diff --git a/examples/Single_Photon_Test.ipynb b/examples/Single_Photon_Test.ipynb
index 4320e82..76a04be 100644
--- a/examples/Single_Photon_Test.ipynb
+++ b/examples/Single_Photon_Test.ipynb
@@ -41,7 +41,7 @@
{
"data": {
"text/plain": [
- "{'dynamic': 0, 'num_procs': 64, 'threads_limit': 2147483647, 'threads_max': 64}"
+ "{'dynamic': 0, 'num_procs': 8, 'threads_limit': 2147483647, 'threads_max': 8}"
]
},
"execution_count": 3,
@@ -64,13 +64,16 @@
"text": [
"Help on function find_photons in module pycentroids.pycentroids:\n",
"\n",
- "find_photons(images, threshold=200, box=2, search_box=1, pixel_photon=9, pixel_bgnd=15, com_photon=9, overlap_max=0, sum_min=800, sum_max=1250, fit_pixels_2d=True, fit_pixels_1d_x=True, fit_pixels_1d_y=True, return_pixels='none', return_map=False)\n",
+ "find_photons(images, filter=None, threshold=200, box=2, search_box=1, pixel_photon=9, pixel_bgnd=15, com_photon=9, overlap_max=0, sum_min=800, sum_max=1250, pixel_lut=None, pixel_lut_range=None, fit_pixels_2d=True, fit_pixels_1d_x=True, fit_pixels_1d_y=True, fit_constraints=None, fit_weights_2d=None, fit_weights_1d=None, return_pixels='none', return_map=False, tag_pixels=False)\n",
" Find photons in CCD images and process for sub-pixel center.\n",
" \n",
" Parameters\n",
" ----------\n",
" images : numpy.ndarray\n",
" Images to process of 3 dimensions\n",
+ " filter : numpy.ndarray or None\n",
+ " Filter image of 2d or 3d shape. Should be non-zero to filter pixels.\n",
+ " If none, then no pixels are filtered.\n",
" threshold : int\n",
" Pixel value threshold for first search of images\n",
" box : int\n",
@@ -101,6 +104,11 @@
" The minimum integrated intensity to filter the output table.\n",
" sum_max : float\n",
" The maximum integrated intensity to filter the output table.\n",
+ " pixel_lut : np.array\n",
+ " Lookup table for the pixel COM correction. 1D array of\n",
+ " corrected position\n",
+ " pixel_lut_range: tuple\n",
+ " Tuple of the start and end coordinates for the LUT\n",
" fit_pixels_2d : bool\n",
" If true, fit the pixels from a photon with a 2D gaussian\n",
" fit_pixels_1dx : bool\n",
@@ -109,10 +117,22 @@
" fit_pixels_1dy : bool\n",
" If true, fit the pixels from a photon with a 1D gaussian integrating\n",
" along the x-axis to get the y position\n",
+ " fit_constraints : dict\n",
+ " Dictionary of constraints to use for fitting pixels\n",
+ " Currently the dictionary keys can be:\n",
+ " pos_range, pos_cent : Position (x) of photon range and center\n",
+ " sigma_range, sigma_cent : Sigma of the gaussian range anc center\n",
+ " fit_weights_2d : np.array\n",
+ " array of size (2 * box + 1) * (2 * box + 1) of the weights to use for\n",
+ " the pixel fit\n",
+ " fit_weights_1d : np.array\n",
+ " array of size (2 * box + 1) of the weights to use for the pixel fits\n",
" return_pixels : 'none', 'sorted', 'unsorted'\n",
" Option to return array of pixel values\n",
" return_map : bool\n",
" Option to return map of located photons.\n",
+ " tag_pixels : bool\n",
