02, 29, 23, 59, 59, 999000])
|
||||
>>> check_time([1999, 2, 29, 23, 59, 59, 999000])
|
||||
False
|
||||
>>> check_time([2000, 02, 29, 23, 59, 59, 999000])
|
||||
>>> check_time([2000, 2, 29, 23, 59, 59, 999000])
|
||||
True
|
||||
>>> check_time([2000, 13, 29, 23, 59, 59, 999000])
|
||||
False
|
||||
@ -381,6 +383,7 @@ def check_time(datetime):
|
||||
return False
|
||||
|
||||
|
||||
# TODO: change root to datapath
|
||||
def get_file_list(root_dir):
|
||||
"""
|
||||
Function uses a directorie to get all the *.gse files from it.
|
||||
@ -444,7 +447,7 @@ def evt_head_check(root_dir, out_dir=None):
|
||||
"""
|
||||
if not out_dir:
|
||||
print('WARNING files are going to be overwritten!')
|
||||
inp = str(raw_input('Continue? [y/N]'))
|
||||
inp = str(input('Continue? [y/N]'))
|
||||
if not inp == 'y':
|
||||
sys.exit()
|
||||
filelist = get_file_list(root_dir)
|
||||
|
||||
@ -2,6 +2,7 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
import os
|
||||
|
||||
from obspy import UTCDateTime
|
||||
from obspy.core.event import Event as ObsPyEvent
|
||||
from obspy.core.event import Origin, ResourceIdentifier
|
||||
@ -21,12 +22,13 @@ class Event(ObsPyEvent):
|
||||
:param path: path to event directory
|
||||
:type path: str
|
||||
"""
|
||||
# TODO: remove rootpath and database
|
||||
self.pylot_id = path.split('/')[-1]
|
||||
# initialize super class
|
||||
super(Event, self).__init__(resource_id=ResourceIdentifier('smi:local/' + self.pylot_id))
|
||||
self.path = path
|
||||
self.database = path.split('/')[-2]
|
||||
self.datapath = path.split('/')[-3]
|
||||
self.datapath = os.path.split(path)[0] # path.split('/')[-3]
|
||||
self.rootpath = '/' + os.path.join(*path.split('/')[:-3])
|
||||
self.pylot_autopicks = {}
|
||||
self.pylot_picks = {}
|
||||
@ -73,7 +75,7 @@ class Event(ObsPyEvent):
|
||||
text = lines[0]
|
||||
self.addNotes(text)
|
||||
try:
|
||||
datetime = UTCDateTime(path.split('/')[-1])
|
||||
datetime = UTCDateTime(self.path.split('/')[-1])
|
||||
origin = Origin(resource_id=self.resource_id, time=datetime, latitude=0, longitude=0, depth=0)
|
||||
self.origins.append(origin)
|
||||
except:
|
||||
@ -296,13 +298,13 @@ class Event(ObsPyEvent):
|
||||
:rtype: None
|
||||
"""
|
||||
try:
|
||||
import cPickle
|
||||
import pickle
|
||||
except ImportError:
|
||||
import _pickle as cPickle
|
||||
import _pickle as pickle
|
||||
|
||||
try:
|
||||
outfile = open(filename, 'wb')
|
||||
cPickle.dump(self, outfile, -1)
|
||||
pickle.dump(self, outfile, -1)
|
||||
self.dirty = False
|
||||
except Exception as e:
|
||||
print('Could not pickle PyLoT event. Reason: {}'.format(e))
|
||||
@ -317,11 +319,11 @@ class Event(ObsPyEvent):
|
||||
:rtype: Event
|
||||
"""
|
||||
try:
|
||||
import cPickle
|
||||
import pickle
|
||||
except ImportError:
|
||||
import _pickle as cPickle
|
||||
import _pickle as pickle
|
||||
infile = open(filename, 'rb')
|
||||
event = cPickle.load(infile)
|
||||
event = pickle.load(infile)
|
||||
event.dirty = False
|
||||
print('Loaded %s' % filename)
|
||||
return event
|
||||
|
||||
@ -3,24 +3,37 @@
|
||||
# small script that creates array maps for each event within a previously generated PyLoT project
|
||||
|
||||
import os
|
||||
|
||||
num_thread = "16"
|
||||
os.environ["OMP_NUM_THREADS"] = num_thread
|
||||
os.environ["OPENBLAS_NUM_THREADS"] = num_thread
|
||||
os.environ["MKL_NUM_THREADS"] = num_thread
|
||||
os.environ["VECLIB_MAXIMUM_THREADS"] = num_thread
|
||||
os.environ["NUMEXPR_NUM_THREADS"] = num_thread
|
||||
os.environ["NUMEXPR_MAX_THREADS"] = num_thread
|
||||
|
||||
import multiprocessing
|
||||
import sys
|
||||
import glob
|
||||
import matplotlib
|
||||
|
||||
matplotlib.use('Qt5Agg')
|
||||
sys.path.append(os.path.join('/'.join(sys.argv[0].split('/')[:-1]), '../../..'))
|
||||
|
||||
from PyLoT import Project
|
||||
from pylot.core.util.dataprocessing import Metadata
|
||||
from pylot.core.util.array_map import Array_map
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
import argparse
|
||||
|
||||
|
||||
def main(project_file_path, manual=False, auto=True, file_format='png', f_ext='', ncores=None):
|
||||
project = Project.load(project_file_path)
|
||||
nEvents = len(project.eventlist)
|
||||
input_list = []
|
||||
|
||||
print('\n')
|
||||
for index, event in enumerate(project.eventlist):
|
||||
# MP MP TESTING +++
|
||||
#if not eventdir.endswith('20170908_044946.a'):
|
||||
# continue
|
||||
# MP MP ----
|
||||
kwargs = dict(project=project, event=event, nEvents=nEvents, index=index, manual=manual, auto=auto,
|
||||
file_format=file_format, f_ext=f_ext)
|
||||
input_list.append(kwargs)
|
||||
@ -30,14 +43,20 @@ def main(project_file_path, manual=False, auto=True, file_format='png', f_ext=''
|
||||
array_map_worker(item)
|
||||
else:
|
||||
pool = multiprocessing.Pool(ncores)
|
||||
result = pool.map(array_map_worker, input_list)
|
||||
pool.map(array_map_worker, input_list)
|
||||
pool.close()
|
||||
pool.join()
|
||||
|
||||
|
||||
def array_map_worker(input_dict):
|
||||
event = input_dict['event']
|
||||
eventdir = event.path
|
||||
print('Working on event: {} ({}/{})'.format(eventdir, input_dict['index'] + 1, input_dict['nEvents']))
|
||||
xml_picks = glob.glob(os.path.join(eventdir, f'*{input_dict["f_ext"]}.xml'))
|
||||
if not len(xml_picks):
|
||||
print('Event {} does not have any picks associated with event file extension {}'.format(eventdir,
|
||||
input_dict['f_ext']))
|
||||
return
|
||||
# check for picks
|
||||
manualpicks = event.getPicks()
|
||||
autopicks = event.getAutopicks()
|
||||
@ -51,11 +70,12 @@ def array_map_worker(input_dict):
|
||||
continue
|
||||
if not metadata:
|
||||
metadata = Metadata(inventory=metadata_path, verbosity=0)
|
||||
|
||||
# create figure to plot on
|
||||
fig = plt.figure(figsize=(16,9))
|
||||
fig, ax = plt.subplots(figsize=(15, 9))
|
||||
# create array map object
|
||||
map = Array_map(None, metadata, parameter=input_dict['project'].parameter, figure=fig,
|
||||
width=2.13e6, height=1.2e6, pointsize=15., linewidth=1.0)
|
||||
map = Array_map(None, metadata, parameter=input_dict['project'].parameter, axes=ax,
|
||||
width=2.13e6, height=1.2e6, pointsize=25., linewidth=1.0)
|
||||
# set combobox to auto/manual to plot correct pick type
|
||||
map.comboBox_am.setCurrentIndex(map.comboBox_am.findText(pick_type))
|
||||
# add picks to map and save file
|
||||
@ -65,11 +85,13 @@ def array_map_worker(input_dict):
|
||||
fig.savefig(fpath_out, dpi=300.)
