WIP: Simplify data structure #39
@ -20,6 +20,10 @@ from pylot.core.io.inputs import PylotParameter, FilterOptions
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from pylot.core.util.obspyDMT_interface import check_obspydmt_eventfolder
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from pylot.styles import style_settings
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Rgba: Type[tuple] = Tuple[int, int, int, int]
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Mplrgba: Type[tuple] = Tuple[float, float, float, float]
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Mplrgbastr: Type[tuple] = Tuple[str, str, str, str]
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def _pickle_method(m):
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if m.im_self is None:
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@ -121,7 +125,7 @@ def gen_Pool(ncores=0):
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print('gen_Pool: Generated multiprocessing Pool with {} cores\n'.format(ncores))
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pool = multiprocessing.Pool(ncores, maxtasksperchild=100)
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pool = multiprocessing.Pool(ncores)
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return pool
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@ -382,6 +386,7 @@ def get_bool(value):
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else:
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return False
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def four_digits(year):
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"""
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takes a two digit year integer and returns the correct four digit equivalent
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@ -655,32 +660,53 @@ def key_for_set_value(d):
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return r
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def prepTimeAxis(stime, trace, verbosity=0):
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def prep_time_axis(offset, trace, verbosity=0):
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"""
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takes a starttime and a trace object and returns a valid time axis for
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takes an offset and a trace object and returns a valid time axis for
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plotting
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:param stime: start time of the actual seismogram as UTCDateTime
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:type stime: `~obspy.core.utcdatetime.UTCDateTime`
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:param offset: offset of the actual seismogram on plotting axis
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:type offset: float or int
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:param trace: seismic trace object
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:type trace: `~obspy.core.trace.Trace`
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:param verbosity: if != 0, debug output will be written to console
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:type verbosity: int
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:return: valid numpy array with time stamps for plotting
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:rtype: `~numpy.ndarray`
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>>> tr = read()[0]
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>>> prep_time_axis(0., tr)
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array([0.00000000e+00, 1.00033344e-02, 2.00066689e-02, ...,
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2.99799933e+01, 2.99899967e+01, 3.00000000e+01])
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>>> prep_time_axis(22.5, tr)
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array([22.5 , 22.51000333, 22.52000667, ..., 52.47999333,
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52.48999667, 52.5 ])
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>>> prep_time_axis(tr.stats.starttime, tr)
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Traceback (most recent call last):
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...
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AssertionError: 'offset' is not of type 'float' or 'int'; type: <class 'obspy.core.utcdatetime.UTCDateTime'>
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>>> tr.stats.npts -= 1
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>>> prep_time_axis(0, tr)
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array([0.00000000e+00, 1.00033356e-02, 2.00066711e-02, ...,
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2.99699933e+01, 2.99799967e+01, 2.99900000e+01])
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>>> tr.stats.npts += 2
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>>> prep_time_axis(0, tr)
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array([0.00000000e+00, 1.00033333e-02, 2.00066667e-02, ...,
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2.99899933e+01, 2.99999967e+01, 3.00100000e+01])
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"""
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assert isinstance(offset, (float, int)), "'offset' is not of type 'float' or 'int'; type: {}".format(type(offset))
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nsamp = trace.stats.npts
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srate = trace.stats.sampling_rate
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tincr = trace.stats.delta
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etime = stime + nsamp / srate
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time_ax = np.linspace(stime, etime, nsamp)
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etime = offset + nsamp / srate
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time_ax = np.linspace(offset, etime, nsamp)
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if len(time_ax) < nsamp:
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if verbosity:
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print('elongate time axes by one datum')
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time_ax = np.arange(stime, etime + tincr, tincr)
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time_ax = np.arange(offset, etime + tincr, tincr)
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elif len(time_ax) > nsamp:
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if verbosity:
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print('shorten time axes by one datum')
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time_ax = np.arange(stime, etime - tincr, tincr)
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time_ax = np.arange(offset, etime - tincr, tincr)
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if len(time_ax) != nsamp:
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print('Station {0}, {1} samples of data \n '
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'{2} length of time vector \n'
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@ -713,7 +739,7 @@ def find_horizontals(data):
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return rval
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def pick_color(picktype, phase, quality=0):
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def pick_color(picktype: Literal['manual', 'automatic'], phase: Literal['P', 'S'], quality: int = 0) -> Rgba:
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"""
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Create pick color by modifying the base color by the quality.
