diff --git a/prime/postrefine/mod_util.py b/prime/postrefine/mod_util.py index 1957a8e1565..8e176c26fe4 100644 --- a/prime/postrefine/mod_util.py +++ b/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') diff --git a/simtbx/modeling/predictions.py b/simtbx/modeling/predictions.py index a1aa37236f5..1e8372a2076 100644 --- a/simtbx/modeling/predictions.py +++ b/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"]) diff --git a/xfel/command_line/xtc_process.py b/xfel/command_line/xtc_process.py index fe935ba802f..e12fdde3761 100644 --- a/xfel/command_line/xtc_process.py +++ b/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)