|
||||
print('Wrote file: {}'.format(fpath_out))
|
||||
|
||||
if __name__ == '__main__':
|
||||
dataroot = '/home/marcel'
|
||||
infiles=['alparray_all_events_0.03-0.1_mantle_correlated_v3.plp']
|
||||
|
||||
for infile in infiles:
|
||||
main(os.path.join(dataroot, infile), f_ext='_correlated_0.1Hz', ncores=10)
|
||||
#main('E:\Shared\AlpArray\\test_aa.plp', f_ext='_correlated_0.5Hz', ncores=1)
|
||||
#main('/home/marcel/alparray_m6.5-6.9_mantle_correlated_v3.plp', f_ext='_correlated_0.5Hz')
|
||||
if __name__ == '__main__':
|
||||
cl = argparse.ArgumentParser()
|
||||
cl.add_argument('--dataroot', help='Directory containing the PyLoT .plp file', type=str)
|
||||
cl.add_argument('--infiles', help='.plp files to use', nargs='+')
|
||||
cl.add_argument('--ncores', hepl='Specify number of parallel processes', type=int, default=1)
|
||||
args = cl.parse_args()
|
||||
|
||||
for infile in args.infiles:
|
||||
main(os.path.join(args.dataroot, infile), f_ext='_correlated_0.03-0.1', ncores=args.ncores)
|
||||
|
||||
@ -7,11 +7,10 @@ try:
|
||||
except Exception as e:
|
||||
print('Warning: Could not import module pyqtgraph.')
|
||||
try:
|
||||
from PySide import QtCore
|
||||
from PySide2 import QtCore
|
||||
except Exception as e:
|
||||
print('Warning: Could not import module QtCore.')
|
||||
|
||||
|
||||
from pylot.core.util.utils import pick_color
|
||||
|
||||
|
||||
@ -49,7 +48,7 @@ def which(program, parameter):
|
||||
:rtype: str
|
||||
"""
|
||||
try:
|
||||
from PySide.QtCore import QSettings
|
||||
from PySide2.QtCore import QSettings
|
||||
settings = QSettings()
|
||||
for key in settings.allKeys():
|
||||
if 'binPath' in key:
|
||||
@ -101,4 +100,3 @@ def make_pen(picktype, phase, key, quality):
|
||||
linestyle, width = pick_linestyle_pg(picktype, key)
|
||||
pen = pg.mkPen(rgba, width=width, style=linestyle)
|
||||
return pen
|
||||
|
||||
|
||||
@ -2,6 +2,7 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
import os
|
||||
|
||||
from obspy import UTCDateTime
|
||||
|
||||
|
||||
@ -34,17 +35,25 @@ def qml_from_obspyDMT(path):
|
||||
|
||||
if not os.path.exists(path):
|
||||
return IOError('Could not find Event at {}'.format(path))
|
||||
infile = open(path, 'rb')
|
||||
event_dmt = pickle.load(infile)#, fix_imports=True)
|
||||
|
||||
with open(path, 'rb') as infile:
|
||||
event_dmt = pickle.load(infile) # , fix_imports=True)
|
||||
|
||||
event_dmt['origin_id'].id = str(event_dmt['origin_id'].id)
|
||||
|
||||
ev = Event(resource_id=event_dmt['event_id'])
|
||||
#small bugfix "unhashable type: 'newstr' "
|
||||
# small bugfix "unhashable type: 'newstr' "
|
||||
event_dmt['origin_id'].id = str(event_dmt['origin_id'].id)
|
||||
origin = Origin(resource_id=event_dmt['origin_id'], time=event_dmt['datetime'], longitude=event_dmt['longitude'],
|
||||
latitude=event_dmt['latitude'], depth=event_dmt['depth'])
|
||||
mag = Magnitude(mag=event_dmt['magnitude'], magnitude_type=event_dmt['magnitude_type'],
|
||||
|
||||
origin = Origin(resource_id=event_dmt['origin_id'],
|
||||
time=event_dmt['datetime'],
|
||||
longitude=event_dmt['longitude'],
|
||||
latitude=event_dmt['latitude'],
|
||||
depth=event_dmt['depth'])
|
||||
mag = Magnitude(mag=event_dmt['magnitude'],
|
||||
magnitude_type=event_dmt['magnitude_type'],
|
||||
origin_id=event_dmt['origin_id'])
|
||||
|
||||
ev.magnitudes.append(mag)
|
||||
ev.origins.append(origin)
|
||||
return ev
|
||||
|
||||
@ -1,8 +1,9 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
import numpy as np
|
||||
import warnings
|
||||
|
||||
import numpy as np
|
||||
from obspy import UTCDateTime
|
||||
|
||||
from pylot.core.util.utils import fit_curve, clims
|
||||
|
||||
@ -4,8 +4,8 @@ import os
|
||||
import sys
|
||||
import traceback
|
||||
|
||||
from PySide.QtCore import QThread, Signal, Qt, Slot, QRunnable, QObject
|
||||
from PySide.QtGui import QDialog, QProgressBar, QLabel, QHBoxLayout
|
||||
from PySide2.QtCore import QThread, Signal, Qt, Slot, QRunnable, QObject
|
||||
from PySide2.QtWidgets import QDialog, QProgressBar, QLabel, QHBoxLayout, QPushButton
|
||||
|
||||
|
||||
class Thread(QThread):
|
||||
@ -22,9 +22,11 @@ class Thread(QThread):
|
||||
self.abortButton = abortButton
|
||||
self.finished.connect(self.hideProgressbar)
|
||||
self.showProgressbar()
|
||||
self.old_stdout = None
|
||||
|
||||
def run(self):
|
||||
if self.redirect_stdout:
|
||||
self.old_stdout = sys.stdout
|
||||
sys.stdout = self
|
||||
try:
|
||||
if self.arg is not None:
|
||||
@ -39,7 +41,7 @@ class Thread(QThread):
|
||||
exctype, value = sys.exc_info()[:2]
|
||||
self._executedErrorInfo = '{} {} {}'. \
|
||||
format(exctype, value, traceback.format_exc())
|
||||
sys.stdout = sys.__stdout__
|
||||
sys.stdout = self.old_stdout
|
||||
|
||||
def showProgressbar(self):
|
||||
if self.progressText:
|
||||
@ -49,7 +51,23 @@ class Thread(QThread):
|
||||
# self.pb_widget.setWindowFlags(Qt.SplashScreen)
|
||||
# self.pb_widget.setModal(True)
|
||||
|
||||
self.pb_widget.label.setText(self.progressText)
|
||||
# generate widget if not given in init
|
||||
if not self.pb_widget:
|
||||
self.pb_widget = QDialog(self.parent())
|
||||
self.pb_widget.setWindowFlags(Qt.SplashScreen)
|
||||
self.pb_widget.setModal(True)
|
||||
|
||||
# add button
|
||||
delete_button = QPushButton('X')
|
||||
delete_button.clicked.connect(self.exit)
|
||||
hl = QHBoxLayout()
|
||||
pb = QProgressBar()
|
||||
pb.setRange(0, 0)
|
||||
hl.addWidget(pb)
|
||||
hl.addWidget(QLabel(self.progressText))
|
||||
if self.abortButton:
|
||||
hl.addWidget(delete_button)
|
||||
self.pb_widget.setLayout(hl)
|
||||
self.pb_widget.show()
|
||||
|
||||
def hideProgressbar(self):
|
||||
@ -80,10 +98,12 @@ class Worker(QRunnable):
