[update] increased robustness of correlation picker. If autoPyLoT fails on the stacked trace it tries to pick other stacked traces. Ignoring failed autoPyLoT picks can manually be set if they are not important (e.g. when only pick differences are important)

[minor] Commented out search for network name in metadata filename considered being unsafe

PyLoT.py

@@ -716,14 +716,14 @@ class MainWindow(QMainWindow):
         self.tabs.addTab(wf_tab, 'Waveform Plot')
         self.tabs.addTab(array_tab, 'Array Map')
         self.tabs.addTab(events_tab, 'Eventlist')
-        self.tabs.addTab(spectro_tab, 'Spectro')
+        #self.tabs.addTab(spectro_tab, 'Spectro')
 
         self.wf_layout.addWidget(self.no_data_label)
         self.wf_layout.addWidget(self.wf_scroll_area)
         self.wf_scroll_area.setWidgetResizable(True)
         self.init_array_tab()
         self.init_event_table()
-        self.init_spectro_tab()
+        #self.init_spectro_tab()
         self.tabs.setCurrentIndex(0)
 
         self.eventLabel = QLabel()
@@ -1011,7 +1011,7 @@ class MainWindow(QMainWindow):
         for event in events:
             for filename in filenames:
                 if os.path.isfile(filename) and event.pylot_id in filename:
-                    self.load_data(filename, draw=False, event=event, ask_user=True, merge_strategy=sld.merge_strategy)
+                    self.load_data(filename, draw=False, event=event, ask_user=False, merge_strategy=sld.merge_strategy)
                     refresh = True
         if not refresh:
             return
@@ -1020,8 +1020,8 @@ class MainWindow(QMainWindow):
         self.fill_eventbox()
         self.setDirty(True)
 
-    def load_data(self, fname=None, loc=False, draw=True, event=None, ask_user=False, merge_strategy='Overwrite'):
+    def load_data(self, fname=None, loc=False, draw=True, event=None, ask_user=True, merge_strategy='Overwrite',):
-        if not ask_user:
+        if ask_user:
             if not self.okToContinue():
                 return
         if fname is None:
@@ -1034,7 +1034,7 @@ class MainWindow(QMainWindow):
         if not event:
             event = self.get_current_event()
 
-        if event.picks:
+        if event.picks and ask_user:
             qmb = QMessageBox(self, icon=QMessageBox.Question,
                               text='Do you want to overwrite the data?',)
             overwrite_button = qmb.addButton('Overwrite', QMessageBox.YesRole)
@@ -1976,7 +1976,6 @@ class MainWindow(QMainWindow):
         self.dataPlot.activateObspyDMToptions(self.obspy_dmt)
         if self.obspy_dmt:
             self.prepareObspyDMT_data(eventpath)
-            self.dataPlot.activateCompareOptions(True)
 
     def loadWaveformData(self):
         '''
@@ -2153,10 +2152,11 @@ class MainWindow(QMainWindow):
         self.wf_scroll_area.setVisible(len(plots) > 0)
         self.no_data_label.setVisible(not len(plots) > 0)
         for times, data, times_syn, data_syn in plots:
-            self.dataPlot.plotWidget.getPlotItem().plot(times, data,
+            self.dataPlot.plotWidget.getPlotItem().plot(np.array(times), np.array(data),
-                                                        pen=self.dataPlot.pen_linecolor)
+                                                        pen=self.dataPlot.pen_linecolor,
+                                                        skipFiniteCheck=True)
             if len(data_syn) > 0:
-                self.dataPlot.plotWidget.getPlotItem().plot(times_syn, data_syn,
+                self.dataPlot.plotWidget.getPlotItem().plot(np.array(times_syn), np.array(data_syn),
                                                             pen=self.dataPlot.pen_linecolor_syn)
         self.dataPlot.reinitMoveProxy()
         self.highlight_stations()
@@ -3096,7 +3096,7 @@ class MainWindow(QMainWindow):
 
                 if self.pg:
                     if spe:
-                        if picks['epp'] and picks['lpp']:
+                        if not self.plot_method == 'fast' and picks['epp'] and picks['lpp']:
                             pen = make_pen(picktype, phaseID, 'epp', quality)
                             self.drawnPicks[picktype][station].append(pw.plot([epp, epp], ylims,
                                                                               alpha=.25, pen=pen, name='EPP'))
@@ -3590,7 +3590,7 @@ class MainWindow(QMainWindow):
     def calc_magnitude(self):
         self.init_metadata()
         if not self.metadata:
-            return None
+            return []
 
         wf_copy = self.get_data().getWFData().copy()
 
@@ -3599,6 +3599,10 @@ class MainWindow(QMainWindow):
         for station in np.unique(list(self.getPicks('manual').keys()) + list(self.getPicks('auto').keys())):
             wf_select += wf_copy.select(station=station)
 
+        if not wf_select:
+            logging.warning('Empty Stream in calc_magnitude. Return.')
+            return []
+
         corr_wf = restitute_data(wf_select, self.metadata)
         # calculate moment magnitude
         moment_mag = MomentMagnitude(corr_wf, self.get_data().get_evt_data(), self.inputs.get('vp'),

README.md

@@ -54,33 +54,17 @@ In order to run PyLoT you need to install:
 
 #### Some handwork:
 
-PyLoT needs a properties folder on your system to work. It should be situated in your home directory
+Some extra information on error estimates (just needed for reading old PILOT data) and the Richter magnitude scaling
-(on Windows usually C:/Users/*username*):
-
-    mkdir ~/.pylot
-
-In the next step you have to copy some files to this directory:
-
-*for local distance seismicity*
-
-    cp path-to-pylot/inputs/pylot_local.in ~/.pylot/pylot.in
-
-*for regional distance seismicity*
-
-    cp path-to-pylot/inputs/pylot_regional.in ~/.pylot/pylot.in
-
-*for global distance seismicity*
-
-    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
 
     cp path-to-pylot/inputs/PILOT_TimeErrors.in path-to-pylot/inputs/richter_scaling.data ~/.pylot/
 
 You may need to do some modifications to these files. Especially folder names should be reviewed.
 
