ISEPOS-2360 Move spectral parameter source code from apps_to_migrate from official-apps-artifact-builder

src/SpectralAnalysisApp.py

@@ -0,0 +1,162 @@
+from obspy import read, read_events, read_inventory
+
+from SpectralAnalysis import SpectralAnalysis
+from base_logger import getDefaultLogger
+
+
+def count_matching_stations(stream, inventory):
+    """
+    Count how many stations from the given stream are present in the inventory.
+
+    Parameters:
+    - stream: ObsPy Stream object containing seismic data.
+    - inventory: ObsPy Inventory object containing network and station metadata.
+
+    Returns:
+    - count: Number of stations from the stream found in the inventory.
+    """
+    # Extract unique station codes from the stream
+    stream_stations = set([trace.stats.station for trace in stream])
+
+    # Extract unique station codes from the inventory
+    inventory_stations = set([station.code for network in inventory for station in network.stations])
+
+    # Count how many stations from the stream are in the inventory
+    count = len(stream_stations.intersection(inventory_stations))
+
+    return count, len(stream_stations)
+
+def filter_stream_by_picks(st, qml):
+    """
+    Select from stream only traces that have an associated pick.
+
+    Parameters:
+    - st: ObsPy Stream object containing seismic data.
+    - qml: ObsPy Catalog object containing phase picks.
+
+    Returns:
+    - st2: ObsPy Stream object containing seismic data.
+    """
+    st2 = read().clear() #create blank stream object
+
+    for pick in qml.picks:
+        net = pick.waveform_id.network_code
+        sta = pick.waveform_id.station_code
+        loc = pick.waveform_id.location_code
+        cha = pick.waveform_id.channel_code[:2] + "*" #wildcard to obtain all 3 components
+        NSLC = net + '.' + sta + '.' + loc + '.' + cha
+        st2 = st2 + st.select(id=NSLC) #add trace to new stream
+
+    st2.merge() #remove duplicate traces
+    return st2
+
+
+def main(waveforms, network_inventory, picks_qml, event_latitude, event_longitude, event_depth, vp, vs, density, taper_type, taper_len,
+         window_len, freq_min, freq_max, min_sn_ratio=1, min_energy_ratio=1, p_wave_analysis=True, s_wave_analysis=True,
+         raytracing=True, allow_station_elevations=False,
+         source_model="Madariaga", sp_fit_model="FBoatwright", norm="L2", z_threshold=6,
+         q_min=1, q_max=400, velocity_model=None):
+    """
+    Main function for application: SPECTRALPARAMETERS
+    Arguments:
+        waveforms: path to input file of type 'seismogram'
+        Velocity model: path to input file of type 'velocity_model'
+        network_inventory: path to input file of type 'inventory'
+        event_qml: path to input file of type 'quakeml_seismogram_picks'
+        raytracing: parameter of type 'BOOLEAN'
+        save plots: parameter of type 'BOOLEAN'
+    Returns:
+        File(s) named 'Katalog sejsmiczny' of type 'quakeml_seismogram_picks' and format 'XML' from working directory
+        :param event_qml:
+    """
+
+    logger = getDefaultLogger(__name__)
+
+    config = {
+        # filenames
+        "P_WAVE_SP_FITTING_RESULTS_JSON": "P_wave_analysis_sp_fit_solutions.json",
+        "S_WAVE_SP_FITTING_RESULTS_JSON": "S_wave_analysis_sp_fit_solutions.json",
+        "P_WAVE_JK_RESULTS": "P_wave_analysis_JK_solutions.csv",
+        "S_WAVE_JK_RESULTS": "S_wave_analysis_JK_solutions.csv",
+        "P_WAVE_SP_FITTING_RESULTS": "P_wave_analysis_sp_fit_solutions.csv",
+        "S_WAVE_SP_FITTING_RESULTS": "S_wave_analysis_sp_fit_solutions.csv",
+        "EVENT_RESULTS": "results.csv",
+        "velocity_mat_file": velocity_model,
+        # app options
+        "P_wave_analysis": p_wave_analysis,
+        "S_wave_analysis": s_wave_analysis,
+        "raytrace": raytracing,
+        "allow_station_elev": allow_station_elevations,
+
+        #event location
+        "longitude": event_longitude,
+        "latitude": event_latitude,
+        "depth": event_depth, # in meters
+
+        # phase hints
+        "p_phase_hint": ["P", "Pg"],
+        "s_phase_hint": ["S", "Sg"],
+
+        # source parameters
+        "vp": vp,
+        "vs": vs,
+        "density": density,
+
+        # window parameters
+        "taper_len": taper_len,
+        "window_len": window_len,
+        "taper_type": taper_type,
+        # filter parameters
+        "freq_min": freq_min,
+        "freq_max": freq_max,
+        # frequency signal-to-noise ratio
+        "min_sn_ratio": min_sn_ratio,
+        # if station signal-to-noise ratio
+        "min_energy_ratio": min_energy_ratio,
+
+        # L1 / L2
+        "norm": norm,
+        # Spectrum fitting model: FBrune / FBoatwright
+        "sp_fit_model": sp_fit_model,
+        # Source model: Madariaga / Brune
+        "sp_source_model": source_model,
+
+        # outliers detection
+        "z_threshold": z_threshold,
+
+        # q - damping limits
+        "q_min": q_min,
+        "q_max": q_max,
+
+    }
+
+    # reading files
+    stream = read(waveforms)
+    inv = read_inventory(network_inventory)
+
+    qml = read_events(picks_qml).events[0]
+
+    if not stream:
+        msg = "MSEED file is empty"
+        logger.error(msg)
+        raise Exception(msg)
+    if not inv or len(inv) == 0:
+        msg = "Inventory file is empty"
+        logger.error(msg)
+        raise Exception(msg)
+    else:
+        stream = filter_stream_by_picks(stream, qml)
+        if len(stream) == 0:
+            msg = "No waveform data was found corresponding to the provided picks"
+            logger.error(msg)
+            raise Exception(msg)
+        else:
+            count, total = count_matching_stations(stream, inv)
+            logger.info(f"{count} out of {total} stations in stream are in the inventory")
+            if count == 0:
+                msg = "No stations from MSEED in the Network Inventory"
+                logger.error(msg)
+                raise Exception(msg)
+            else:
+                sa = SpectralAnalysis(stream=stream, event=qml, inventory=inv, config=config, logger=logger)
+                sa.run()