|
||||
self.progressText = progressText
|
||||
self.pb_widget = pb_widget
|
||||
self.redirect_stdout = redirect_stdout
|
||||
self.old_stdout = None
|
||||
|
||||
@Slot()
|
||||
def run(self):
|
||||
if self.redirect_stdout:
|
||||
self.old_stdout = sys.stdout
|
||||
sys.stdout = self
|
||||
|
||||
try:
|
||||
@ -96,7 +116,7 @@ class Worker(QRunnable):
|
||||
self.signals.result.emit(result)
|
||||
finally:
|
||||
self.signals.finished.emit('Done')
|
||||
sys.stdout = sys.__stdout__
|
||||
sys.stdout = self.old_stdout
|
||||
|
||||
def write(self, text):
|
||||
self.signals.message.emit(text)
|
||||
@ -128,11 +148,13 @@ class MultiThread(QThread):
|
||||
self.progressText = progressText
|
||||
self.pb_widget = pb_widget
|
||||
self.redirect_stdout = redirect_stdout
|
||||
self.old_stdout = None
|
||||
self.finished.connect(self.hideProgressbar)
|
||||
self.showProgressbar()
|
||||
|
||||
def run(self):
|
||||
if self.redirect_stdout:
|
||||
self.old_stdout = sys.stdout
|
||||
sys.stdout = self
|
||||
try:
|
||||
if not self.ncores:
|
||||
@ -148,7 +170,7 @@ class MultiThread(QThread):
|
||||
exc_type, exc_obj, exc_tb = sys.exc_info()
|
||||
fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1]
|
||||
print('Exception: {}, file: {}, line: {}'.format(exc_type, fname, exc_tb.tb_lineno))
|
||||
sys.stdout = sys.__stdout__
|
||||
sys.stdout = self.old_stdout
|
||||
|
||||
def showProgressbar(self):
|
||||
if self.progressText:
|
||||
|
||||
@ -2,12 +2,13 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
import hashlib
|
||||
import numpy as np
|
||||
import os
|
||||
import platform
|
||||
import re
|
||||
import subprocess
|
||||
import warnings
|
||||
|
||||
import numpy as np
|
||||
from obspy import UTCDateTime, read
|
||||
from obspy.core import AttribDict
|
||||
from obspy.signal.rotate import rotate2zne
|
||||
@ -227,7 +228,7 @@ def findComboBoxIndex(combo_box, val):
|
||||
:type val: basestring
|
||||
:return: index value of item with name val or 0
|
||||
"""
|
||||
return combo_box.findText(val) if combo_box.findText(val) is not -1 else 0
|
||||
return combo_box.findText(val) if combo_box.findText(val) != -1 else 0
|
||||
|
||||
|
||||
def find_in_list(list, str):
|
||||
@ -950,10 +951,13 @@ def check4rotated(data, metadata=None, verbosity=1):
|
||||
if any(rotation_required):
|
||||
t_start = full_range(wfstream)
|
||||
try:
|
||||
azimuts = [metadata.get_coordinates(tr_id, t_start)['azimuth'] for tr_id in trace_ids]
|
||||
dips = [metadata.get_coordinates(tr_id, t_start)['dip'] for tr_id in trace_ids]
|
||||
azimuts = []
|
||||
dips = []
|
||||
for tr_id in trace_ids:
|
||||
azimuts.append(metadata.get_coordinates(tr_id, t_start)['azimuth'])
|
||||
dips.append(metadata.get_coordinates(tr_id, t_start)['dip'])
|
||||
except (KeyError, TypeError) as e:
|
||||
print('Failed to rotate trace {}, no azimuth or dip available in metadata'.format(trace_id))
|
||||
print('Failed to rotate trace {}, no azimuth or dip available in metadata'.format(tr_id))
|
||||
return wfstream
|
||||
if len(wfstream) < 3:
|
||||
print('Failed to rotate Stream {}, not enough components available.'.format(wfstream))
|
||||
@ -964,7 +968,7 @@ def check4rotated(data, metadata=None, verbosity=1):
|
||||
z, n, e = rotate2zne(wfstream[0], azimuts[0], dips[0],
|
||||
wfstream[1], azimuts[1], dips[1],
|
||||
wfstream[2], azimuts[2], dips[2])
|
||||
print('check4rotated: rotated trace {} to ZNE'.format(trace_id))
|
||||
print('check4rotated: rotated trace {} to ZNE'.format(trace_ids))
|
||||
# replace old data with rotated data, change the channel code to ZNE
|
||||
z_index = dips.index(min(
|
||||
dips)) # get z-trace index, z has minimum dip of -90 (dip is measured from 0 to -90, with -90 being vertical)
|
||||
@ -1013,7 +1017,7 @@ def scaleWFData(data, factor=None, components='all'):
|
||||
:return: scaled waveform data
|
||||
:rtype: `~obspy.core.stream.Stream` object
|
||||
"""
|
||||
if components is not 'all':
|
||||
if components != 'all':
|
||||
for comp in components:
|
||||
if factor is None:
|
||||
max_val = np.max(np.abs(data.select(component=comp)[0].data))
|
||||
|
||||
@ -35,9 +35,9 @@ from __future__ import print_function
|
||||
|
||||
__all__ = "get_git_version"
|
||||
|
||||
import inspect
|
||||
# NO IMPORTS FROM PYLOT IN THIS FILE! (file gets used at installation time)
|
||||
import os
|
||||
import inspect
|
||||
from subprocess import Popen, PIPE
|
||||
|
||||
# NO IMPORTS FROM PYLOT IN THIS FILE! (file gets used at installation time)
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
12
requirements.txt
Normal file
12
requirements.txt
Normal file
@ -0,0 +1,12 @@
|
||||
# This file may be used to create an environment using:
|
||||
# $ conda create --name <env> --file <this file>
|
||||
# platform: win-64
|
||||
cartopy=0.20.2
|
||||
matplotlib-base=3.3.4
|
||||
numpy=1.22.3
|
||||
obspy=1.3.0
|
||||
pyqtgraph=0.12.4
|
||||
pyside2=5.13.2
|
||||
python=3.8.12
|
||||
qt=5.12.9
|
||||
scipy=1.8.0
|
||||
17
setup.py
17
setup.py
@ -1,17 +0,0 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
from distutils.core import setup
|
||||
|
||||
setup(
|
||||
name='PyLoT',
|
||||
version='0.2',
|
||||
packages=['pylot', 'pylot.core', 'pylot.core.loc', 'pylot.core.pick',
|
||||
'pylot.core.io', 'pylot.core.util', 'pylot.core.active',
|
||||
'pylot.core.analysis', 'pylot.testing'],
|
||||
requires=['obspy', 'PySide', 'matplotlib', 'numpy', 'scipy', 'pyqtgraph'],
|
||||
url='dummy',
|
||||
license='LGPLv3',
|
||||
author='Sebastian Wehling-Benatelli',
|
||||
author_email='sebastian.wehling@rub.de',
|
||||
description='Comprehensive Python picking and Location Toolbox for seismological data.'