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@ -726,7 +752,7 @@ def pick_color(picktype, phase, quality=0):
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:param quality: quality of pick. Decides the new intensity of the modifier color
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:type quality: int
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:return: tuple containing modified rgba color values
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:rtype: (int, int, int, int)
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:rtype: Rgba
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"""
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min_quality = 3
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bpc = base_phase_colors(picktype, phase) # returns dict like {'modifier': 'g', 'rgba': (0, 0, 255, 255)}
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@ -782,17 +808,17 @@ def pick_linestyle_plt(picktype, key):
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return linestyles[picktype][key]
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def modify_rgba(rgba, modifier, intensity):
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def modify_rgba(rgba: Rgba, modifier: Literal['r', 'g', 'b'], intensity: float) -> Rgba:
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"""
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Modify rgba color by adding the given intensity to the modifier color
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:param rgba: tuple containing rgba values
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:type rgba: (int, int, int, int)
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:param modifier: which color should be modified, eg. 'r', 'g', 'b'
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:type modifier: str
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:type rgba: Rgba
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:param modifier: which color should be modified; options: 'r', 'g', 'b'
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:type modifier: Literal['r', 'g', 'b']
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:param intensity: intensity to be added to selected color
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:type intensity: float
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:return: tuple containing rgba values
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:rtype: (int, int, int, int)
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:rtype: Rgba
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"""
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rgba = list(rgba)
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index = {'r': 0,
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@ -826,18 +852,20 @@ def transform_colors_mpl_str(colors, no_alpha=False):
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Transforms rgba color values to a matplotlib string of color values with a range of [0, 1]
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:param colors: tuple of rgba color values ranging from [0, 255]
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:type colors: (float, float, float, float)
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:param no_alpha: Wether to return a alpha value in the matplotlib color string
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:param no_alpha: Whether to return an alpha value in the matplotlib color string
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:type no_alpha: bool
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:return: String containing r, g, b values and alpha value if no_alpha is False (default)
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:rtype: str
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>>> transform_colors_mpl_str((255., 255., 255., 255.), True)
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'(1.0, 1.0, 1.0)'
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>>> transform_colors_mpl_str((255., 255., 255., 255.))
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'(1.0, 1.0, 1.0, 1.0)'
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"""
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colors = list(colors)
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colors_mpl = tuple([color / 255. for color in colors])
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if no_alpha:
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colors_mpl = '({}, {}, {})'.format(*colors_mpl)
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return '({}, {}, {})'.format(*transform_colors_mpl(colors))
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else:
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colors_mpl = '({}, {}, {}, {})'.format(*colors_mpl)
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return colors_mpl
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return '({}, {}, {}, {})'.format(*transform_colors_mpl(colors))
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def transform_colors_mpl(colors):
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@ -847,6 +875,10 @@ def transform_colors_mpl(colors):
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:type colors: (float, float, float, float)
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:return: tuple of rgba color values ranging from [0, 1]
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:rtype: (float, float, float, float)
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>>> transform_colors_mpl((127.5, 0., 63.75, 255.))
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(0.5, 0.0, 0.25, 1.0)
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>>> transform_colors_mpl(())
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"""
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colors = list(colors)
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colors_mpl = tuple([color / 255. for color in colors])
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@ -49,7 +49,7 @@ from pylot.core.pick.utils import getSNR, earllatepicker, getnoisewin, \
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from pylot.core.pick.compare import Comparison
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from pylot.core.pick.autopick import fmpicker
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from pylot.core.util.defaults import OUTPUTFORMATS, FILTERDEFAULTS
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from pylot.core.util.utils import prepTimeAxis, full_range, demeanTrace, isSorted, findComboBoxIndex, clims, \
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from pylot.core.util.utils import prep_time_axis, full_range, demeanTrace, isSorted, findComboBoxIndex, clims, \
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pick_linestyle_plt, pick_color_plt, \
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check4rotated, check4doubled, check_for_gaps_and_merge, check_for_nan, identifyPhase, \
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loopIdentifyPhase, trim_station_components, transformFilteroptions2String, \
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@ -923,10 +923,10 @@ class WaveformWidgetPG(QtWidgets.QWidget):
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msg = 'plotting %s channel of station %s' % (channel, station)
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print(msg)
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stime = trace.stats.starttime - self.wfstart
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time_ax = prepTimeAxis(stime, trace)
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time_ax = prep_time_axis(stime, trace)
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if st_syn:
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stime_syn = trace_syn.stats.starttime - self.wfstart
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time_ax_syn = prepTimeAxis(stime_syn, trace_syn)
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time_ax_syn = prep_time_axis(stime_syn, trace_syn)
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if method == 'fast':
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trace.data, time_ax = self.minMax(trace, time_ax)
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@ -1409,7 +1409,7 @@ class PylotCanvas(FigureCanvas):
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msg = 'plotting %s channel of station %s' % (channel, station)
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print(msg)
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stime = trace.stats.starttime - wfstart
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time_ax = prepTimeAxis(stime, trace)
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time_ax = prep_time_axis(stime, trace)
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if time_ax is not None:
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if scaleToChannel:
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st_scale = wfdata.select(channel=scaleToChannel)
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@ -1447,7 +1447,7 @@ class PylotCanvas(FigureCanvas):
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if not scaleddata:
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trace.detrend('constant')
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trace.normalize(np.max(np.abs(trace.data)) * 2)
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time_ax = prepTimeAxis(stime, trace)
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time_ax = prep_time_axis(stime, trace)
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times = [time for index, time in enumerate(time_ax) if not index % nth_sample]
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p_data = compare_stream[0].data
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# #normalize
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@ -2548,7 +2548,7 @@ class PickDlg(QDialog):
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# prepare plotting of data
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for trace in data:
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t = prepTimeAxis(trace.stats.starttime - stime, trace)
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t = prep_time_axis(trace.stats.starttime - stime, trace)
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inoise = getnoisewin(t, ini_pick, noise_win, gap_win)
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trace = demeanTrace(trace, inoise)
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# upscale trace data in a way that each trace is vertically zoomed to noiselevel*factor
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