+ " Option to tag the found photons in the pixel map by setting the MSB\n",
" \n",
" Returns\n",
" -------\n",
@@ -205,11 +225,11 @@
},
{
"cell_type": "code",
- "execution_count": 48,
+ "execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
- "df, out, pixels = pycentroids.find_photons(data, 250, 3, sum_max=1200, sum_min=800,\n",
+ "df, out, pixels = pycentroids.find_photons(data, None, 250, 3, sum_max=1200, sum_min=800,\n",
" pixel_photon=9, pixel_bgnd=20, com_photon=5,\n",
" fit_pixels_2d=True, fit_pixels_1d_x=True, fit_pixels_1d_y=True,\n",
" return_pixels='unsorted', return_map=True)"
@@ -217,7 +237,7 @@
},
{
"cell_type": "code",
- "execution_count": 49,
+ "execution_count": 11,
"metadata": {},
"outputs": [
{
@@ -226,7 +246,7 @@
"(702, 44)"
]
},
- "execution_count": 49,
+ "execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
@@ -237,7 +257,7 @@
},
{
"cell_type": "code",
- "execution_count": 50,
+ "execution_count": 12,
"metadata": {},
"outputs": [
{
@@ -255,7 +275,7 @@
},
{
"cell_type": "code",
- "execution_count": 51,
+ "execution_count": 13,
"metadata": {},
"outputs": [
{
@@ -264,13 +284,13 @@
"text": [
"(702, 7, 7)\n",
"\n",
- "array([[156, 152, 155, 155, 161, 153, 148],\n",
- " [155, 156, 159, 163, 149, 156, 168],\n",
- " [151, 159, 162, 178, 169, 163, 166],\n",
- " [158, 163, 161, 930, 251, 177, 159],\n",
- " [155, 157, 149, 196, 187, 153, 153],\n",
- " [153, 152, 151, 171, 157, 152, 161],\n",
- " [156, 159, 159, 143, 155, 158, 161]], dtype=uint16)\n"
+ "array([[167, 163, 153, 166, 181, 158, 161],\n",
+ " [152, 156, 150, 161, 156, 159, 160],\n",
+ " [161, 154, 171, 185, 165, 178, 157],\n",
+ " [145, 164, 404, 467, 201, 200, 162],\n",
+ " [160, 161, 213, 311, 178, 166, 154],\n",
+ " [158, 161, 166, 158, 156, 162, 153],\n",
+ " [159, 158, 160, 144, 162, 159, 159]], dtype=uint16)\n"
]
}
],
@@ -283,26 +303,26 @@
},
{
"cell_type": "code",
- "execution_count": 52,
+ "execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['Pixel X', 'Pixel Y', 'COM X', 'COM Y', 'COR COM X', 'COR COM Y', 'Int',\n",
- " 'Bgnd', 'Overlap', 'Fit X', 'Fit Y', 'Fit Bgnd', 'Fit Amp', 'Fit Sigma',\n",
- " 'Fit Err X', 'Fit Err Y', 'Fit Err Bgnd', 'Fit Err Amp',\n",
- " 'Fit Err Sigma', 'Fit Fnorm', 'Fit Outcome', 'Fit StdErr', 'Fit 1DX X',\n",
- " 'Fit 1DX Bgnd', 'Fit 1DX Amp', 'Fit 1DX Sigma', 'Fit 1DX Err X',\n",
- " 'Fit 1DX Err Bgnd', 'Fit 1DX Err Amp', 'Fit 1DX Err Sigma',\n",
+ " 'Bgnd', 'Overlap', 'Fit X', 'Fit Y', 'Fit Amp', 'Fit Sigma', 'Fit Bgnd',\n",
+ " 'Fit Err X', 'Fit Err Y', 'Fit Err Amp', 'Fit Err Sigma',\n",
+ " 'Fit Err Bgnd', 'Fit Fnorm', 'Fit Outcome', 'Fit StdErr', 'Fit 1DX X',\n",
+ " 'Fit 1DX Amp', 'Fit 1DX Sigma', 'Fit 1DX Bgnd', 'Fit 1DX Err X',\n",
+ " 'Fit 1DX Err Amp', 'Fit 1DX Err Sigma', 'Fit 1DX Err Bgnd',\n",
" 'Fit 1DX Fnorm', 'Fit 1DX Outcome', 'Fit 1DX StdErr', 'Fit 1DY Y',\n",
- " 'Fit 1DY Bgnd', 'Fit 1DY Amp', 'Fit 1DY Sigma', 'Fit 1DY Err Y',\n",
- " 'Fit 1DY Err Bgnd', 'Fit 1DY Err Amp', 'Fit 1DY Err Sigma',\n",
