change all np.float to float, np.bool to bool

prime/postrefine/mod_util.py

@@ -551,7 +551,7 @@ def plot_stats(self, results, iparams):
       n_cols = int(math.ceil(len(params)/n_rows))
       num_bins = 10
       for i in range(len(params)-1):
-        tmp_params = params_array[:,i].astype(np.float)
+        tmp_params = params_array[:,i].astype(float)
         plt.subplot(n_rows,n_cols,i+1)
         plt.hist(tmp_params, num_bins, normed=0, facecolor='green', alpha=0.5)
         plt.ylabel('Frequencies')

simtbx/modeling/predictions.py

@@ -198,7 +198,7 @@ def label_weak_spots_for_integration(fraction, predictions, num_res_bins=10):
     res_sort = np.sort(res)
     res_bins = [rb[0]-1e-6 for rb in np.array_split( res_sort, num_res_bins)] + [res_sort[-1]+1e-6]
     res_bin_assigments = np.digitize(res, res_bins)
-    is_weak_but_integratable = np.zeros(len(predictions)).astype(np.bool)
+    is_weak_but_integratable = np.zeros(len(predictions)).astype(bool)
     for i_res in range(1, num_res_bins+1):
         # grab weak spots in this res bin
         is_weak_and_in_bin = logi_and(res_bin_assigments == i_res, predictions["is_weak"])

xfel/command_line/xtc_process.py

@@ -22,7 +22,6 @@
 from libtbx.phil import parse
 from dxtbx.model.experiment_list import ExperimentListFactory
 from dials.array_family import flex
-import numpy as np
 from libtbx import easy_pickle
 from dxtbx.model.experiment_list import ExperimentList
 
@@ -508,7 +507,7 @@ def mpi_log_write(self, string):
     mpi_log_file_handle.close()
 
   def psana_mask_to_dials_mask(self, psana_mask):
-    if psana_mask.dtype == np.bool:
+    if psana_mask.dtype == bool:
       psana_mask = flex.bool(psana_mask)
     else:
       psana_mask = flex.bool(psana_mask == 1)