-PyLoT has been tested on Mac OSX (10.11), Debian Linux 8 and on Windows 10.
+PyLoT has been tested on Mac OSX (10.11), Debian Linux 8 and on Windows 10/11.
+
+## Example Dataset
+An example dataset with waveform data, metadata and automatic picks in the obspy-dmt dataset format for testing the teleseismic picking can be found at https://zenodo.org/doi/10.5281/zenodo.13759803
 
 ## Release notes
 
@@ -89,6 +73,7 @@ PyLoT has been tested on Mac OSX (10.11), Debian Linux 8 and on Windows 10.
 - event organisation in project files and waveform visualisation
 - consistent manual phase picking through predefined SNR dependant zoom level
 - consistent automatic phase picking routines using Higher Order Statistics, AIC and Autoregression
+- pick correlation correction for teleseismic waveforms
 - interactive tuning of auto-pick parameters
 - uniform uncertainty estimation from waveform's properties for automatic and manual picks
 - pdf representation and comparison of picks taking the uncertainty intrinsically into account
@@ -97,17 +82,17 @@ PyLoT has been tested on Mac OSX (10.11), Debian Linux 8 and on Windows 10.
 
 #### Known issues:
 
-We hope to solve these with the next release.
+Current release is still in development progress and has several issues. We are currently lacking manpower, but hope to assess many of the issues in the near future.
 
 ## Staff
 
-Original author(s): M. Rische, S. Wehling-Benatelli, L. Kueperkoch, M. Bischoff (PILOT)
+Developer(s): M. Paffrath, S. Wehling-Benatelli, L. Kueperkoch, D. Arnold, K. Cökerim, K. Olbert, M. Bischoff, C. Wollin, M. Rische, S. Zimmermann
 
-Developer(s): S. Wehling-Benatelli, M. Paffrath, L. Kueperkoch, K. Olbert, M. Bischoff, C. Wollin, M. Rische, D. Arnold, K. Cökerim, S. Zimmermann
+Original author(s): M. Rische, S. Wehling-Benatelli, L. Kueperkoch, M. Bischoff (PILOT)
 
 Others: A. Bruestle, T. Meier, W. Friederich
 
 
 [ObsPy]: http://github.com/obspy/obspy/wiki
 
-August 2024
+March 2025

docs/correlation.md

@@ -0,0 +1,77 @@
+# Pick-Correlation Correction
+
+## Introduction
+Currently, the pick-correlation correction algorithm is not accessible from they PyLoT GUI. The main file *pick_correlation_correction.py* is located in the directory *pylot\correlation*.
+The program only works for an obspy dmt database structure.
+
+The basic workflow of the algorithm is shown in the following diagram. The first step **(1)** is the normal (automatic) picking procedure in PyLoT. Everything from step **(2)** to **(5)** is part of the correlation correction algorithm.
+
+*Note: The first step is not required in case theoretical onsets are used instead of external picks when the parameter use_taupy_onsets is set to True. However, an existing event quakeML (.xml) file generated by PyLoT might be required for each event in case not external picks are used.*
+
+![images/workflow_stacking.png](images/workflow_stacking.png)
+
+A detailed description of the algorithm can be found in the corresponding publication:
+
+*Paffrath, M., Friederich, W., and the AlpArray and AlpArray-SWATH D Working Groups: Teleseismic P waves at the AlpArray seismic network: wave fronts, absolute travel times and travel-time residuals, Solid Earth, 12, 1635–1660, https://doi.org/10.5194/se-12-1635-2021, 2021.*
+
+## How to use
+To use the program you have to call the main program providing two mandatory arguments: a path to the obspy dmt database folder *dmt_database_path* and the path to the PyLoT infile *pylot.in* for picking of the beam trace:
+
+```python pick_correlation_correction.py dmt_database_path pylot.in```
+
+By default, the parameter file *parameters.yaml* is used. You can use the command line option *--params* to specify a different parameter file and other optional arguments such as *-pd* for plotting detailed information or *-n 4* to use 4 cores for parallel processing:
+
+```python pick_correlation_correction.py dmt_database_path pylot.in --params parameters_adriaarray.yaml -pd -n 4```
+
+## Cross-Correlation Parameters
+
+The program uses the parameters in the file *parameters.yaml* by default. You can use the command line option *--params* to specify a different parameter file. An example of the parameter file is provided in the *correlation\parameters.yaml* file.
+
+In the top level of the parameter file the logging level *logging* can be set, as well as a list of pick phases *pick_phases* (e.g. ['P', 'S']).
+
+For each pick phase the different parameters can be set in the first sub-level of the parameter file, e.g.:
+
+```yaml
+logging: info
+pick_phases: ['P', 'S']
+
+P:
+ min_corr_stacking: 0.8
+ min_corr_export: 0.6
+ [...]
+
+S:
+ min_corr_stacking: 0.7
+ [...]
+```
+
+The following parameters are available:
+
+
+| Parameter Name                 | Description                                                                                        | Parameter Type |
+|--------------------------------|----------------------------------------------------------------------------------------------------|----------------|
+| min_corr_stacking              | Minimum correlation coefficient for building beam trace                                            | float          |
+| min_corr_export                | Minimum correlation coefficient for pick export                                                    | float          |
+| min_stack                      | Minimum number of stations for building beam trace                                                 | int            |
+| t_before                       | Correlation window before reference pick                                                           | float          |
+| t_after                        | Correlation window after reference pick                                                            | float          |
+| cc_maxlag                      | Maximum shift for initial correlation                                                              | float          |
+| cc_maxlag2                     | Maximum shift for second (final) correlation (also for calculating pick uncertainty)               | float          |
+| initial_pick_outlier_threshold | Threshold for excluding large outliers of initial (AIC) picks                                      | float          |
+| export_threshold               | Automatically exclude all onsets which deviate more than this threshold from corrected taup onsets | float          |
+| min_picks_export               | Minimum number of correlated picks for export                                                      | int            |
+| min_picks_autopylot            | Minimum number of reference auto picks to continue with event                                      | int            |
+| check_RMS                      | Do RMS check to search for restitution errors (very experimental)                                  | bool           |
+| use_taupy_onsets               | Use taupy onsets as reference picks instead of external picks                                      | bool           |
+| station_list                   | Use the following stations as reference for stacking                                               | list[str]      |
+| use_stacked_trace              | Use existing stacked trace if found (spare re-computation)                                         | bool           |
+| data_dir                       | obspyDMT data subdirectory (e.g. 'raw', 'processed')                                               | str            |
+| pickfile_extension             | Use quakeML files (PyLoT output) with the following extension                                      | str            |
+| dt_stacking                    | Time difference for stacking window (in seconds)                                                   | list[float]    |
+| filter_options                 | Filter for first correlation (rough)                                                               | dict           |
+| filter_options_final           | Filter for second correlation (fine)                                                               | dict           |
+| filter_type                    | Filter type (e.g. bandpass)                                                                        | str            |
+| sampfreq                       | Sampling frequency (in Hz)                                                                         | float          |
+
+## Example Dataset
+An example dataset with waveform data, metadata and automatic picks in the obspy-dmt dataset format for testing can be found at https://zenodo.org/doi/10.5281/zenodo.13759803

docs/tuning.md

@@ -6,122 +6,123 @@ A description of the parameters used for determining automatic picks.
 
 Parameters applied to the traces before picking algorithm starts.
 
-| Name                | Description                                                                                                                                                                                                             |
+| Name          | Description                                                                                                                                                                                                             |
-|---------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+|---------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| *P Start*, *P
+| *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.    |
+| 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
+| *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. |
+| 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
+| *Bandpass     |                                                                                                                                                                                                                         |
-Z1*       | Filter settings for Butterworth bandpass applied to vertical trace for calculation of initial P pick.                                                                                                                   |
+| Z1*           | Filter settings for Butterworth bandpass applied to vertical trace for calculation of initial P pick.                                                                                                                   |
-| *Bandpass
+| *Bandpass     |                                                                                                                                                                                                                         |
-Z2*       | Filter settings for Butterworth bandpass applied to vertical trace for calculation of precise P pick.                                                                                                                   |
+| Z2*           | Filter settings for Butterworth bandpass applied to vertical trace for calculation of precise P pick.                                                                                                                   |
-| *Bandpass
+| *Bandpass     |                                                                                                                                                                                                                         |
-H1*       | Filter settings for Butterworth bandpass applied to horizontal traces for calculation of initial S pick.                                                                                                                |
+| H1*           | Filter settings for Butterworth bandpass applied to horizontal traces for calculation of initial S pick.                                                                                                                |
-| *Bandpass
+| *Bandpass     |                                                                                                                                                                                                                         |
-H2*       | Filter settings for Butterworth bandpass applied to horizontal traces for calculation of precise S pick.                                                                                                                |
+| 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                                                                                                                  |
+| Name                                                                                                              | Description                                                                                                            |
-|--------------|------------------------------------------------------------------------------------------------------------------------------|
+|-------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|
-| *
+| *                                                                                                                 |                                                                                                                        |
-tLTA*       | Size of gliding LTA window in seconds used for calculation of HOS-CF.                                                        |
+| tLTA*                                                                                                             | Size of gliding LTA window in seconds used for calculation of HOS-CF.                                                  |
-| *pickwin
+| *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.       |
+| 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.                                             |
+| 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.                             |
+| checkwinP*                                                                                                        | Time in front of the global maximum of the HOS-CF in which to search for a second local extrema.                       |
-| *minfactorP* | Used with *
+| *minfactorP*                                                                                                      | Used with *                                                                                                            |
-checkwinP*. If a second local maximum is found, it has to be at least as big as the first maximum * *minfactorP*. |
+| 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.                                       |
+| 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.                                      |
+| tnoise*                                                                                                           | Time window in seconds in front of initial P pick used for determining noise amplitude.                                |
-| *tsafetey*   | Time in seconds between *tsignal* and *
+| *tsafetey*                                                                                                        | Time in seconds between *tsignal* and *                                                                                |
-tnoise*.                                                                              |
+| tnoise*.                                                                                                          |                                                                                                                        |
-| *
+| *                                                                                                                 |                                                                                                                        |
-tslope*     | Time window in seconds after initial P pick in which the slope of the onset is calculated.                                   |
+| 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                                                                                                                  |
+| Name                                                                                                              | Description                                                                                         |
-|---------------|------------------------------------------------------------------------------------------------------------------------------|
+|-------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------|
-| *
+| *                                                                                                                 |                                                                                                     |
-tdet1h*      | Length of time window in seconds in which AR params of the waveform are determined.                                          |
+| 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.                                      |
+| 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.                                                     |
+| 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.                          |
+| 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.                             |
+| checkwinS*                                                                                                        | Time in front of the global maximum of the ARH-CF in which to search for a second local extrema.    |
-| *minfactorP*  | Used with *
+| *minfactorP*                                                                                                      | Used with *                                                                                         |
-checkwinS*. If a second local maximum is found, it has to be at least as big as the first maximum * *minfactorS*. |
+| 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.                                       |
+| 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.                                      |
+| tnoise*                                                                                                           | Time window in seconds in front of initial P pick used for determining noise amplitude.             |
-| *tsafetey*    | Time in seconds between *tsignal* and *
+| *tsafetey*                                                                                                        | Time in seconds between *tsignal* and *                                                             |
-tnoise*.                                                                              |
+| tnoise*.                                                                                                          |                                                                                                     |
-| *
+| *                                                                                                                 |                                                                                                     |
-tslope*      | Time window in seconds after initial P pick in which the slope of the onset is calculated.                                   |
+| 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                                                                                                                                                                                                             |
+| Name                                                                                | Description                                                                                                                                                                                                      |
-|--------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+|-------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| *Precalcwin* | Time window in seconds for recalculation of the HOS-CF. The new CF will be two times the size of *
+| *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*.                                   |
+| 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.                                                                                                                                    |
+| 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*                                                                               | 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*). |
+| ausP*).                                                                             |                                                                                                                                                                                                                  |
 
 ## Precise S pick
 
 Parameters used for determination of precise S pick.
 
-| Name         | Description                                                                                                                                                                                                             |
+| Name         | Description                                                                                                                                                                                                      |
-|--------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+|--------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| *
+| *            |                                                                                                                                                                                                                  |
-tdet2h*     | Time window for determination of AR coefficients.                                                                                                                                                                       |
+| tdet2h*      | Time window for determination of AR coefficients.                                                                                                                                                                |
-| *
+| *            |                                                                                                                                                                                                                  |
-tpred2h*    | Time window in which the waveform is predicted using the determined AR parameters.                                                                                                                                      |
+| 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* | Time window for recalculation of ARH-CF. New CF will be calculated from initial pick +/- *                                                                                                                       |
-Srecalcwin*.                                                                                                                  |
+| Srecalcwin*. |                                                                                                                                                                                                                  |
-| *
+| *            |                                                                                                                                                                                                                  |
-tsmoothS*   | Average of samples in this time window will be used for smoothing the second ARH-CF.                                                                                                                                    |
+| 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*        | 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*). |
+| ausS*).      |                                                                                                                                                                                                                  |
-| *
+| *            |                                                                                                                                                                                                                  |
-pickwinS*   | Time window around initial pick in which to look for a precise pick.                                                                                                                                                    |
+| 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                                                                                                                                                                                                                                                                    |
+| Name                                       | Description                                                           |
-|--------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+|--------------------------------------------|-----------------------------------------------------------------------|
-| *
+| *                                          |                                                                       |
-minAICPslope*                             | Initial P picks with a slope lower than this value will be discared.                                                                                                                                                                                                           |
+| 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.                                                                                                                                                                                                                 |
+| 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.                                                                                                                                                                                                          |
+| 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.                                                                                                                                                                                                                 |
+| 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*, *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.                                                                                                        |
 | *
@@ -139,12 +140,12 @@ wdttolerance*                             | Maximum allowed deviation of S onset
 
 Parameters for discrete quality classes.
 
-| Name             | Description                                                                                                                                                                                                           |
+| 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.                                                                           |
+| 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.                                                                           |
+| 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 *
+| *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. |
+| nfac* * mean value of the RMS amplitude in the time window *tnoise* corresponds to the latest possible onset time. |                                                                                                                                             |
 

pylot/core/io/data.py

@@ -36,8 +36,17 @@ class Data(object):
     loaded event. Container object holding, e.g. phase arrivals, etc.
     """
 
-    def __init__(self, parent=None, evtdata=None):
+    def __init__(self, parent=None, evtdata=None, picking_parameter=None):
         self._parent = parent
+
+        if not picking_parameter:
+            if hasattr(parent, '_inputs'):
+                picking_parameter = parent._inputs
+            else:
+                logging.warning('No picking parameters found! Using default input parameters!!!')
+                picking_parameter = PylotParameter()
+        self.picking_parameter = picking_parameter
+
         if self.getParent():
             self.comp = parent.getComponent()
         else:
@@ -403,23 +412,19 @@ class Data(object):
                                      not implemented: {1}'''.format(evtformat, e))
             if fnext == '.cnv':
                 try:
-                    velest.export(picks_copy, fnout + fnext, eventinfo=self.get_evt_data())
+                    velest.export(picks_copy, fnout + fnext, self.picking_parameter, eventinfo=self.get_evt_data())
                 except KeyError as e:
                     raise KeyError('''{0} export format
                                      not implemented: {1}'''.format(evtformat, e))
             if fnext == '_focmec.in':
                 try:
-                    parameter = PylotParameter()
+                    focmec.export(picks_copy, fnout + fnext, self.picking_parameter, eventinfo=self.get_evt_data())
-                    logging.warning('Using default input parameter')
-                    focmec.export(picks_copy, fnout + fnext, parameter, eventinfo=self.get_evt_data())
                 except KeyError as e:
                     raise KeyError('''{0} export format
                                      not implemented: {1}'''.format(evtformat, e))
             if fnext == '.pha':
                 try:
-                    parameter = PylotParameter()
+                    hypodd.export(picks_copy, fnout + fnext, self.picking_parameter, eventinfo=self.get_evt_data())
-                    logging.warning('Using default input parameter')
-                    hypodd.export(picks_copy, fnout + fnext, parameter, eventinfo=self.get_evt_data())
                 except KeyError as e:
                     raise KeyError('''{0} export format
                                      not implemented: {1}'''.format(evtformat, e))

pylot/core/io/inputs.py

@@ -53,10 +53,16 @@ class PylotParameter(object):
         self.__parameter = {}
         self._verbosity = verbosity
         self._parFileCont = {}
+
         # io from parsed arguments alternatively
         for key, val in kwargs.items():
             self._parFileCont[key] = val
         self.from_file()
+
+        # if no filename or kwargs given, use default values
+        if not fnin and not kwargs:
+            self.reset_defaults()
+
         if fnout:
             self.export2File(fnout)
 

