add check that m_max is not too large for the ground motion model

src/seismic_hazard_forecasting.py

@@ -45,20 +45,16 @@ def main(catalog_file, mc_file, pdf_file, m_file, m_select, mag_label, mc, m_max
     """
 
     import sys
+    from importlib.metadata import version
     import logging
     from base_logger import getDefaultLogger
     from timeit import default_timer as timer
     from math import ceil, floor, isnan
     import numpy as np
-    import scipy
-    import obspy
-    import dask
     from dask.diagnostics import ProgressBar  # use Dask progress bar
     import kalepy as kale
     import utm
     from skimage.transform import resize
-    import psutil
-    import openquake.engine
     import igfash
     from igfash.io import read_mat_cat, read_mat_m, read_mat_pdf, read_csv
     from igfash.window import win_CTL, win_CNE
@@ -105,28 +101,24 @@ verbose: {verbose}")
 
     # print key package version numbers
     logger.debug(f"Python version {sys.version}")
-    logger.debug(f"Numpy version {np.__version__}")
+    logger.debug(f"Numpy version {version('numpy')}")
-    logger.debug(f"Scipy version {scipy.__version__}")
+    logger.debug(f"Scipy version {version('scipy')}")
-    logger.debug(f"Obspy version {obspy.__version__}")
+    logger.debug(f"Obspy version {version('obspy')}")
-    logger.debug(f"Openquake version {openquake.engine.__version__}")
+    logger.debug(f"Openquake version {version('openquake.engine')}")
-    logger.debug(f"Igfash version {igfash.__version__}")
+    logger.debug(f"Igfash version {version('igfash')}")
-
+    logger.debug(f"Rbeast version {version('rbeast')}")
-    # print number of cpu cores available
+    logger.debug(f"Dask version {version('dask')}")
-    ncpu = psutil.cpu_count(logical=False)
-    logger.debug(f"Number of cpu cores available: {ncpu}")
-    for process in psutil.process_iter():
-        with process.oneshot():
-
-            # cpu = process.cpu_percent()
-            cpu = process.cpu_percent() / ncpu
-
-            if cpu > 1:
-                logger.debug(f"{process.name()}, {cpu}")
-
-    logger.debug(f"BASELINE CPU LOAD% {psutil.cpu_percent(interval=None, percpu=True)}")
 
     dask.config.set(scheduler='processes')
 
+    # validate m_max against the grond motion model if forecasting was selected
+    models_anthro_limited = ['Lasocki2013', 'Atkinson2015', 'ConvertitoEtAl2012Geysers'] # these models require that m_max<=4.5
+    if forecast_select:
+        if m_max > 4.5 and model in models_anthro_limited: 
+            msg = "Selected ground motion model only valid up to a maximum magnitude of 4.5. Please try again with a lower maximum magnitude."
+            logger.error(msg)
+            raise Exception(msg)
+
     # run magnitude distribution modeling if selected by user and no magnitude pdf file provided
     if m_select and m_range[0] == None and m_pdf[0] == None:
         logger.info("Magnitude distribution modeling selected")
@@ -166,9 +158,9 @@ verbose: {verbose}")
             lat = np.delete(lat, indices)
             lon = np.delete(lon, indices)
 
-        # if user does not provide a m_max, set m_max to 3 magnitude units above max magnitude in catalog
+        # if user does not provide a m_max, set m_max to 1 magnitude unit above max magnitude in catalog
         if m_max == None:
-            m_max = mag.max() + 3.0
+            m_max = mag.max() + 1.0
 
         start = timer()
 
@@ -365,7 +357,7 @@ verbose: {verbose}")
         act_rate, bin_counts, bin_edges, out, pprs, rt, idx, u_e = calc_bins(np.array(datenum_data), time_unit,
                                                                              time_win_duration, dates_calc,
                                                                              rate_forecast, rate_unc_high, rate_unc_low,
-                                                                             multiplicator, quiet=True)
+                                                                             multiplicator, quiet=True, figsize=(14,9))
 
         # Assign probabilities 
         lambdas, lambdas_perc = lambda_probs(act_rate, dates_calc, bin_edges)
@@ -426,7 +418,10 @@ verbose: {verbose}")
             rx_lat[i], rx_lon[i] = utm.to_latlon(x_rx[i], y_rx[i], utm_zone_number,
                                                  utm_zone_letter)  # get receiver location as lat,lon
 
-        # experimental - compute ground motion only at grid points that have minimum probability density of thresh_fxy
+        # convert distances from m to km because openquake ground motion models take input distances in kilometres
+        distances = distances/1000.0
+
+        # compute ground motion only at grid points that have minimum probability density of thresh_fxy
         if exclude_low_fxy:
             indices = list(np.where(fxy.flatten() > thresh_fxy)[0])
         else:
@@ -475,6 +470,11 @@ verbose: {verbose}")
         end = timer()
         logger.info(f"Ground motion exceedance computation time: {round(end - start, 1)} seconds")
 
+        if np.isnan(iml_grid_raw).all():
+            msg = "No valid ground motion intensity measures were forecasted. Try a different ground motion model."
+            logger.error(msg)
+            raise Exception(msg)
+
         # create list of one empty list for each imt
         iml_grid = [[] for _ in range(len(products))]  # final ground motion grids
         iml_grid_prep = iml_grid.copy()  # temp ground motion grids