|
||||
)
|
||||
1735
tests/PyLoT_e0019.048.13.xml
Normal file
1735
tests/PyLoT_e0019.048.13.xml
Normal file
File diff suppressed because it is too large
Load Diff
@ -1,6 +1,8 @@
|
||||
import unittest
|
||||
|
||||
from pylot.core.pick.autopick import PickingResults
|
||||
|
||||
|
||||
class TestPickingResults(unittest.TestCase):
|
||||
|
||||
def setUp(self):
|
||||
@ -70,9 +72,9 @@ class TestPickingResults(unittest.TestCase):
|
||||
curr_len = len(self.pr)
|
||||
except Exception:
|
||||
self.fail("test_dunder_attributes overwrote an instance internal dunder method")
|
||||
self.assertEqual(prev_len+1, curr_len) # +1 for the added __len__ key/value-pair
|
||||
self.assertEqual(prev_len + 1, curr_len) # +1 for the added __len__ key/value-pair
|
||||
|
||||
self.pr.__len__ = 42
|
||||
|
||||
self.assertEqual(42, self.pr['__len__'])
|
||||
self.assertEqual(prev_len+1, curr_len, msg="__len__ was overwritten")
|
||||
self.assertEqual(prev_len + 1, curr_len, msg="__len__ was overwritten")
|
||||
|
||||
@ -1,5 +1,6 @@
|
||||
import os
|
||||
import unittest
|
||||
|
||||
from obspy import UTCDateTime
|
||||
from obspy.io.xseed import Parser
|
||||
from obspy.io.xseed.utils import SEEDParserException
|
||||
@ -27,7 +28,7 @@ class TestMetadata(unittest.TestCase):
|
||||
result = {}
|
||||
for channel in ('Z', 'N', 'E'):
|
||||
with HidePrints():
|
||||
coords = self.m.get_coordinates(self.station_id+channel, time=self.time)
|
||||
coords = self.m.get_coordinates(self.station_id + channel, time=self.time)
|
||||
result[channel] = coords
|
||||
self.assertDictEqual(result[channel], expected[channel])
|
||||
|
||||
@ -42,7 +43,7 @@ class TestMetadata(unittest.TestCase):
|
||||
result = {}
|
||||
for channel in ('Z', 'N', 'E'):
|
||||
with HidePrints():
|
||||
coords = self.m.get_coordinates(self.station_id+channel)
|
||||
coords = self.m.get_coordinates(self.station_id + channel)
|
||||
result[channel] = coords
|
||||
self.assertDictEqual(result[channel], expected[channel])
|
||||
|
||||
@ -145,7 +146,7 @@ class TestMetadata_read_single_file(unittest.TestCase):
|
||||
|
||||
def test_read_single_file(self):
|
||||
"""Test if reading a single file works"""
|
||||
fname = os.path.join(self.metadata_folders[0], 'DATALESS.'+self.station_id)
|
||||
fname = os.path.join(self.metadata_folders[0], 'DATALESS.' + self.station_id)
|
||||
with HidePrints():
|
||||
res = self.m.read_single_file(fname)
|
||||
# method should return true if file is successfully read
|
||||
@ -172,7 +173,7 @@ class TestMetadata_read_single_file(unittest.TestCase):
|
||||
|
||||
def test_read_single_file_multiple_times(self):
|
||||
"""Test if reading a file twice doesnt add it twice to the metadata object"""
|
||||
fname = os.path.join(self.metadata_folders[0], 'DATALESS.'+self.station_id)
|
||||
fname = os.path.join(self.metadata_folders[0], 'DATALESS.' + self.station_id)
|
||||
with HidePrints():
|
||||
res1 = self.m.read_single_file(fname)
|
||||
res2 = self.m.read_single_file(fname)
|
||||
@ -197,7 +198,8 @@ class TestMetadataMultipleTime(unittest.TestCase):
|
||||
def setUp(self):
|
||||
self.seed_id = 'LE.ROTT..HN'
|
||||
path = os.path.dirname(__file__) # gets path to currently running script
|
||||
metadata = os.path.join('test_data', 'dless_multiple_times', 'MAGS2_LE_ROTT.dless') # specific subfolder of test data
|
||||
metadata = os.path.join('test_data', 'dless_multiple_times',
|
||||
'MAGS2_LE_ROTT.dless') # specific subfolder of test data
|
||||
metadata_path = os.path.join(path, metadata)
|
||||
self.m = Metadata(metadata_path)
|
||||
self.p = Parser(metadata_path)
|
||||
@ -299,7 +301,8 @@ Channels:
|
||||
def setUp(self):
|
||||
self.seed_id = 'KB.TMO07.00.HHZ'
|
||||
path = os.path.dirname(__file__) # gets path to currently running script
|
||||
metadata = os.path.join('test_data', 'dless_multiple_instruments', 'MAGS2_KB_TMO07.dless') # specific subfolder of test data
|
||||
metadata = os.path.join('test_data', 'dless_multiple_instruments',
|
||||
'MAGS2_KB_TMO07.dless') # specific subfolder of test data
|
||||
metadata_path = os.path.join(path, metadata)
|
||||
self.m = Metadata(metadata_path)
|
||||
self.p = Parser(metadata_path)
|
||||
|
||||
@ -1,35 +0,0 @@
|
||||
import unittest
|
||||
from pylot.core.pick.autopick import PickingParameters
|
||||
|
||||
class TestPickingParameters(unittest.TestCase):
|
||||
|
||||
def setUp(self):
|
||||
self.simple_dict = {'a': 3, 'b': 14}
|
||||
self.nested_dict = {'a': self.simple_dict, 'b': self.simple_dict}
|
||||
|
||||
def assertParameterEquality(self, dic, instance):
|
||||
"""Test wether all parameters given in dic are found in instance"""
|
||||
for key, value in dic.items():
|
||||
self.assertEqual(value, getattr(instance, key))
|
||||
|
||||
def test_add_params_from_dict_simple(self):
|
||||
pickparam = PickingParameters()
|
||||
pickparam.add_params_from_dict(self.simple_dict)
|
||||
self.assertParameterEquality(self.simple_dict, pickparam)
|
||||
|
||||
def test_add_params_from_dict_nested(self):
|
||||
pickparam = PickingParameters()
|
||||
pickparam.add_params_from_dict(self.nested_dict)
|
||||
self.assertParameterEquality(self.nested_dict, pickparam)
|
||||
|
||||
def test_init(self):
|
||||
pickparam = PickingParameters(self.simple_dict)
|
||||
self.assertParameterEquality(self.simple_dict, pickparam)
|
||||
|
||||
def test_dot_access(self):
|
||||
pickparam = PickingParameters(self.simple_dict)
|
||||
self.assertEqual(pickparam.a, self.simple_dict['a'])
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
@ -1,12 +1,13 @@
|
||||
import unittest
|
||||
from unittest import skip
|
||||
import obspy
|
||||
from obspy import UTCDateTime
|
||||
import os
|
||||
import sys
|
||||
from pylot.core.pick.autopick import autopickstation
|
||||
from pylot.core.io.inputs import PylotParameter
|
||||
import unittest
|
||||
|
||||
import obspy
|
||||
from obspy import UTCDateTime
|
||||
|
||||
from pylot.core.io.data import Data
|
||||
from pylot.core.io.inputs import PylotParameter
|
||||
from pylot.core.pick.autopick import autopickstation
|
||||
from pylot.core.util.utils import trim_station_components
|
||||
|
||||
|
||||
@ -93,51 +94,100 @@ class TestAutopickStation(unittest.TestCase):
|
||||
self.inputfile_taupy_disabled = os.path.join(os.path.dirname(__file__), 'autoPyLoT_global_taupy_false.in')
|
||||
self.pickparam_taupy_enabled = PylotParameter(fnin=self.inputfile_taupy_enabled)
|
||||
self.pickparam_taupy_disabled = PylotParameter(fnin=self.inputfile_taupy_disabled)
|
||||
self.xml_file = os.path.join(os.path.dirname(__file__),self.event_id, 'PyLoT_'+self.event_id+'.xml')
|
||||
self.xml_file = os.path.join(os.path.dirname(__file__), self.event_id, 'PyLoT_' + self.event_id + '.xml')
|
||||
self.data = Data(evtdata=self.xml_file)
|
||||
# create origin for taupy testing
|
||||
self.origin = [obspy.core.event.origin.Origin(magnitude=7.1, latitude=59.66, longitude=-153.45, depth=128.0, time=UTCDateTime("2016-01-24T10:30:30.0"))]
|
||||
self.origin = [obspy.core.event.origin.Origin(magnitude=7.1, latitude=59.66, longitude=-153.45, depth=128.0,
|
||||
time=UTCDateTime("2016-01-24T10:30:30.0"))]