pylot/core/io/phases.py

@@ -278,7 +278,6 @@ def picksdict_from_picks(evt, parameter=None):
         weight = phase.get('weight')
         if not weight:
             if not parameter:
-                logging.warning('Using ')
                 logging.warning('Using default input parameter')
                 parameter = PylotParameter()
             pick.phase_hint = identifyPhase(pick.phase_hint)
@@ -513,7 +512,7 @@ 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('datapath'), parameter.get('eventID')))
-        arrivals = chooseArrivals(arrivals)  # MP MP what is chooseArrivals? It is not defined anywhere
+        arrivals = chooseArrivals(arrivals)
         for key in arrivals:
             # P onsets
             if 'P' in arrivals[key]:
@@ -666,7 +665,7 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
         fid = open("%s" % filename, 'w')
         # write header
         fid.write('%s, event %s \n' % (parameter.get('datapath'), parameter.get('eventID')))
-        arrivals = chooseArrivals(arrivals)  # MP MP what is chooseArrivals? It is not defined anywhere
+        arrivals = chooseArrivals(arrivals)
         for key in arrivals:
             # P onsets
             if 'P' in  arrivals[key] and arrivals[key]['P']['mpp'] is not None:
@@ -757,11 +756,11 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
             cns, eventsource['longitude'], cew, eventsource['depth'], eventinfo.magnitudes[0]['mag'], ifx))
         n = 0
         # check whether arrivals are dictionaries (autoPyLoT) or pick object (PyLoT)
-        if isinstance(arrivals, dict) == False:
+        if isinstance(arrivals, dict) is False:
             # convert pick object (PyLoT) into dictionary
             evt = ope.Event(resource_id=eventinfo['resource_id'])
             evt.picks = arrivals
-            arrivals = picksdict_from_picks(evt)
+            arrivals = picksdict_from_picks(evt, parameter=parameter)
         # check for automatic and manual picks
         # prefer manual picks
         usedarrivals = chooseArrivals(arrivals)
@@ -822,7 +821,7 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
             # convert pick object (PyLoT) into dictionary
             evt = ope.Event(resource_id=eventinfo['resource_id'])
             evt.picks = arrivals
-            arrivals = picksdict_from_picks(evt)
+            arrivals = picksdict_from_picks(evt, parameter=parameter)
         # check for automatic and manual picks
         # prefer manual picks
         usedarrivals = chooseArrivals(arrivals)
@@ -873,7 +872,7 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
             # convert pick object (PyLoT) into dictionary
             evt = ope.Event(resource_id=eventinfo['resource_id'])
             evt.picks = arrivals
-            arrivals = picksdict_from_picks(evt)
+            arrivals = picksdict_from_picks(evt, parameter=parameter)
         # check for automatic and manual picks
         # prefer manual picks
         usedarrivals = chooseArrivals(arrivals)

pylot/core/util/array_map.py

@@ -134,8 +134,8 @@ class Array_map(QtWidgets.QWidget):
         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 viridis as default
+        # try to set to plasma as default
-        self.cmaps_box.setCurrentIndex(self.cmaps_box.findText('viridis'))
+        self.cmaps_box.setCurrentIndex(self.cmaps_box.findText('plasma'))
 
         self.top_row.addWidget(QtWidgets.QLabel('Select a phase: '))
         self.top_row.addWidget(self.comboBox_phase)

pylot/core/util/dataprocessing.py

@@ -59,6 +59,8 @@ class Metadata(object):
         :type path_to_inventory: str
         :return: None
         """
+        path_to_inventory = path_to_inventory.replace('\\', '/')
+        path_to_inventory = os.path.abspath(path_to_inventory)
         assert (os.path.isdir(path_to_inventory)), '{} is no directory'.format(path_to_inventory)
         if path_to_inventory not in self.inventories:
             self.inventories.append(path_to_inventory)
@@ -218,9 +220,9 @@ class Metadata(object):
                     network_name = network.code
                     if not station_name in self.stations_dict.keys():
                         st_id = '{}.{}'.format(network_name, station_name)
-                        self.stations_dict[st_id] = {'latitude': station[0].latitude,
+                        self.stations_dict[st_id] = {'latitude': station.latitude,
-                                                     'longitude': station[0].longitude,
+                                                     'longitude': station.longitude,
-                                                     'elevation': station[0].elevation}
+                                                     'elevation': station.elevation}
 
         read_stat = {'xml': stat_info_from_inventory,
                      'dless': stat_info_from_parser}
@@ -266,9 +268,6 @@ class Metadata(object):
         if not fnames:
             # search for station name in filename
             fnames = glob.glob(os.path.join(path_to_inventory, '*' + station + '*'))
-        if not fnames:
-            # search for network name in filename
-            fnames = glob.glob(os.path.join(path_to_inventory, '*' + network + '*'))
         if not fnames:
             if self.verbosity:
                 print('Could not find filenames matching station name, network name or seed id')
@@ -280,7 +279,7 @@ class Metadata(object):
                     continue
             invtype, robj = self._read_metadata_file(os.path.join(path_to_inventory, fname))
             try:
-                # robj.get_coordinates(station_seed_id)  # TODO: Commented out, failed with Parser, is this needed?
+                robj.get_coordinates(station_seed_id)
                 self.inventory_files[fname] = {'invtype': invtype,
                                                'data': robj}
                 if station_seed_id in self.seed_ids.keys():
@@ -288,6 +287,7 @@ class Metadata(object):
                 self.seed_ids[station_seed_id] = fname
                 return True
             except Exception as e:
+                logging.warning(e)
                 continue
         print('Could not find metadata for station_seed_id {} in path {}'.format(station_seed_id, path_to_inventory))
 
@@ -652,6 +652,8 @@ def restitute_data(data, metadata, unit='VEL', force=False, ncores=0):
     """
 
     # data = remove_underscores(data)
+    if not data:
+        return
 
     # loop over traces
     input_tuples = []
@@ -659,9 +661,14 @@ def restitute_data(data, metadata, unit='VEL', force=False, ncores=0):
         input_tuples.append((tr, metadata, unit, force))
         data.remove(tr)
 
-    pool = gen_Pool(ncores)
+    if ncores == 0:
-    result = pool.imap_unordered(restitute_trace, input_tuples)
+        result = []
-    pool.close()
+        for input_tuple in input_tuples:
+            result.append(restitute_trace(input_tuple))
+    else:
+        pool = gen_Pool(ncores)
+        result = pool.imap_unordered(restitute_trace, input_tuples)
+        pool.close()
 
     for tr, remove_trace in result:
         if not remove_trace:

pylot/core/util/gui.py

@@ -1,6 +1,7 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 import os
+from functools import lru_cache
 
