From 7d1240967015c035be18d07eda7c12b7d5e882cf Mon Sep 17 00:00:00 2001 From: bpalmeiro Date: Tue, 14 Jan 2025 18:14:46 +0100 Subject: [PATCH] Change floats to ints And alignment accordingly --- .../reco/icaro_components_test.py | 24 +++++++++---------- 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/invisible_cities/reco/icaro_components_test.py b/invisible_cities/reco/icaro_components_test.py index 972c6cc94..2d665a2af 100644 --- a/invisible_cities/reco/icaro_components_test.py +++ b/invisible_cities/reco/icaro_components_test.py @@ -18,9 +18,9 @@ @mark.parametrize("signal", icarcomp.type_of_signal) @given(nsignals= integers(min_value = 1, - max_value = 1e4)) + max_value = 10*1000)) def test_select_nS_mask_and_check_right_output(nsignals, signal): - nevt = int(1e4) + nevt = 10*1000 data = np.concatenate([np.zeros(nevt- nsignals), np.ones(nsignals)]) np.random.shuffle(data) data = pd.DataFrame({'nS1': data, 'nS2': data, 'event': range(nevt)}) @@ -30,9 +30,9 @@ def test_select_nS_mask_and_check_right_output(nsignals, signal): @given(integers(min_value = 1, - max_value = 1e4)) + max_value = 10*1000)) def test_select_nS_mask_and_check_consistency(nsignals): - nevt = int(1e4) + nevt = 10*1000 data = np.concatenate([np.zeros(nevt - nsignals), np.ones(nsignals)]) np.random.shuffle(data) data = pd.DataFrame({'nS1': data, 'event': range(nevt)}) @@ -42,11 +42,11 @@ def test_select_nS_mask_and_check_consistency(nsignals): @given(integers(min_value = 1, - max_value = 1e4), + max_value = 10*1000), integers(min_value = 1, - max_value = 1e4)) + max_value = 10*1000)) def test_select_nS_mask_and_check_concatenating(ns1, ns2): - nevt = int(1e4) + nevt = 10*1000 dataS1 = np.concatenate([np.zeros(nevt- ns1), np.ones (ns1)]) dataS2 = np.concatenate([np.zeros(nevt- ns2), @@ -62,12 +62,12 @@ def test_select_nS_mask_and_check_concatenating(ns1, ns2): def test_select_nS_mask_and_check_range_assertion(): - nevt = int(1e4) - ns1 = int(1e3) + nevt = 10*1000 + ns1 = 1000 min_eff = 0.5 max_eff = 1 - dataS1 = np.concatenate([np.zeros(nevt- ns1), - np.ones (ns1)]) + dataS1 = np.concatenate([np.zeros(nevt- ns1), + np.ones (ns1)]) np.random.shuffle(dataS1) data = pd.DataFrame({'nS1': dataS1, 'event': range(nevt)}) eff = ns1 / nevt @@ -79,7 +79,7 @@ def test_select_nS_mask_and_check_range_assertion(): @mark.parametrize("sigma", (0.1, 1, 5, 10, 20)) def test_estimate_sigma(sigma): - nevt = int(1e4) + nevt = 10*1000 xrange = [0, 1000] slope = 100 n0 = 100