official-apps/SeismicHazardForecasting
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Update src/seismic_hazard_forecasting.py

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ftong
2026-06-22 22:58:10 +02:00
parent 3d4f9138d7
commit 337457d49c
1 changed files with 10 additions and 11 deletions
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src/seismic_hazard_forecasting.py
+9 -10
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@@ -767,7 +767,7 @@ 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=True) for i in iter]
rtol=0.1, use_cython=False) for i in iter]
iml = dask.compute(*imls)
iml_grid_raw.append(list(iml))
@@ -837,18 +837,17 @@ verbose: {verbose}")
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[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:
up_factor = 1
iml_grid_hd = resize(iml_grid_tmp, (up_factor * len(iml_grid_tmp), up_factor * len(iml_grid_tmp)),
mode='reflect', anti_aliasing=False)
trim_thresh = vmin
iml_grid_hd[iml_grid_hd < trim_thresh] = np.nan
else:
#if np.count_nonzero(iml_grid_tmp) >= 10 and vmax-vmin > 0.1:
# up_factor = 1
# iml_grid_hd = resize(iml_grid_tmp, (up_factor * len(iml_grid_tmp), up_factor * len(iml_grid_tmp)),
# mode='reflect', anti_aliasing=False)
# 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