|
||||
# mocking metadata since reading it takes a long time to read from file
|
||||
self.metadata = MockMetadata()
|
||||
|
||||
# show complete diff when difference in results dictionaries are found
|
||||
self.maxDiff = None
|
||||
|
||||
#@skip("Works")
|
||||
# @skip("Works")
|
||||
def test_autopickstation_taupy_disabled_gra1(self):
|
||||
expected = {'P': {'picker': 'auto', 'snrdb': 15.405649120980094, 'weight': 0, 'Mo': None, 'marked': [], 'Mw': None, 'fc': None, 'snr': 34.718816470730317, 'mpp': UTCDateTime(2016, 1, 24, 10, 41, 31, 690000), 'w0': None, 'spe': 0.93333333333333235, 'network': u'GR', 'epp': UTCDateTime(2016, 1, 24, 10, 41, 28, 890000), 'lpp': UTCDateTime(2016, 1, 24, 10, 41, 32, 690000), 'fm': 'D', 'channel': u'LHZ'}, 'S': {'picker': 'auto', 'snrdb': 10.669661906545489, 'network': u'GR', 'weight': 0, 'Ao': None, 'lpp': UTCDateTime(2016, 1, 24, 10, 50, 30, 690000), 'snr': 11.667187857573905, 'epp': UTCDateTime(2016, 1, 24, 10, 50, 21, 690000), 'mpp': UTCDateTime(2016, 1, 24, 10, 50, 29, 690000), 'fm': None, 'spe': 2.6666666666666665, 'channel': u'LHE'}}
|
||||
expected = {
|
||||
'P': {'picker': 'auto', 'snrdb': 15.405649120980094, 'weight': 0, 'Mo': None, 'marked': [], 'Mw': None,
|
||||
'fc': None, 'snr': 34.718816470730317, 'mpp': UTCDateTime(2016, 1, 24, 10, 41, 31, 690000),
|
||||
'w0': None, 'spe': 0.93333333333333235, 'network': u'GR',
|
||||
'epp': UTCDateTime(2016, 1, 24, 10, 41, 28, 890000),
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 41, 32, 690000), 'fm': 'D', 'channel': u'LHZ'},
|
||||
'S': {'picker': 'auto', 'snrdb': 10.669661906545489, 'network': u'GR', 'weight': 0, 'Ao': None,
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 50, 30, 690000), 'snr': 11.667187857573905,
|
||||
'epp': UTCDateTime(2016, 1, 24, 10, 50, 21, 690000),
|
||||
'mpp': UTCDateTime(2016, 1, 24, 10, 50, 29, 690000), 'fm': None, 'spe': 2.6666666666666665,
|
||||
'channel': u'LHE'}}
|
||||
with HidePrints():
|
||||
result, station = autopickstation(wfstream=self.gra1, pickparam=self.pickparam_taupy_disabled, metadata=(None, None))
|
||||
result, station = autopickstation(wfstream=self.gra1, pickparam=self.pickparam_taupy_disabled,
|
||||
metadata=(None, None))
|
||||
self.assertDictContainsSubset(expected=expected['P'], actual=result['P'])
|
||||
self.assertDictContainsSubset(expected=expected['S'], actual=result['S'])
|
||||
self.assertEqual('GRA1', station)
|
||||
|
||||
def test_autopickstation_taupy_enabled_gra1(self):
|
||||
expected = {'P': {'picker': 'auto', 'snrdb': 15.599905299126778, 'weight': 0, 'Mo': None, 'marked': [], 'Mw': None, 'fc': None, 'snr': 36.307013769185403, 'mpp': UTCDateTime(2016, 1, 24, 10, 41, 27, 690000), 'w0': None, 'spe': 0.93333333333333235, 'network': u'GR', 'epp': UTCDateTime(2016, 1, 24, 10, 41, 24, 890000), 'lpp': UTCDateTime(2016, 1, 24, 10, 41, 28, 690000), 'fm': 'U', 'channel': u'LHZ'}, 'S': {'picker': 'auto', 'snrdb': 10.669661906545489, 'network': u'GR', 'weight': 0, 'Ao': None, 'lpp': UTCDateTime(2016, 1, 24, 10, 50, 30, 690000), 'snr': 11.667187857573905, 'epp': UTCDateTime(2016, 1, 24, 10, 50, 21, 690000), 'mpp': UTCDateTime(2016, 1, 24, 10, 50, 29, 690000), 'fm': None, 'spe': 2.6666666666666665, 'channel': u'LHE'}}
|
||||
expected = {
|
||||
'P': {'picker': 'auto', 'snrdb': 15.599905299126778, 'weight': 0, 'Mo': None, 'marked': [], 'Mw': None,
|
||||
'fc': None, 'snr': 36.307013769185403, 'mpp': UTCDateTime(2016, 1, 24, 10, 41, 27, 690000),
|
||||
'w0': None, 'spe': 0.93333333333333235, 'network': u'GR',
|
||||
'epp': UTCDateTime(2016, 1, 24, 10, 41, 24, 890000),
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 41, 28, 690000), 'fm': 'U', 'channel': u'LHZ'},
|
||||
'S': {'picker': 'auto', 'snrdb': 10.669661906545489, 'network': u'GR', 'weight': 0, 'Ao': None,
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 50, 30, 690000), 'snr': 11.667187857573905,
|
||||
'epp': UTCDateTime(2016, 1, 24, 10, 50, 21, 690000),
|
||||
'mpp': UTCDateTime(2016, 1, 24, 10, 50, 29, 690000), 'fm': None, 'spe': 2.6666666666666665,
|
||||
'channel': u'LHE'}}
|
||||
with HidePrints():
|
||||
result, station = autopickstation(wfstream=self.gra1, pickparam=self.pickparam_taupy_enabled, metadata=self.metadata, origin=self.origin)
|
||||
result, station = autopickstation(wfstream=self.gra1, pickparam=self.pickparam_taupy_enabled,
|
||||
metadata=self.metadata, origin=self.origin)
|
||||
self.assertDictContainsSubset(expected=expected['P'], actual=result['P'])
|
||||
self.assertDictContainsSubset(expected=expected['S'], actual=result['S'])
|
||||
self.assertEqual('GRA1', station)
|
||||
|
||||
def test_autopickstation_taupy_disabled_gra2(self):
|
||||
expected = {'P': {'picker': 'auto', 'snrdb': None, 'weight': 9, 'Mo': None, 'marked': 'shortsignallength', 'Mw': None, 'fc': None, 'snr': None, 'mpp': UTCDateTime(2016, 1, 24, 10, 36, 59, 150000), 'w0': None, 'spe': None, 'network': u'GR', 'epp': UTCDateTime(2016, 1, 24, 10, 36, 43, 150000), 'lpp': UTCDateTime(2016, 1, 24, 10, 37, 15, 150000), 'fm': 'N', 'channel': u'LHZ'}, 'S': {'picker': 'auto', 'snrdb': None, 'network': u'GR', 'weight': 4, 'Ao': None, 'lpp': UTCDateTime(2016, 1, 24, 10, 37, 15, 150000), 'snr': None, 'epp': UTCDateTime(2016, 1, 24, 10, 36, 43, 150000), 'mpp': UTCDateTime(2016, 1, 24, 10, 36, 59, 150000), 'fm': None, 'spe': None, 'channel': u'LHE'}}
|
||||
expected = {
|
||||
'P': {'picker': 'auto', 'snrdb': None, 'weight': 9, 'Mo': None, 'marked': 'shortsignallength', 'Mw': None,
|
||||
'fc': None, 'snr': None, 'mpp': UTCDateTime(2016, 1, 24, 10, 36, 59, 150000), 'w0': None, 'spe': None,
|
||||
'network': u'GR', 'epp': UTCDateTime(2016, 1, 24, 10, 36, 43, 150000),
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 37, 15, 150000), 'fm': 'N', 'channel': u'LHZ'},
|
||||
'S': {'picker': 'auto', 'snrdb': None, 'network': u'GR', 'weight': 4, 'Ao': None,
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 37, 15, 150000), 'snr': None,
|
||||
'epp': UTCDateTime(2016, 1, 24, 10, 36, 43, 150000),
|
||||
'mpp': UTCDateTime(2016, 1, 24, 10, 36, 59, 150000), 'fm': None, 'spe': None, 'channel': u'LHE'}}
|
||||
with HidePrints():
|
||||
result, station = autopickstation(wfstream=self.gra2, pickparam=self.pickparam_taupy_disabled, metadata=(None, None))
|
||||
result, station = autopickstation(wfstream=self.gra2, pickparam=self.pickparam_taupy_disabled,
|
||||
metadata=(None, None))
|
||||
self.assertDictContainsSubset(expected=expected['P'], actual=result['P'])
|
||||
self.assertDictContainsSubset(expected=expected['S'], actual=result['S'])
|
||||
self.assertEqual('GRA2', station)
|
||||
|
||||
def test_autopickstation_taupy_enabled_gra2(self):
|
||||
expected = {'P': {'picker': 'auto', 'snrdb': 13.957959025719253, 'weight': 0, 'Mo': None, 'marked': [], 'Mw': None, 'fc': None, 'snr': 24.876879503607871, 'mpp': UTCDateTime(2016, 1, 24, 10, 41, 29, 150000), 'w0': None, 'spe': 1.0, 'network': u'GR', 'epp': UTCDateTime(2016, 1, 24, 10, 41, 26, 150000), 'lpp': UTCDateTime(2016, 1, 24, 10, 41, 30, 150000), 'fm': None, 'channel': u'LHZ'}, 'S': {'picker': 'auto', 'snrdb': 10.573236990555648, 'network': u'GR', 'weight': 1, 'Ao': None, 'lpp': UTCDateTime(2016, 1, 24, 10, 50, 34, 150000), 'snr': 11.410999834108294, 'epp': UTCDateTime(2016, 1, 24, 10, 50, 21, 150000), 'mpp': UTCDateTime(2016, 1, 24, 10, 50, 33, 150000), 'fm': None, 'spe': 4.666666666666667, 'channel': u'LHE'}}
