Update src/seismic_hazard_forecasting.py

src/seismic_hazard_forecasting.py

@@ -768,7 +768,7 @@ verbose: {verbose}")
                 imls = [dask.delayed(compute_IMT_exceedance)(rx_lat[i], rx_lon[i], distances[i].flatten(), fr, p, lambdas,
                                                             forecast_len, lambdas_perc, m_range, m_pdf, m_cdf, model,
                                                             log_level=logging.DEBUG, imt=imt, IMT_min=0.0, IMT_max=IMT_max, rx_label=i,
-                                                            rtol=0.1, use_cython=False) for i in iter]
+                                                            rtol=0.1, use_cython=True) for i in iter]
                 iml = dask.compute(*imls)
                 iml_grid_raw.append(list(iml))
 
@@ -838,10 +838,11 @@ verbose: {verbose}")
             iml_grid_prep = iml_grid_raw
 
         for j in range(0, len(products)):
-            vmin = min(x for x in iml_grid_prep[j] if x is not np.nan)
-            vmax = max(x for x in iml_grid_prep[j] if x is not np.nan)
-            iml_grid[j] = np.reshape(iml_grid_prep[j], (nx, ny)).astype(dtype=np.float64)  # this reduces values to 8 decimal places
-            iml_grid_tmp = np.nan_to_num(iml_grid[j])  # change nans to zeroes
+            vmin = np.nanmin(iml_grid_prep[j])
+            vmax = np.nanmax(iml_grid_prep[j])
+
+            #iml_grid[j] = np.reshape(iml_grid_prep[j], (nx, ny)).astype(dtype=np.float64)  # this reduces values to 8 decimal places
+            #iml_grid_tmp = np.nan_to_num(iml_grid[j])  # change nans to zeroes
 
             # upscale the grid, trim, and interpolate if there are at least 10 grid values with range greater than 0.1
             #if np.count_nonzero(iml_grid_tmp) >= 10 and vmax-vmin > 0.1:
@@ -851,13 +852,13 @@ verbose: {verbose}")
             #    trim_thresh = vmin
             #    iml_grid_hd[iml_grid_hd < trim_thresh] = np.nan
             #else:
-            iml_grid_hd = iml_grid_tmp
-
-            iml_grid_hd[iml_grid_hd == 0.0] = np.nan  # change zeroes back to nan
+            #iml_grid_hd = iml_grid_tmp
 
+            #iml_grid_hd[iml_grid_hd == 0.0] = np.nan  # change zeroes back to nan
 
+            iml_grid_hd = iml_grid_prep[j]   
             #vmin_hd = min(x for x in iml_grid_hd.flatten() if not isnan(x))
-            vmax_hd = max(x for x in iml_grid_hd.flatten() if not isnan(x))
+            vmax_hd = np.nanmax(iml_grid_hd.flatten())
 
             # generate image overlay
             north, south = lat.max(), lat.min()  # Latitude range