 try:
     import pyqtgraph as pg
@@ -25,14 +26,14 @@ def pick_linestyle_pg(picktype, key):
     :return: Qt line style parameters
     :rtype:
     """
-    linestyles_manu = {'mpp': (QtCore.Qt.SolidLine, 2.),
+    linestyles_manu = {'mpp': (QtCore.Qt.SolidLine, 2),
-                       'epp': (QtCore.Qt.DashLine, 1.),
+                       'epp': (QtCore.Qt.DashLine, 1),
-                       'lpp': (QtCore.Qt.DashLine, 1.),
+                       'lpp': (QtCore.Qt.DashLine, 1),
-                       'spe': (QtCore.Qt.DashLine, 1.)}
+                       'spe': (QtCore.Qt.DashLine, 1)}
-    linestyles_auto = {'mpp': (QtCore.Qt.DotLine, 2.),
+    linestyles_auto = {'mpp': (QtCore.Qt.DotLine, 2),
-                       'epp': (QtCore.Qt.DashDotLine, 1.),
+                       'epp': (QtCore.Qt.DashDotLine, 1),
-                       'lpp': (QtCore.Qt.DashDotLine, 1.),
+                       'lpp': (QtCore.Qt.DashDotLine, 1),
-                       'spe': (QtCore.Qt.DashDotLine, 1.)}
+                       'spe': (QtCore.Qt.DashDotLine, 1)}
     linestyles = {'manual': linestyles_manu,
                   'auto': linestyles_auto}
     return linestyles[picktype][key]
@@ -80,6 +81,7 @@ def which(program, parameter):
     return None
 
 
+@lru_cache(maxsize=128)
 def make_pen(picktype, phase, key, quality):
     """
     Make  PyQtGraph.QPen

pylot/core/util/utils.py

@@ -51,7 +51,6 @@ def readDefaultFilterInformation():
     :rtype: dict
     """
     pparam = PylotParameter()
-    pparam.reset_defaults()
     return readFilterInformation(pparam)
 
 

pylot/correlation/parameters_adriaarray.yaml

@@ -9,7 +9,7 @@
 # initial_pick_outlier_threshold: (hopefully) threshold for excluding large outliers of initial (AIC) picks
 # export_threshold: automatically exclude all onsets which deviate more than this threshold from corrected taup onsets
 # min_picks_export: minimum number of correlated picks for export
-# min_picks_autopylot: minimum number of reference autopicks picks to continue with event
+# min_picks_autopylot: minimum number of reference auto picks to continue with event
 # check_RMS: do RMS check to search for restitution errors (very experimental)
 # use_taupy_onsets: use taupy onsets as reference picks instead of external picks
 # station_list: use the following stations as reference for stacking
@@ -17,6 +17,11 @@
 # data_dir: obspyDMT data subdirectory (e.g. 'raw', 'processed')
 # pickfile_extension: use quakeML files (PyLoT output) with the following extension, e.g. '_autopylot' for pickfiles
 #                     such as 'PyLoT_20170501_141822_autopylot.xml'
+# dt_stacking: time shift for stacking (e.g. [0, 250] for 0 and 250 seconds shift)
+# filter_options: filter for first correlation (rough)
+# filter_options_final: filter for second correlation (fine)
+# filter_type: e.g. 'bandpass'
+# sampfreq: sampling frequency of the data
 
 logging: info
 pick_phases: ['P', 'S']
@@ -54,6 +59,9 @@ P:
   filter_type: bandpass
   sampfreq: 20.0
 
+  # ignore if autopylot fails to pick master-trace (not recommended if absolute onset times matter)
+  ignore_autopylot_fail_on_master: True
+
 # S-phase
 S:
   min_corr_stacking: 0.7
@@ -88,3 +96,6 @@ S:
   filter_type: bandpass
   sampfreq: 20.0
 
+  # ignore if autopylot fails to pick master-trace (not recommended if absolute onset times matter)
+  ignore_autopylot_fail_on_master: True
+

pylot/correlation/pick_correlation_correction.py

@@ -436,6 +436,7 @@ def correlation_main(database_path_dmt: str, pylot_infile_path: str, params: dic
 
     # iterate over all events in "database_path_dmt"
     for eventindex, eventdir in enumerate(eventdirs):
+        eventindex += 1
         if not istart <= eventindex < istop:
             continue
 
@@ -443,12 +444,16 @@ def correlation_main(database_path_dmt: str, pylot_infile_path: str, params: dic
             continue
 
         logging.info('\n' + 100 * '#')
-        logging.info('Working on event {} ({}/{})'.format(eventdir, eventindex + 1, len(eventdirs)))
+        logging.info('Working on event {} ({}/{})'.format(eventdir, eventindex, len(eventdirs)))
         if event_blacklist and get_event_id(eventdir) in event_blacklist:
             logging.info('Event on blacklist. Continue')
 
-        correlate_event(eventdir, pylot_parameter, params=params, channel_config=channel_config,
+        try:
-                        update=update)
+            correlate_event(eventdir, pylot_parameter, params=params, channel_config=channel_config,
+                            update=update)
+        except Exception as e:
+            logging.error(f'Could not correlate event {eventindex}: {e}')
+            continue
 
     logging.info('Finished script after {} at {}'.format(datetime.now() - tstart, datetime.now()))
 
@@ -522,7 +527,7 @@ def cut_stream_to_same_length(wfdata: Stream) -> None:
         st.trim(tstart, tend, pad=True, fill_value=0.)
         # check for stream length
         if len(st) < 3:
-            logging.info('Not enough traces in stream, remove it from dataset:', str(st))
+            logging.info(f'Not enough traces in stream, remove it from dataset: {st}')
             remove(wfdata, st)
             continue
         if st[0].stats.starttime != st[1].stats.starttime or st[1].stats.starttime != st[2].stats.starttime:
@@ -635,10 +640,19 @@ def correlate_event(eventdir: str, pylot_parameter: PylotParameter, params: dict
             if len(picks) < params[phase_type]['min_picks_autopylot']:
                 logging.info('Not enough automatic picks for correlation. Continue!')
                 continue
-            # calculate corrected taupy picks and remove strong outliers
+            ## calculate corrected taupy picks and remove strong outliers - part commented out for now. Maybe make this
-            taupypicks_corr_initial, median_diff = get_corrected_taupy_picks(picks, taupypicks_orig)
+            ## another option but I think it is not worth it
-            picks = remove_outliers(picks, taupypicks_corr_initial,
+            # taupypicks_corr_initial, median_diff = get_corrected_taupy_picks(picks, taupypicks_orig)
-                                    params[phase_type]['initial_pick_outlier_threshold'])
+            # picks = remove_outliers(picks, taupypicks_corr_initial,
+            #                        params[phase_type]['initial_pick_outlier_threshold'])
+
+            # use mean/median corrected picks from taupy as the new reference picks. This largely increases the yield
+            # of final picks since every station has a decent reference onset now for a correlation
+            taupypicks, time_shift = get_corrected_taupy_picks(picks, taupypicks_orig, all_available=True)
+
+            picks = copy.deepcopy(taupypicks)
+            for pick in picks:
+                pick.method_id.id = 'auto'
 
