official-apps/SeismicHazardForecasting
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impose requirement of minimum size of range of output data to do image processing

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ftong
2025-09-10 16:33:11 +02:00
parent 5a1f43d6cd
commit 00bd39a098
1 changed files with 5 additions and 4 deletions
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src/seismic_hazard_forecasting.py
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@@ -519,8 +519,8 @@ verbose: {verbose}")
dtype=np.float64) # this reduces values to 8 decimal places dtype=np.float64) # this reduces values to 8 decimal places
iml_grid_tmp = np.nan_to_num(iml_grid[j]) # change nans to zeroes iml_grid_tmp = np.nan_to_num(iml_grid[j]) # change nans to zeroes
# upscale the grid if there are at least 10 grid values # upscale the grid if there are at least 10 grid values with range greater than 0.1
if np.count_nonzero(iml_grid_tmp) >= 10: if np.count_nonzero(iml_grid_tmp) >= 10 and vmax-vmin > 0.1:
up_factor = 4 up_factor = 4
iml_grid_hd = resize(iml_grid_tmp, (up_factor * len(iml_grid_tmp), up_factor * len(iml_grid_tmp)), iml_grid_hd = resize(iml_grid_tmp, (up_factor * len(iml_grid_tmp), up_factor * len(iml_grid_tmp)),
mode='reflect', anti_aliasing=False) mode='reflect', anti_aliasing=False)
@@ -529,9 +529,10 @@ verbose: {verbose}")
iml_grid_hd[iml_grid_hd == 0.0] = np.nan # change zeroes back to nan iml_grid_hd[iml_grid_hd == 0.0] = np.nan # change zeroes back to nan
# trim edges so the grid is not so blocky #vmin_hd = min(x for x in iml_grid_hd.flatten() if not isnan(x))
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 = max(x for x in iml_grid_hd.flatten() if not isnan(x))
# trim edges so the grid is not so blocky
trim_thresh = vmin trim_thresh = vmin
iml_grid_hd[iml_grid_hd < trim_thresh] = np.nan iml_grid_hd[iml_grid_hd < trim_thresh] = np.nan