|
||||
expected = {
|
||||
'P': {'picker': 'auto', 'snrdb': 13.957959025719253, 'weight': 0, 'Mo': None, 'marked': [], 'Mw': None,
|
||||
'fc': None, 'snr': 24.876879503607871, 'mpp': UTCDateTime(2016, 1, 24, 10, 41, 29, 150000),
|
||||
'w0': None, 'spe': 1.0, 'network': u'GR', 'epp': UTCDateTime(2016, 1, 24, 10, 41, 26, 150000),
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 41, 30, 150000), 'fm': None, 'channel': u'LHZ'},
|
||||
'S': {'picker': 'auto', 'snrdb': 10.573236990555648, 'network': u'GR', 'weight': 1, 'Ao': None,
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 50, 34, 150000), 'snr': 11.410999834108294,
|
||||
'epp': UTCDateTime(2016, 1, 24, 10, 50, 21, 150000),
|
||||
'mpp': UTCDateTime(2016, 1, 24, 10, 50, 33, 150000), 'fm': None, 'spe': 4.666666666666667,
|
||||
'channel': u'LHE'}}
|
||||
with HidePrints():
|
||||
result, station = autopickstation(wfstream=self.gra2, pickparam=self.pickparam_taupy_enabled, metadata=self.metadata, origin = self.origin)
|
||||
result, station = autopickstation(wfstream=self.gra2, pickparam=self.pickparam_taupy_enabled,
|
||||
metadata=self.metadata, origin=self.origin)
|
||||
self.assertDictContainsSubset(expected=expected['P'], actual=result['P'])
|
||||
self.assertDictContainsSubset(expected=expected['S'], actual=result['S'])
|
||||
self.assertEqual('GRA2', station)
|
||||
|
||||
def test_autopickstation_taupy_disabled_ech(self):
|
||||
expected = {'P': {'picker': 'auto', 'snrdb': None, 'weight': 9, 'Mo': None, 'marked': 'SinsteadP', 'Mw': None, 'fc': None, 'snr': None, 'mpp': UTCDateTime(2016, 1, 24, 10, 26, 57), 'w0': None, 'spe': None, 'network': u'G', 'epp': UTCDateTime(2016, 1, 24, 10, 26, 41), 'lpp': UTCDateTime(2016, 1, 24, 10, 27, 13), 'fm': 'N', 'channel': u'LHZ'}, 'S': {'picker': 'auto', 'snrdb': None, 'network': u'G', 'weight': 4, 'Ao': None, 'lpp': UTCDateTime(2016, 1, 24, 10, 27, 13), 'snr': None, 'epp': UTCDateTime(2016, 1, 24, 10, 26, 41), 'mpp': UTCDateTime(2016, 1, 24, 10, 26, 57), 'fm': None, 'spe': None, 'channel': u'LHE'}}
|
||||
expected = {'P': {'picker': 'auto', 'snrdb': None, 'weight': 9, 'Mo': None, 'marked': 'SinsteadP', 'Mw': None,
|
||||
'fc': None, 'snr': None, 'mpp': UTCDateTime(2016, 1, 24, 10, 26, 57), 'w0': None, 'spe': None,
|
||||
'network': u'G', 'epp': UTCDateTime(2016, 1, 24, 10, 26, 41),
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 27, 13), 'fm': 'N', 'channel': u'LHZ'},
|
||||
'S': {'picker': 'auto', 'snrdb': None, 'network': u'G', 'weight': 4, 'Ao': None,
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 27, 13), 'snr': None,
|
||||
'epp': UTCDateTime(2016, 1, 24, 10, 26, 41), 'mpp': UTCDateTime(2016, 1, 24, 10, 26, 57),
|
||||
'fm': None, 'spe': None, 'channel': u'LHE'}}
|
||||
with HidePrints():
|
||||
result, station = autopickstation(wfstream=self.ech, pickparam=self.pickparam_taupy_disabled)
|
||||
self.assertDictContainsSubset(expected=expected['P'], actual=result['P'])
|
||||
@ -146,16 +196,32 @@ class TestAutopickStation(unittest.TestCase):
|
||||
|
||||
def test_autopickstation_taupy_enabled_ech(self):
|
||||
# this station has a long time of before the first onset, so taupy will help during picking
|
||||
expected = {'P': {'picker': 'auto', 'snrdb': 9.9753586609166316, 'weight': 0, 'Mo': None, 'marked': [], 'Mw': None, 'fc': None, 'snr': 9.9434218804137107, 'mpp': UTCDateTime(2016, 1, 24, 10, 41, 34), 'w0': None, 'spe': 1.6666666666666667, 'network': u'G', 'epp': UTCDateTime(2016, 1, 24, 10, 41, 29), 'lpp': UTCDateTime(2016, 1, 24, 10, 41, 35), 'fm': None, 'channel': u'LHZ'}, 'S': {'picker': 'auto', 'snrdb': 12.698999454169567, 'network': u'G', 'weight': 0, 'Ao': None, 'lpp': UTCDateTime(2016, 1, 24, 10, 50, 44), 'snr': 18.616581906366577, 'epp': UTCDateTime(2016, 1, 24, 10, 50, 33), 'mpp': UTCDateTime(2016, 1, 24, 10, 50, 43), 'fm': None, 'spe': 3.3333333333333335, 'channel': u'LHE'}}
|
||||
expected = {
|
||||
'P': {'picker': 'auto', 'snrdb': 9.9753586609166316, 'weight': 0, 'Mo': None, 'marked': [], 'Mw': None,
|
||||
'fc': None, 'snr': 9.9434218804137107, 'mpp': UTCDateTime(2016, 1, 24, 10, 41, 34), 'w0': None,
|
||||
'spe': 1.6666666666666667, 'network': u'G', 'epp': UTCDateTime(2016, 1, 24, 10, 41, 29),
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 41, 35), 'fm': None, 'channel': u'LHZ'},
|
||||
'S': {'picker': 'auto', 'snrdb': 12.698999454169567, 'network': u'G', 'weight': 0, 'Ao': None,
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 50, 44), 'snr': 18.616581906366577,
|
||||
'epp': UTCDateTime(2016, 1, 24, 10, 50, 33), 'mpp': UTCDateTime(2016, 1, 24, 10, 50, 43), 'fm': None,
|
||||
'spe': 3.3333333333333335, 'channel': u'LHE'}}
|
||||
with HidePrints():
|
||||
result, station = autopickstation(wfstream=self.ech, pickparam=self.pickparam_taupy_enabled, metadata=self.metadata, origin=self.origin)
|
||||
result, station = autopickstation(wfstream=self.ech, pickparam=self.pickparam_taupy_enabled,
|
||||
metadata=self.metadata, origin=self.origin)
|
||||
self.assertDictContainsSubset(expected=expected['P'], actual=result['P'])
|
||||
self.assertDictContainsSubset(expected=expected['S'], actual=result['S'])
|
||||
self.assertEqual('ECH', station)
|
||||
|
||||
def test_autopickstation_taupy_disabled_fiesa(self):
|
||||
# this station has a long time of before the first onset, so taupy will help during picking
|
||||
expected = {'P': {'picker': 'auto', 'snrdb': None, 'weight': 9, 'Mo': None, 'marked': 'SinsteadP', 'Mw': None, 'fc': None, 'snr': None, 'mpp': UTCDateTime(2016, 1, 24, 10, 35, 58), 'w0': None, 'spe': None, 'network': u'CH', 'epp': UTCDateTime(2016, 1, 24, 10, 35, 42), 'lpp': UTCDateTime(2016, 1, 24, 10, 36, 14), 'fm': 'N', 'channel': u'LHZ'}, 'S': {'picker': 'auto', 'snrdb': None, 'network': u'CH', 'weight': 4, 'Ao': None, 'lpp': UTCDateTime(2016, 1, 24, 10, 36, 14), 'snr': None, 'epp': UTCDateTime(2016, 1, 24, 10, 35, 42), 'mpp': UTCDateTime(2016, 1, 24, 10, 35, 58), 'fm': None, 'spe': None, 'channel': u'LHE'}}
|
||||
expected = {'P': {'picker': 'auto', 'snrdb': None, 'weight': 9, 'Mo': None, 'marked': 'SinsteadP', 'Mw': None,
|
||||
'fc': None, 'snr': None, 'mpp': UTCDateTime(2016, 1, 24, 10, 35, 58), 'w0': None, 'spe': None,
|
||||
'network': u'CH', 'epp': UTCDateTime(2016, 1, 24, 10, 35, 42),
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 36, 14), 'fm': 'N', 'channel': u'LHZ'},
|
||||
'S': {'picker': 'auto', 'snrdb': None, 'network': u'CH', 'weight': 4, 'Ao': None,
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 36, 14), 'snr': None,
|
||||
'epp': UTCDateTime(2016, 1, 24, 10, 35, 42), 'mpp': UTCDateTime(2016, 1, 24, 10, 35, 58),
|
||||
'fm': None, 'spe': None, 'channel': u'LHE'}}
|
||||
with HidePrints():
|
||||
result, station = autopickstation(wfstream=self.fiesa, pickparam=self.pickparam_taupy_disabled)
|
||||
self.assertDictContainsSubset(expected=expected['P'], actual=result['P'])
|
||||
