Update src/seismic_hazard_forecasting.py

src/seismic_hazard_forecasting.py

@@ -4,6 +4,27 @@
 def main(catalog_file, mc_file, pdf_file, m_file, m_select, mag_label, mc, m_max,
          m_kde_method, xy_select, grid_dim, xy_win_method, rate_select, time_win_duration,
          forecast_select, custom_rate, forecast_len, time_unit, model, products_string, verbose):
+    #catalog_file = 'LGCD_catalog_2024.mat'
+    mc_file = None
+    pdf_file = None
+    m_file = None
+    m_select = True
+    mag_label = 'Mw'
+    mc = 1.8
+    m_max = 4.5
+    m_kde_method = 'arviz-silverman'
+    xy_select = True
+    grid_dim = 5000
+    xy_win_method = False
+    rate_select = True
+    time_win_duration = 100
+    forecast_select = True
+    custom_rate = None
+    forecast_len = 100
+    time_unit = 'days'
+    model = 'Lasocki2013'
+    products_string = 'PGA'
+    verbose = True
     """
     Python application that reads an earthquake catalog and performs seismic hazard forecasting.
     Arguments:
@@ -69,6 +90,7 @@ def main(catalog_file, mc_file, pdf_file, m_file, m_select, mag_label, mc, m_max
     from matplotlib.contour import ContourSet
     import xml.etree.ElementTree as ET
     import json
+    import multiprocessing as mp
 
     logger = getDefaultLogger('igfash')
 
@@ -457,8 +479,9 @@ verbose: {verbose}")
         use_pp = True
 
         if use_pp:         # use dask parallel computing
-            pbar = ProgressBar()
+            mp.set_start_method("fork", force=True)
-            pbar.register()
+            #pbar = ProgressBar()
+            #pbar.register()
             # iter = range(0,len(distances))
             iter = indices
             iml_grid_raw = []  # raw ground motion grids