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updated tables with results for referee revision
1 parent c0006b9 commit 56edd7b

14 files changed

+27
-27
lines changed

Diff for: examples/analysis.ipynb

+22-22
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@@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
@@ -12,7 +12,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"9604\n",
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"2719\n",
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"1240\n",
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"147\n"
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"2694\n",
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"1211\n",
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"149\n"
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]
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}
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],
@@ -56,7 +56,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
@@ -68,7 +68,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
@@ -78,7 +78,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"source": [
@@ -89,7 +89,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
@@ -98,7 +98,7 @@
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"'firing_pixels_filtered.fits'"
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]
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},
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"execution_count": 6,
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -112,7 +112,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
@@ -122,9 +122,9 @@
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"Filename: firing_pixels.fits\n",
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"No. Name Ver Type Cards Dimensions Format\n",
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" 0 PRIMARY 1 PrimaryHDU 4 () \n",
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" 1 ALPHA=0.01 1 BinTableHDU 19 9957R x 5C [K, E, E, E, E] \n",
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" 2 ALPHA=0.05 1 BinTableHDU 19 9500R x 5C [K, E, E, E, E] \n",
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" 3 ALPHA=0.1 1 BinTableHDU 19 8681R x 5C [K, E, E, E, E] \n"
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" 1 ALPHA=0.01 1 BinTableHDU 19 10068R x 5C [K, E, E, E, E] \n",
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" 2 ALPHA=0.05 1 BinTableHDU 19 9636R x 5C [K, E, E, E, E] \n",
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" 3 ALPHA=0.1 1 BinTableHDU 19 9409R x 5C [K, E, E, E, E] \n"
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]
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},
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{
@@ -143,7 +143,7 @@
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"BITPIX = 8 / array data type \n",
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"NAXIS = 2 / number of array dimensions \n",
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"NAXIS1 = 24 / length of dimension 1 \n",
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"NAXIS2 = 9957 / length of dimension 2 \n",
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"NAXIS2 = 10068 / length of dimension 2 \n",
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"PCOUNT = 0 / number of group parameters \n",
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"GCOUNT = 1 / number of groups \n",
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"TFIELDS = 5 / number of table fields \n",
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{
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"data": {
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"text/plain": [
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"FITS_rec([( 146881, 6.8197925e+05, 1. , 1. , 1. ),\n",
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" (2545130, 6.4414856e+05, 1. , 1. , 1. ),\n",
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" (2543081, 3.3422578e+05, 1. , 1. , 1. ),\n",
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"FITS_rec([( 146881, 6.819703e+05, 1. , 1. , 1. ),\n",
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" (2545130, 6.438488e+05, 1. , 1. , 1. ),\n",
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" (2543081, 3.341038e+05, 1. , 1. , 1. ),\n",
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" ...,\n",
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" (2907254, 3.3943626e+01, 0.50394815, 0.49927253, 0.5106475 ),\n",
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" (2427848, 3.3915901e+01, 0.50070864, 0.49590784, 0.5073455 ),\n",
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" ( 387044, 3.3909271e+01, 0.50050616, 0.4957333 , 0.50716674)],\n",
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" ( 690723, 3.331866e+01, 0.5034965 , 0.49776882, 0.5099845 ),\n",
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" ( 558036, 3.331725e+01, 0.50312847, 0.49743295, 0.5096404 ),\n",
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" ( 460713, 3.331335e+01, 0.50257635, 0.49686065, 0.50907266)],\n",
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" dtype=(numpy.record, [('pixel', '>i8'), ('TS', '>f4'), ('QF_best', '>f4'), ('QF_min', '>f4'), ('QF_max', '>f4')]))"
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]
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},

Diff for: examples/firing_pixels.fits

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Diff for: pyproject.toml

+1-1
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@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
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[project]
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name = "gPCS"
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version = "1.0.2"
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version = "1.0.3"
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authors = [
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{ name="Aurelio Amerio", email="[email protected]" },
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{ name="Francesca Calore", email=""},

Diff for: src/gPCS/data/TS_map_4FGL.npz

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Diff for: src/gPCS/data/TS_map_fermi.npz

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Diff for: src/gPCS/data/TS_star_alpha_0.01.npz

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Diff for: src/gPCS/data/TS_star_alpha_0.01_4FGL.npz

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Diff for: src/gPCS/data/TS_star_alpha_0.05.npz

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Diff for: src/gPCS/data/TS_star_alpha_0.05_4FGL.npz

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Diff for: src/gPCS/data/TS_star_alpha_0.1.npz

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Diff for: src/gPCS/data/TS_star_alpha_0.1_4FGL.npz

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Diff for: tests/files/TS_ranking_fermi.npz

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Diff for: tests/files/pixel_firing.npz

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Diff for: tests/test_gPCS.py

+4-4
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@@ -23,20 +23,20 @@ def test_get_CDF():
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return
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def test_get_QF_from_TS():
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QF_ref = 0.47013565499088883
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QF_ref = 0.527972027972028 #0.47013565499088883
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QF = gPCS.get_QF_from_TS(36, alpha=0.05)
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assert np.allclose(QF, QF_ref)
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return
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def test_get_QF_ranges_from_TS():
32-
m_ref = 0.47
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s_ref = 0.0086
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m_ref = 0.52 #0.47
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s_ref = 0.0086 #0.0086
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m, s = gPCS.get_QF_ranges_from_TS(36, alpha=0.05, batches=1_000, batch_size=2000)
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assert np.allclose(m, m_ref, rtol=1e-1) and np.allclose(s, s_ref, rtol=1e-1)
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return
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def test_get_TS_from_QF():
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TS_ref = 36.56653911691979
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TS_ref = 35.791377316749134 #36.56653911691979
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TS = gPCS.get_TS_from_QF(0.5, alpha=0.05)
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assert np.allclose(TS, TS_ref)
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return

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