update.

flarestack/analyses/general/check_stack_bias_equal_dist_iip.py

@@ -0,0 +1,75 @@
+import numpy as np
+import os
+from astropy.table import Table
+import argparse
+from flarestack.core.results import ResultsHandler
+from flarestack.data.icecube import ps_v002_p01
+from flarestack.shared import plot_output_dir, flux_to_k
+from flarestack.analyses.ccsn.stasik_2017.ccsn_limits import limits, get_figure_limits, p_vals
+from flarestack.analyses.ccsn.necker_2019.ccsn_helpers import sn_cats, updated_sn_catalogue_name, \
+    sn_time_pdfs, raw_output_dir, pdf_names, limit_sens
+from flarestack.analyses.ccsn import get_sn_color
+from flarestack.cluster import analyse
+from flarestack.cluster.run_desy_cluster import wait_for_cluster
+import math
+import pickle
+from flarestack.utils.custom_dataset import custom_dataset
+import os
+import logging
+import time
+logging.getLogger().setLevel("INFO")
+injection_energy = {
+    "energy_pdf_name": "power_law",
+    "gamma": 2.0
+}
+
+injection_time = {
+    'time_pdf_name': 'steady'
+}
+
+llh_energy = {
+    "energy_pdf_name": "power_law"
+}
+
+llh_time = {
+    'time_pdf_name': 'steady'
+}
+
+inj_dict = {
+    'injection_energy_pdf': injection_energy,
+    'injection_sig_time_pdf': injection_time
+}
+
+llh_dict = {
+    "llh_name": "standard_matrix",
+    "llh_energy_pdf": llh_energy,
+    "llh_sig_time_pdf": llh_time,
+    "llh_bkg_time_pdf": {"time_pdf_name": "steady"}
+}
+
+
+catalogue = np.load(updated_sn_catalogue_name('IIP'))
+catalogue['distance_mpc'] = np.array([1] * len(catalogue))
+dir_path = os.path.dirname(os.path.realpath(__file__))
+temp_save_catalogue_to = f'{dir_path}/temp_check_stack_bias_equal_dist_cat_iip.npy'
+np.save(temp_save_catalogue_to, catalogue)
+
+
+mh_dict = {
+    "name": "examples/crosscheck_stacking_equal_dist_iip/",
+    "mh_name": 'large_catalogue',
+    "dataset": ps_v002_p01.get_seasons(),
+    "catalogue": temp_save_catalogue_to,
+#     "catalogue": ps_stack_catalogue_name(0.1, 0.3),
+#     "catalogue": tde_catalogue_name("jetted"),
+    "inj_dict": inj_dict,
+    "llh_dict": llh_dict,
+    "scale": 10.,
+    "n_trials": 60,
+    "n_steps": 10
+}
+
+analyse(mh_dict, cluster=False, n_cpu=32)
+rh = ResultsHandler(mh_dict)
+
+os.remove(temp_save_catalogue_to)