         if phase_type == 'S':
             # check whether rotation to ZNE is possible (to get rid of horizontal channel 1,2,3)
@@ -671,19 +685,56 @@ def correlate_event(eventdir: str, pylot_parameter: PylotParameter, params: dict
         if not params[phase_type]['use_stacked_trace']:
             # first stack mastertrace by using stations with high correlation on that station in station list with the
             # highest correlation coefficient
-            stack_result = stack_mastertrace(wfdata_lowf, wfdata_highf, wfdata, picks, params=params[phase_type],
+            logging.info('Searching for master trace. ' + 20 * '-')
-                                             channels=channels_list, method=method, fig_dir=fig_dir)
+            best_result = None
-        else:
+            for stack_result in stack_mastertrace(wfdata_lowf, wfdata_highf, wfdata, picks, params=params[phase_type],
-            stack_result = load_stacked_trace(eventdir, params[phase_type]['min_corr_stacking'])
+                                                  channels=channels_list, method=method, fig_dir=fig_dir):
+
+                if not stack_result:
+                    continue
+
+                # save best result in case it is still needed
+                if not best_result:
+                    best_result = stack_result
+
+                # extract stack result
+                correlations_dict, nwst_id, trace_master, nstack = stack_result
+
+                # now pick stacked trace with PyLoT for a more precise pick (use raw trace, gets filtered by autoPyLoT)
+                pick_stacked = repick_master_trace(wfdata_lowf, trace_master, pylot_parameter, event, event_id, metadata,
+                                                   phase_type, correlation_out_dir)
+
+                if not pick_stacked or not pick_stacked.time_errors.uncertainty:
+                    logging.info(f'Invalid autoPyLoT pick on master trace. Try next one.')
+                    continue
+                else:
+                    break
+
+            else:
+                logging.info('Did not find autoPyLoT pick for any stacked trace.')
+
+                if params[phase_type]['ignore_autopylot_fail_on_master'] is True:
+                    # Fallback in case autopylot failed
+                    logging.warning(f'Could not pick stacked trace. Using reference pick instead. If you need '
+                                    f'absolute onsets you need to account for a time-shift.')
+
+                    correlations_dict, nwst_id, trace_master, nstack = best_result
+                    pick_stacked = get_pick4station(picks, network_code=trace_master.stats.network,
+                                                    station_code=trace_master.stats.station, method='auto')
+                else:
+                    pick_stacked = None
+
+                if not pick_stacked:
+                    logging.info('Could not find reference pick also. Continue with next phase.')
+                    continue
+
+        else:
+            raise NotImplementedError('Loading stacked trace currently not implemented')
+            # stack_result = load_stacked_trace(eventdir, params[phase_type]['min_corr_stacking'])
 
-        if not stack_result:
-            logging.info('No stack result. Continue.')
-            continue
 
         #############################################
         # NOW DO THE FINAL CORRELATION
-        # extract stack result
-        correlations_dict, nwst_id, trace_master, nstack = stack_result
 
         if params[phase_type]['plot']:
             # plot correlations of traces used to generate stacked trace
@@ -700,11 +751,6 @@ def correlate_event(eventdir: str, pylot_parameter: PylotParameter, params: dict
         # write unfiltered trace
         trace_master.write(os.path.join(correlation_out_dir, '{}_stacked.mseed'.format(trace_master.id)))
 
-        # now pick stacked trace with PyLoT for a more precise pick (use raw trace, gets filtered by autoPyLoT)
-        pick_stacked = repick_master_trace(wfdata_lowf, trace_master, pylot_parameter, event, event_id, metadata,
-                                           phase_type, correlation_out_dir)
-        if not pick_stacked:
-            continue
 
         # correlate stations with repicked and stacked master trace
         fig_dir_traces = make_figure_dirs(fig_dir, trace_master.id)
@@ -826,7 +872,7 @@ def get_picks_mean(picks: list) -> UTCDateTime:
 
 
 def get_corrected_taupy_picks(picks: list, taupypicks: list, all_available: bool = False) -> tuple:
-    """ get mean/median from picks taupy picks, correct latter for the difference """
+    """ get mean/median from picks relative to taupy picks, correct latter for the difference """
 
     def nwst_id_from_wfid(wfid):
         return '{}.{}'.format(wfid.network_code if wfid.network_code else '',
@@ -1165,38 +1211,38 @@ def stack_mastertrace(wfdata_lowf: Stream, wfdata_highf: Stream, wfdata_raw: Str
     A master trace will be created by stacking well correlating traces onto this station.
     """
 
-    def get_best_station4stack(sta_result):
+    def get_best_stations4stack(sta_result, n_max=4):
-        """ return station with maximum mean_ccc"""
+        """ return stations sorted after maximum mean_ccc"""
         ccc_means = {nwst_id: value['mean_ccc'] for nwst_id, value in sta_result.items() if
                      not np.isnan(value['mean_ccc'])}
         if len(ccc_means) < 1:
             logging.warning('No valid station found for stacking! Return.')
             return
-        best_station_id = max(ccc_means, key=ccc_means.get)
+        best_station_ids = sorted(ccc_means, key=ccc_means.get, reverse=True)[:n_max]
-        logging.info(
+        logging.info(f'Found mean correlations for stations: {ccc_means}')
-            'Found highest mean correlation for station {} ({})'.format(best_station_id, max(ccc_means.values())))
+        return best_station_ids, ccc_means
-        return best_station_id
 
     station_results = iterate_correlation(wfdata_lowf, wfdata_highf, channels, picks, method, params, fig_dir=fig_dir)
-    nwst_id_master = get_best_station4stack(station_results)
+    nwst_ids_master, ccc_means = get_best_stations4stack(station_results)
 
