clean Combine.py add orientat computation from wcs
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@@ -258,7 +258,7 @@ def bkg_fit(data, error, mask, headers, subtract_error=True, display=False, save
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n_error_array[i] = np.sqrt(n_error_array[i] ** 2 + error_bkg[i] ** 2)
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# Substract background
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if subtract_error > 0:
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if np.abs(subtract_error) > 0:
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n_data_array[i][mask] = n_data_array[i][mask] - bkg
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n_data_array[i][np.logical_and(mask, n_data_array[i] <= 1e-3 * bkg)] = 1e-3 * bkg
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@@ -367,7 +367,7 @@ def bkg_hist(data, error, mask, headers, sub_type=None, subtract_error=True, dis
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n_error_array[i] = np.sqrt(n_error_array[i] ** 2 + error_bkg[i] ** 2)
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# Substract background
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if subtract_error > 0:
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if np.abs(subtract_error) > 0:
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n_data_array[i][mask] = n_data_array[i][mask] - bkg
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n_data_array[i][np.logical_and(mask, n_data_array[i] <= 1e-3 * bkg)] = 1e-3 * bkg
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@@ -464,7 +464,7 @@ def bkg_mini(data, error, mask, headers, sub_shape=(15, 15), subtract_error=True
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n_error_array[i] = np.sqrt(n_error_array[i] ** 2 + error_bkg[i] ** 2)
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# Substract background
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if subtract_error > 0.0:
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if np.abs(subtract_error) > 0:
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n_data_array[i][mask] = n_data_array[i][mask] - bkg
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n_data_array[i][np.logical_and(mask, n_data_array[i] <= 1e-3 * bkg)] = 1e-3 * bkg
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