@ -164,9 +230,18 @@ class TestAutopickStation(unittest.TestCase):
|
||||
|
||||
def test_autopickstation_taupy_enabled_fiesa(self):
|
||||
# this station has a long time of before the first onset, so taupy will help during picking
|
||||
expected = {'P': {'picker': 'auto', 'snrdb': 13.921049277904373, 'weight': 0, 'Mo': None, 'marked': [], 'Mw': None, 'fc': None, 'snr': 24.666352170589487, 'mpp': UTCDateTime(2016, 1, 24, 10, 41, 47), 'w0': None, 'spe': 1.2222222222222285, 'network': u'CH', 'epp': UTCDateTime(2016, 1, 24, 10, 41, 43, 333333), 'lpp': UTCDateTime(2016, 1, 24, 10, 41, 48), 'fm': None, 'channel': u'LHZ'}, 'S': {'picker': 'auto', 'snrdb': 10.893086316477728, 'network': u'CH', 'weight': 0, 'Ao': None, 'lpp': UTCDateTime(2016, 1, 24, 10, 51, 5), 'snr': 12.283118216397849, 'epp': UTCDateTime(2016, 1, 24, 10, 50, 59, 333333), 'mpp': UTCDateTime(2016, 1, 24, 10, 51, 2), 'fm': None, 'spe': 2.8888888888888764, 'channel': u'LHE'}}
|
||||
expected = {
|
||||
'P': {'picker': 'auto', 'snrdb': 13.921049277904373, 'weight': 0, 'Mo': None, 'marked': [], 'Mw': None,
|
||||
'fc': None, 'snr': 24.666352170589487, 'mpp': UTCDateTime(2016, 1, 24, 10, 41, 47), 'w0': None,
|
||||
'spe': 1.2222222222222285, 'network': u'CH', 'epp': UTCDateTime(2016, 1, 24, 10, 41, 43, 333333),
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 41, 48), 'fm': None, 'channel': u'LHZ'},
|
||||
'S': {'picker': 'auto', 'snrdb': 10.893086316477728, 'network': u'CH', 'weight': 0, 'Ao': None,
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 51, 5), 'snr': 12.283118216397849,
|
||||
'epp': UTCDateTime(2016, 1, 24, 10, 50, 59, 333333), 'mpp': UTCDateTime(2016, 1, 24, 10, 51, 2),
|
||||
'fm': None, 'spe': 2.8888888888888764, 'channel': u'LHE'}}
|
||||
with HidePrints():
|
||||
result, station = autopickstation(wfstream=self.fiesa, pickparam=self.pickparam_taupy_enabled, metadata=self.metadata, origin=self.origin)
|
||||
result, station = autopickstation(wfstream=self.fiesa, pickparam=self.pickparam_taupy_enabled,
|
||||
metadata=self.metadata, origin=self.origin)
|
||||
self.assertDictContainsSubset(expected=expected['P'], actual=result['P'])
|
||||
self.assertDictContainsSubset(expected=expected['S'], actual=result['S'])
|
||||
self.assertEqual('FIESA', station)
|
||||
@ -176,7 +251,8 @@ class TestAutopickStation(unittest.TestCase):
|
||||
wfstream = self.gra1.copy()
|
||||
wfstream = wfstream.select(channel='*E') + wfstream.select(channel='*N')
|
||||
with HidePrints():
|
||||
result, station = autopickstation(wfstream=wfstream, pickparam=self.pickparam_taupy_disabled, metadata=(None, None))
|
||||
result, station = autopickstation(wfstream=wfstream, pickparam=self.pickparam_taupy_disabled,
|
||||
metadata=(None, None))
|
||||
self.assertIsNone(result)
|
||||
self.assertEqual('GRA1', station)
|
||||
|
||||
@ -184,17 +260,36 @@ class TestAutopickStation(unittest.TestCase):
|
||||
"""Picking on a stream without horizontal traces should still pick the P phase on the vertical component"""
|
||||
wfstream = self.gra1.copy()
|
||||
wfstream = wfstream.select(channel='*Z')
|
||||
expected = {'P': {'picker': 'auto', 'snrdb': 15.405649120980094, 'network': u'GR', 'weight': 0, 'Ao': None, 'Mo': None, 'marked': [], 'lpp': UTCDateTime(2016, 1, 24, 10, 41, 32, 690000), 'Mw': None, 'fc': None, 'snr': 34.718816470730317, 'epp': UTCDateTime(2016, 1, 24, 10, 41, 28, 890000), 'mpp': UTCDateTime(2016, 1, 24, 10, 41, 31, 690000), 'w0': None, 'spe': 0.9333333333333323, 'fm': 'D', 'channel': u'LHZ'}, 'S': {'picker': 'auto', 'snrdb': None, 'network': None, 'weight': 4, 'Mo': None, 'Ao': None, 'lpp': None, 'Mw': None, 'fc': None, 'snr': None, 'marked': [], 'mpp': None, 'w0': None, 'spe': None, 'epp': None, 'fm': 'N', 'channel': None}}
|
||||
expected = {
|
||||
'P': {'picker': 'auto', 'snrdb': 15.405649120980094, 'network': u'GR', 'weight': 0, 'Ao': None, 'Mo': None,
|
||||
'marked': [], 'lpp': UTCDateTime(2016, 1, 24, 10, 41, 32, 690000), 'Mw': None, 'fc': None,
|
||||
'snr': 34.718816470730317, 'epp': UTCDateTime(2016, 1, 24, 10, 41, 28, 890000),
|
||||
'mpp': UTCDateTime(2016, 1, 24, 10, 41, 31, 690000), 'w0': None, 'spe': 0.9333333333333323, 'fm': 'D',
|
||||
'channel': u'LHZ'},
|
||||
'S': {'picker': 'auto', 'snrdb': None, 'network': None, 'weight': 4, 'Mo': None, 'Ao': None, 'lpp': None,
|
||||
'Mw': None, 'fc': None, 'snr': None, 'marked': [], 'mpp': None, 'w0': None, 'spe': None, 'epp': None,
|
||||
'fm': 'N', 'channel': None}}
|
||||
with HidePrints():
|
||||
result, station = autopickstation(wfstream=wfstream, pickparam=self.pickparam_taupy_disabled, metadata=(None, None))
|
||||
result, station = autopickstation(wfstream=wfstream, pickparam=self.pickparam_taupy_disabled,
|
||||
metadata=(None, None))
|
||||
self.assertEqual(expected, result)
|
||||
self.assertEqual('GRA1', station)
|
||||
|
||||
def test_autopickstation_a106_taupy_enabled(self):
|
||||
"""This station has invalid values recorded on both N and E component, but a pick can still be found on Z"""
|
||||
expected = {'P': {'picker': 'auto', 'snrdb': 12.862128789922826, 'network': u'Z3', 'weight': 0, 'Ao': None, 'Mo': None, 'marked': [], 'lpp': UTCDateTime(2016, 1, 24, 10, 41, 34), 'Mw': None, 'fc': None, 'snr': 19.329155459132608, 'epp': UTCDateTime(2016, 1, 24, 10, 41, 30), 'mpp': UTCDateTime(2016, 1, 24, 10, 41, 33), 'w0': None, 'spe': 1.6666666666666667, 'fm': None, 'channel': u'LHZ'}, 'S': {'picker': 'auto', 'snrdb': None, 'network': u'Z3', 'weight': 4, 'Ao': None, 'Mo': None, 'marked': [], 'lpp': UTCDateTime(2016, 1, 24, 10, 28, 56), 'Mw': None, 'fc': None, 'snr': None, 'epp': UTCDateTime(2016, 1, 24, 10, 28, 24), 'mpp': UTCDateTime(2016, 1, 24, 10, 28, 40), 'w0': None, 'spe': None, 'fm': None, 'channel': u'LHE'}}
|
||||
expected = {
|
||||
'P': {'picker': 'auto', 'snrdb': 12.862128789922826, 'network': u'Z3', 'weight': 0, 'Ao': None, 'Mo': None,
|
||||
'marked': [], 'lpp': UTCDateTime(2016, 1, 24, 10, 41, 34), 'Mw': None, 'fc': None,
|
||||
'snr': 19.329155459132608, 'epp': UTCDateTime(2016, 1, 24, 10, 41, 30),
|
||||
'mpp': UTCDateTime(2016, 1, 24, 10, 41, 33), 'w0': None, 'spe': 1.6666666666666667, 'fm': None,
|
||||
'channel': u'LHZ'},
|
||||
'S': {'picker': 'auto', 'snrdb': None, 'network': u'Z3', 'weight': 4, 'Ao': None, 'Mo': None, 'marked': [],
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 28, 56), 'Mw': None, 'fc': None, 'snr': None,
|
||||
'epp': UTCDateTime(2016, 1, 24, 10, 28, 24), 'mpp': UTCDateTime(2016, 1, 24, 10, 28, 40), 'w0': None,
|
||||
'spe': None, 'fm': None, 'channel': u'LHE'}}
|
||||
with HidePrints():
|
||||
result, station = autopickstation(wfstream=self.a106, pickparam=self.pickparam_taupy_enabled, metadata=self.metadata, origin=self.origin)
|
||||
result, station = autopickstation(wfstream=self.a106, pickparam=self.pickparam_taupy_enabled,
|
||||
metadata=self.metadata, origin=self.origin)
|
||||
self.assertEqual(expected, result)
|
||||
|
||||
def test_autopickstation_station_missing_in_metadata(self):
|
||||
@ -202,10 +297,22 @@ class TestAutopickStation(unittest.TestCase):
|
||||
relative to the theoretical onset to one relative to the traces starttime, eg never negative.