     # in case no stream with a valid pick is found
-    if not nwst_id_master:
+    if not nwst_ids_master:
-        logging.info('No mastertrace found! Will skip this event.')
+        logging.info('No mastertrace found! Continue with next.')
         return None
 
-    trace_master = station_results[nwst_id_master]['trace']
+    for nwst_id_master in nwst_ids_master:
-    stations4stack = station_results[nwst_id_master]['stations4stack']
+        trace_master = station_results[nwst_id_master]['trace']
-    correlations_dict = station_results[nwst_id_master]['correlations_dict']
+        stations4stack = station_results[nwst_id_master]['stations4stack']
+        correlations_dict = station_results[nwst_id_master]['correlations_dict']
 
-    wfdata_highf += trace_master
+        wfdata_highf += trace_master
 
-    dt_pre, dt_post = params['dt_stacking']
+        dt_pre, dt_post = params['dt_stacking']
-    trace_master, nstack = apply_stacking(trace_master, stations4stack, wfdata_raw, picks, method=method,
+        trace_master, nstack = apply_stacking(trace_master, stations4stack, wfdata_raw, picks, method=method,
-                                          do_rms_check=params['check_RMS'], plot=params['plot'], fig_dir=fig_dir,
+                                              do_rms_check=params['check_RMS'], plot=params['plot'], fig_dir=fig_dir,
-                                          dt_pre=dt_pre, dt_post=dt_post)
+                                              dt_pre=dt_pre, dt_post=dt_post)
 
-    return correlations_dict, nwst_id_master, trace_master, nstack
+        yield correlations_dict, nwst_id_master, trace_master, nstack
 
 
 def iterate_correlation(wfdata_lowf: Stream, wfdata_highf: Stream, channels: list, picks: list, method: str,
@@ -1984,4 +2030,5 @@ if __name__ == "__main__":
     # MAIN +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
     correlation_main(ARGS.dmt_path, ARGS.pylot_infile, params=CORR_PARAMS, istart=int(ARGS.istart),
                      istop=int(ARGS.istop),
-                     channel_config=CHANNELS, update=ARGS.update, event_blacklist=ARGS.blacklist)
+                     channel_config=CHANNELS, update=ARGS.update, event_blacklist=ARGS.blacklist,
+                     select_events=None) # can add a list of event ids if only specific events shall be picked

pylot/correlation/submit_pick_corr_correction.sh

@@ -32,9 +32,10 @@ export PYTHONPATH="$PYTHONPATH:/home/marcel/git/pylot/"
 #python pick_correlation_correction.py '/data/AlpArray_Data/dmt_database_mantle_M5.8-6.0' '/home/marcel/.pylot/pylot_alparray_mantle_corr_stack_0.03-0.5.in' -pd -n ${NSLOTS:=1} -istart 100 -istop 200
 #python pick_correlation_correction.py 'H:\sciebo\dmt_database' 'H:\Sciebo\dmt_database\pylot_alparray_mantle_corr_S_0.01-0.2.in' -pd -n 4 -t
 
-pylot_infile='/home/marcel/.pylot/pylot_alparray_syn_fwi_mk6_it3.in'
+#pylot_infile='/home/marcel/.pylot/pylot_alparray_syn_fwi_mk6_it3.in'
-#pylot_infile='/home/marcel/.pylot/pylot_adriaarray_corr_P_and_S.in'
+pylot_infile='/home/marcel/.pylot/pylot_adriaarray_corr_P_and_S.in'
 
 # THIS SCRIPT SHOLD BE CALLED BY "submit_to_grid_engine.py" using the following line:
-python pick_correlation_correction.py $1 $pylot_infile -pd -n ${NSLOTS:=1} -istart $2 --params 'parameters_fwi_mk6_it3.yaml'
+# use -pd for detailed plots in eventdir/correlation_XX_XX/figures
+python pick_correlation_correction.py $1 $pylot_infile -n ${NSLOTS:=1} -istart $2 --params 'parameters_adriaarray.yaml' # -pd
 #--event_blacklist eventlist.txt

pylot/correlation/submit_to_grid_engine.py

@@ -3,21 +3,26 @@
 import subprocess
 
 fnames = [
-    ('/data/AlpArray_Data/dmt_database_synth_model_mk6_it3_no_rotation', 0),
+    ('/data/AdriaArray_Data/dmt_database_mantle_M5.0-5.4', 0),
+    ('/data/AdriaArray_Data/dmt_database_mantle_M5.4-5.7', 0),
+    ('/data/AdriaArray_Data/dmt_database_mantle_M5.7-6.0', 0),
+    ('/data/AdriaArray_Data/dmt_database_mantle_M6.0-6.3', 0),
+    ('/data/AdriaArray_Data/dmt_database_mantle_M6.3-10.0', 0),
+    # ('/data/AdriaArray_Data/dmt_database_ISC_mantle_M5.0-5.4', 0),
+    # ('/data/AdriaArray_Data/dmt_database_ISC_mantle_M5.4-5.7', 0),
+    # ('/data/AdriaArray_Data/dmt_database_ISC_mantle_M5.7-6.0', 0),
+    # ('/data/AdriaArray_Data/dmt_database_ISC_mantle_M6.0-10.0', 0),
           ]
 
 #fnames = [('/data/AlpArray_Data/dmt_database_mantle_0.01-0.2_SKS-phase', 0),
 #          ('/data/AlpArray_Data/dmt_database_mantle_0.01-0.2_S-phase', 0),]
 
 ####
-script_location = '/home/marcel/VersionCtrl/git/code_base/correlation_picker/submit_pick_corr_correction.sh'
+script_location = '/home/marcel/VersionCtrl/git/pylot/pylot/correlation/submit_pick_corr_correction.sh'
 ####
 
 for fnin, istart in fnames:
     input_cmds = f'qsub -q low.q@minos15,low.q@minos14,low.q@minos13,low.q@minos12,low.q@minos11 {script_location} {fnin} {istart}'
 
     print(input_cmds)
-    print(subprocess.check_output(input_cmds.split()))
+    print(subprocess.check_output(input_cmds.split()))
-
-
-