Fix/numpy (#150)

* replace np.round_ with np.round * replace numpy.round_ with numpy.round
noaa-ocs-modeling · Aug 7, 2024 · 7b37332 · 7b37332
1 parent 2d08625
commit 7b37332
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diff --git a/ensembleperturbation/plotting/surrogate.py b/ensembleperturbation/plotting/surrogate.py
@@ -400,7 +400,7 @@ def plot_selected_validations(
             validation['y'].max(),
         ]
     )
-    vmax = numpy.round_(validation.sel(source='model').results.quantile(0.98), decimals=1)
+    vmax = numpy.round(validation.sel(source='model').results.quantile(0.98), decimals=1)
     vmin = 0.0
     for run in run_list:
         figure = pyplot.figure()
@@ -476,7 +476,7 @@ def plot_selected_percentiles(
             node_percentiles['y'].max(),
         ]
     )
-    vmax = numpy.round_(percentiles.sel(source='model').quantile(0.98), decimals=1)
+    vmax = numpy.round(percentiles.sel(source='model').quantile(0.98), decimals=1)
     vmin = 0.0
     for perc in perc_list:
         figure = pyplot.figure()

diff --git a/ensembleperturbation/uncertainty_quantification/karhunen_loeve_expansion.py b/ensembleperturbation/uncertainty_quantification/karhunen_loeve_expansion.py
@@ -214,8 +214,8 @@ def karhunen_loeve_prediction(
                 actual_values['y'].max(),
             ]
         )
-        vmax = np.round_(actual_values.quantile(0.98), decimals=1)
-        vmin = min(0.0, np.round_(actual_values.quantile(0.02), decimals=1))
+        vmax = np.round(actual_values.quantile(0.98), decimals=1)
+        vmin = min(0.0, np.round(actual_values.quantile(0.02), decimals=1))
         sources = {'actual': actual_values, 'reconstructed': kl_prediction}
         map_crs = cartopy.crs.PlateCarree()
         for example in ensembles_to_plot: