Change the tests. To implement the np.asset_almots_equal function, to…

… compare the numpy arrays.

ptiming_ana/phaseogram/pulsar_analysis.py

@@ -297,7 +297,7 @@ def set_config(self, configuration_file):
             P3_limits=conf["phase_regions"]["P3"],
         )
 
-        if conf["phase_binning"]["custom_binning"]:
+        if not conf["phase_binning"]["custom_binning"]:
             self.setBinning(
                 conf["phase_binning"]["nbins"],
                 xmin=conf["phase_binning"]["xmin"],

tests/test_tutorial.py

@@ -1,7 +1,6 @@
 import unittest
 from ptiming_ana.phaseogram import PulsarAnalysis
 from astropy.io import fits
-import pandas as pd
 import numpy as np
 
 
@@ -34,31 +33,64 @@ def test_load_config_file(self):
         h.setListsInput(phases, times, energies / 1e6, tel="fermi", energy_units="TeV")
         h.get_results = False
 
-        self.assertEquals(h_config_from_file, h)
+        self.assertEqual(h_config_from_file, h)
 
     def test_run_analysis_phaseogram(self):
         h = PulsarAnalysis()
         h.set_config("tests/files/config_test.yaml")
         h.run()
         results = h.show_Presults()
 
-        expected_result = (
-            pd.read_pickle("tests/files/peak_statistics_tutorial.pkl"),
-            pd.read_pickle("tests/files/periodicity_statistics_tutorial.pkl"),
+        peak_stadistics_data_expec = np.array(
+            [
+                [108.5913594, 58.00656799, 110.16571886, 14.3384333],
+                [5959.23714286, 2677.27142857, 8636.50857143, 1126.74285714],
+                [84.22028603, 62.20823982, 105.93665554, 81.25025086],
+                [6969.0, 3734.0, 10703.0, 4884.0],
+                [1009.76285714, 1056.72857143, 2066.49142857, 3757.25714286],
+                [451.84108843, 241.36129211, 458.39188858, 59.661223],
+                [187.53441252, 82.35892672, 189.98591475, 18.38185577],
+            ]
         )
 
-        pd.testing.assert_frame_equal(results[0], expected_result[0])
-        pd.testing.assert_frame_equal(results[1], expected_result[1])
+        periodicity_statistics_data_expec = np.array(
+            [
+                [26977.43375174, 25992.17369182, 28101.4067069],
+                [0.0, 0.0, 0.0],
+                [np.inf, np.inf, np.inf],
+            ]
+        )
+
+        np.testing.assert_almost_equal(
+            results[0].to_numpy(), peak_stadistics_data_expec, decimal=5
+        )
+        np.testing.assert_almost_equal(
+            results[1].to_numpy(), periodicity_statistics_data_expec, decimal=5
+        )
 
     def test_run_analysis_fitting(self):
         h = PulsarAnalysis()
         h.set_config("tests/files/config_test.yaml")
         h.run()
 
-        self.assertEquals(h.fit_model, "dgaussian")
+        self.assertEqual(h.fit_model, "dgaussian")
         results = h.show_fit_results()
-        expected_result = pd.read_pickle("tests/files/fit_result_tutorial.pkl")
-        pd.testing.assert_frame_equal(results, expected_result)
+
+        fit_result_expected = np.array(
+            [
+                [0.9924233191795764, 0.0015660661377770266],
+                [0.026304542387059753, 0.0014698372893777872],
+                [1.3763409922947634, 0.004402295450743174],
+                [0.0509859742803803, 0.004192067589437329],
+                [466.4375, 0.0],
+                [200.23728941446313, 10.903033719301062],
+                [145.13336608138428, 11.04167277916415],
+            ]
+        )
+
+        np.testing.assert_almost_equal(
+            results.to_numpy()[:, 1:], fit_result_expected, decimal=5
+        )
 
 
 if __name__ == "__main__":