diff --git a/py/picca/bin/picca_export_co.py b/py/picca/bin/picca_export_co.py index 8eade4daa..e8e2f739b 100644 --- a/py/picca/bin/picca_export_co.py +++ b/py/picca/bin/picca_export_co.py @@ -209,7 +209,7 @@ def main(cmdargs): sys.exit() w = np.logical_not( - np.in1d(data[type_corr1]['HEALPID'], + np.isin(data[type_corr1]['HEALPID'], data[type_corr2]['HEALPID'])) if w.sum() != 0: userprint("WARNING: HEALPID are different by {} for {}:{} " diff --git a/py/picca/bin/picca_export_cross_covariance.py b/py/picca/bin/picca_export_cross_covariance.py index a2c53f43f..f5375a474 100644 --- a/py/picca/bin/picca_export_cross_covariance.py +++ b/py/picca/bin/picca_export_cross_covariance.py @@ -77,7 +77,7 @@ def main(cmdargs): # Add unshared healpix as empty data for key in sorted(list(data.keys())): key2 = (key + 1) % 2 - w = np.logical_not(np.in1d(data[key2]['HEALPID'], data[key]['HEALPID'])) + w = np.logical_not(np.isin(data[key2]['HEALPID'], data[key]['HEALPID'])) if w.sum() > 0: new_healpix = data[key2]['HEALPID'][w] num_new_healpix = new_healpix.size diff --git a/py/picca/bin/picca_reduce_spall.py b/py/picca/bin/picca_reduce_spall.py index 343962fbd..e4af2a2e1 100644 --- a/py/picca/bin/picca_reduce_spall.py +++ b/py/picca/bin/picca_reduce_spall.py @@ -28,7 +28,7 @@ qso_catalog = Table.read(args.qso_catalog) print(f'{len(qso_catalog)} entries found in QSO catalog') -w = np.in1d(spall['THING_ID'], qso_catalog['THING_ID']) +w = np.isin(spall['THING_ID'], qso_catalog['THING_ID']) spall_qso = spall[w] #-- Columns required for picca_deltas.py for spec, spplate formats and usage of multiple observations spall_qso.keep_columns( diff --git a/py/picca/cf.py b/py/picca/cf.py index 837bfaff6..e845d824e 100644 --- a/py/picca/cf.py +++ b/py/picca/cf.py @@ -1323,7 +1323,7 @@ def compute_xi_1d_cross(healpix): weights1 = delta1.weights[select1] thingids = [delta2.thingid for delta2 in data2[healpix]] - neighbours = data2[healpix][np.in1d(thingids, [delta1.thingid])] + neighbours = data2[healpix][np.isin(thingids, [delta1.thingid])] for delta2 in neighbours: select2 = delta2.log_lambda <= log_lambda_max select2 &= delta2.log_lambda >= log_lambda_min diff --git a/py/picca/delta_extraction/quasar_catalogues/drq_catalogue.py b/py/picca/delta_extraction/quasar_catalogues/drq_catalogue.py index fa2d6fde1..db66ea0a3 100644 --- a/py/picca/delta_extraction/quasar_catalogues/drq_catalogue.py +++ b/py/picca/delta_extraction/quasar_catalogues/drq_catalogue.py @@ -274,7 +274,7 @@ def read_spall(self, drq_catalogue): f"message: {str(error)}" ) from error - w = np.in1d(catalogue["THING_ID"], drq_catalogue["THING_ID"]) + w = np.isin(catalogue["THING_ID"], drq_catalogue["THING_ID"]) self.logger.progress(f"Found {np.sum(w)} spectra with required THING_ID") w &= catalogue["PLATEQUALITY"] == "good" self.logger.progress(f"Found {np.sum(w)} spectra with 'good' plate") diff --git a/py/picca/pk1d/compute_pk1d.py b/py/picca/pk1d/compute_pk1d.py index 8efdd9158..9e9b71edd 100644 --- a/py/picca/pk1d/compute_pk1d.py +++ b/py/picca/pk1d/compute_pk1d.py @@ -326,7 +326,7 @@ def fill_masked_pixels( lambda_or_log_lambda_index += 0.5 lambda_or_log_lambda_index = np.array(lambda_or_log_lambda_index, dtype=int) index_all = range(lambda_or_log_lambda_index[-1] + 1) - index_ok = np.in1d(index_all, lambda_or_log_lambda_index) + index_ok = np.isin(index_all, lambda_or_log_lambda_index) delta_new = np.zeros(len(index_all)) delta_new[index_ok] = delta diff --git a/py/picca/raw_io.py b/py/picca/raw_io.py index 26c18d7aa..e14c24637 100644 --- a/py/picca/raw_io.py +++ b/py/picca/raw_io.py @@ -73,7 +73,7 @@ def read_transmission_file(filename, num_bins, objs_thingid, tracer='F_LYA', lam hdul = fitsio.FITS(filename) thingid = hdul['METADATA']['MOCKID'][:] - if np.in1d(thingid, objs_thingid).sum() == 0: + if np.isin(thingid, objs_thingid).sum() == 0: hdul.close() return if 'RA' in hdul['METADATA'].get_colnames() and 'DEC' in hdul['METADATA'].get_colnames(): @@ -116,7 +116,7 @@ def read_transmission_file(filename, num_bins, objs_thingid, tracer='F_LYA', lam (lambda_rest_frame < lambda_max_rest_frame)] = 1 num_pixels = np.sum(valid_pixels, axis=1) w = num_pixels >= 50 - w &= np.in1d(thingid, objs_thingid) + w &= np.isin(thingid, objs_thingid) if w.sum() == 0: hdul.close() return diff --git a/py/picca/xcf.py b/py/picca/xcf.py index e2f8abd59..8d1d65dcd 100644 --- a/py/picca/xcf.py +++ b/py/picca/xcf.py @@ -965,7 +965,7 @@ def compute_wick_terms(healpixs): thingid4 = np.array([obj4.thingid for obj4 in neighbours]) if max_diagram == 5: - w = np.in1d(delta1.neighbours, delta3.neighbours) + w = np.isin(delta1.neighbours, delta3.neighbours) if w.sum() == 0: continue aux_ang12 = ang12[w] @@ -973,7 +973,7 @@ def compute_wick_terms(healpixs): aux_weights2 = weights2[w] aux_thingid2 = thingid2[w] - w = np.in1d(delta3.neighbours, delta1.neighbours) + w = np.isin(delta3.neighbours, delta1.neighbours) if w.sum() == 0: continue ang34 = ang34[w] diff --git a/tutorials/picca_export_stacked_correlation.py b/tutorials/picca_export_stacked_correlation.py index fdcbbcf93..c437a5173 100755 --- a/tutorials/picca_export_stacked_correlation.py +++ b/tutorials/picca_export_stacked_correlation.py @@ -82,7 +82,7 @@ ### Add unshared healpix as empty data for i in range(nbData): for j in range(nbData): - w = np.logical_not( np.in1d(data[j]['HEALPID'],data[i]['HEALPID']) ) + w = np.logical_not( np.isin(data[j]['HEALPID'],data[i]['HEALPID']) ) if w.sum()>0: new_healpix = data[j]['HEALPID'][w] nb_new_healpix = new_healpix.size