|
||||
"""
|
||||
self.pickparam_taupy_enabled.setParamKV('pstart', -100) # modify starttime to be relative to theoretical onset
|
||||
expected = {'P': {'picker': 'auto', 'snrdb': 14.464757855513506, 'network': u'Z3', 'weight': 0, 'Mo': None, 'Ao': None, 'lpp': UTCDateTime(2016, 1, 24, 10, 41, 39, 605000), 'Mw': None, 'fc': None, 'snr': 27.956048519707181, 'marked': [], 'mpp': UTCDateTime(2016, 1, 24, 10, 41, 38, 605000), 'w0': None, 'spe': 1.6666666666666667, 'epp': UTCDateTime(2016, 1, 24, 10, 41, 35, 605000), 'fm': None, 'channel': u'LHZ'}, 'S': {'picker': 'auto', 'snrdb': 10.112844176301248, 'network': u'Z3', 'weight': 1, 'Mo': None, 'Ao': None, 'lpp': UTCDateTime(2016, 1, 24, 10, 50, 51, 605000), 'Mw': None, 'fc': None, 'snr': 10.263238413785425, 'marked': [], 'mpp': UTCDateTime(2016, 1, 24, 10, 50, 48, 605000), 'w0': None, 'spe': 4.666666666666667, 'epp': UTCDateTime(2016, 1, 24, 10, 50, 40, 605000), 'fm': None, 'channel': u'LHE'}}
|
||||
expected = {
|
||||
'P': {'picker': 'auto', 'snrdb': 14.464757855513506, 'network': u'Z3', 'weight': 0, 'Mo': None, 'Ao': None,
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 41, 39, 605000), 'Mw': None, 'fc': None,
|
||||
'snr': 27.956048519707181, 'marked': [], 'mpp': UTCDateTime(2016, 1, 24, 10, 41, 38, 605000),
|
||||
'w0': None, 'spe': 1.6666666666666667, 'epp': UTCDateTime(2016, 1, 24, 10, 41, 35, 605000),
|
||||
'fm': None, 'channel': u'LHZ'},
|
||||
'S': {'picker': 'auto', 'snrdb': 10.112844176301248, 'network': u'Z3', 'weight': 1, 'Mo': None, 'Ao': None,
|
||||
'lpp': UTCDateTime(2016, 1, 24, 10, 50, 51, 605000), 'Mw': None, 'fc': None,
|
||||
'snr': 10.263238413785425, 'marked': [], 'mpp': UTCDateTime(2016, 1, 24, 10, 50, 48, 605000),
|
||||
'w0': None, 'spe': 4.666666666666667, 'epp': UTCDateTime(2016, 1, 24, 10, 50, 40, 605000), 'fm': None,
|
||||
'channel': u'LHE'}}
|
||||
with HidePrints():
|
||||
result, station = autopickstation(wfstream = self.a005a, pickparam=self.pickparam_taupy_enabled, metadata=self.metadata, origin=self.origin)
|
||||
result, station = autopickstation(wfstream=self.a005a, pickparam=self.pickparam_taupy_enabled,
|
||||
metadata=self.metadata, origin=self.origin)
|
||||
self.assertEqual(expected, result)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
|
||||
33
tests/test_get_qualities_from_xml.py
Normal file
33
tests/test_get_qualities_from_xml.py
Normal file
@ -0,0 +1,33 @@
|
||||
import unittest
|
||||
|
||||
from pylot.core.io.phases import getQualitiesfromxml
|
||||
|
||||
|
||||
class TestQualityFromXML(unittest.TestCase):
|
||||
def setUp(self):
|
||||
self.path = '.'
|
||||
self.ErrorsP = [0.02, 0.04, 0.08, 0.16]
|
||||
self.ErrorsS = [0.04, 0.08, 0.16, 0.32]
|
||||
self.test0_result = [[0.0136956521739, 0.0126, 0.0101612903226, 0.00734848484849, 0.0135069444444,
|
||||
0.00649659863946, 0.0129513888889, 0.0122747747748, 0.0119252873563, 0.0103947368421,
|
||||
0.0092380952381, 0.00916666666667, 0.0104444444444, 0.0125333333333, 0.00904761904762,
|
||||
0.00885714285714, 0.00911616161616, 0.0164166666667, 0.0128787878788, 0.0122756410256,
|
||||
0.013653253667966917], [0.0239333333333, 0.0223791578953, 0.0217974304255],
|
||||
[0.0504861111111, 0.0610833333333], [], [0.171029411765]], [
|
||||
[0.0195, 0.0203623188406, 0.0212121212121, 0.0345833333333, 0.0196180555556,
|
||||
0.0202536231884, 0.0200347222222, 0.0189, 0.0210763888889, 0.018275862069,
|
||||
0.0213888888889, 0.0319791666667, 0.0205303030303, 0.0156388888889, 0.0192,
|
||||
0.0231349206349, 0.023625, 0.02875, 0.0195512820513, 0.0239393939394, 0.0234166666667,
|
||||
0.0174702380952, 0.0204151307995], [0.040314343081226646], [0.148555555556], [], []]
|
||||
self.test1_result = [77.77777777777777, 11.11111111111111, 7.407407407407407, 0, 3.7037037037037037],\
|
||||
[92.0, 4.0, 4.0, 0, 0]
|
||||
|
||||
def test_result_plotflag0(self):
|
||||
self.assertEqual(getQualitiesfromxml(self.path, self.ErrorsP, self.ErrorsS, 0), self.test0_result)
|
||||
|
||||
def test_result_plotflag1(self):
|
||||
self.assertEqual(getQualitiesfromxml(self.path, self.ErrorsP, self.ErrorsS, 1), self.test1_result)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
@ -1,4 +1,5 @@
|
||||
import unittest
|
||||
|
||||
from pylot.core.pick.utils import get_quality_class
|
||||
|
||||
|
||||
@ -52,5 +53,6 @@ class TestQualityClassFromUncertainty(unittest.TestCase):
|
||||
# Error exactly in class 3
|
||||
self.assertEqual(3, get_quality_class(5.6, self.error_classes))
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
|
||||
@ -33,6 +33,7 @@ class HidePrints:
|
||||
def silencer(*args, **kwargs):
|
||||
with HidePrints():
|
||||
func(*args, **kwargs)
|
||||
|
||||
return silencer
|
||||
|
||||
def __init__(self, hide_prints=True):
|
||||
|
||||
Loading…
Reference in New Issue
Block a user
Please remove commented code if not needed for backup solution implementation. In this case just remove.