+ " 'Fit 1DY Amp', 'Fit 1DY Sigma', 'Fit 1DY Bgnd', 'Fit 1DY Err Y',\n",
+ " 'Fit 1DY Err Amp', 'Fit 1DY Err Sigma', 'Fit 1DY Err Bgnd',\n",
" 'Fit 1DY Fnorm', 'Fit 1DY Outcome', 'Fit 1DY StdErr'],\n",
" dtype='object')"
]
},
- "execution_count": 52,
+ "execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
@@ -313,16 +333,16 @@
},
{
"cell_type": "code",
- "execution_count": 53,
+ "execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "(685, 44)"
+ "(692, 44)"
]
},
- "execution_count": 53,
+ "execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
@@ -336,7 +356,7 @@
},
{
"cell_type": "code",
- "execution_count": 54,
+ "execution_count": 16,
"metadata": {},
"outputs": [
{
@@ -371,13 +391,13 @@
"
Overlap | \n",
" Fit X | \n",
" ... | \n",
- " Fit 1DY Bgnd | \n",
" Fit 1DY Amp | \n",
" Fit 1DY Sigma | \n",
+ " Fit 1DY Bgnd | \n",
" Fit 1DY Err Y | \n",
- " Fit 1DY Err Bgnd | \n",
" Fit 1DY Err Amp | \n",
" Fit 1DY Err Sigma | \n",
+ " Fit 1DY Err Bgnd | \n",
" Fit 1DY Fnorm | \n",
" Fit 1DY Outcome | \n",
" Fit 1DY StdErr | \n",
@@ -386,723 +406,123 @@
" \n",
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\n",
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\n",
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"
\n",
" \n",
"\n",
- "685 rows × 44 columns
\n",
+ "692 rows × 44 columns
\n",
""
],
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- "691 831.0 872.0 831.516233 872.225635 831.515167 872.225500 \n",
- "692 848.0 872.0 847.907535 871.833039 847.906500 871.831333 \n",
- "693 409.0 873.0 409.434811 873.071812 409.434500 873.071500 \n",
- "694 486.0 873.0 486.054955 872.735571 486.053167 872.734167 \n",
- "695 582.0 873.0 582.197424 872.481489 582.196167 872.481167 \n",
- "696 677.0 873.0 677.042021 872.845070 677.040333 872.844167 \n",
- "697 791.0 873.0 790.599205 872.706802 790.598500 872.706667 \n",
- "698 702.0 874.0 702.368639 874.227008 702.368500 874.225500 \n",
- "699 625.0 879.0 625.148112 878.812197 625.146667 878.811167 \n",
- "700 512.0 938.0 512.179942 937.588318 512.179667 937.587500 \n",
- "701 381.0 1008.0 381.433481 1007.774945 381.432667 1007.774500 \n",
+ " Pixel X Pixel Y COM X COM Y COR COM X COR COM Y \\\n",
+ "0 274.0 855.0 273.680844 855.259179 273.680340 855.259630 \n",
+ "1 562.0 872.0 561.714516 872.382630 561.714357 872.382691 \n",
+ "2 581.0 872.0 580.918971 872.441410 580.918459 872.441721 \n",
+ "3 661.0 872.0 661.397199 872.316886 661.397699 872.316658 \n",
+ "4 689.0 872.0 688.902008 872.439284 688.902451 872.439720 \n",
+ ".. ... ... ... ... ... ... \n",
+ "697 444.0 873.0 443.737567 872.653214 443.737369 872.653327 \n",
+ "698 495.0 873.0 495.403632 872.762661 495.403702 872.762381 \n",
+ "699 680.0 873.0 679.937358 873.149703 679.937469 873.149575 \n",
+ "700 538.0 881.0 538.150103 880.543866 538.150575 880.543272 \n",
+ "701 2208.0 934.0 2208.233234 934.266726 2208.233617 934.266633 \n",
"\n",
- " Int Bgnd Overlap Fit X ... Fit 1DY Bgnd \\\n",
- "0 1041.310345 153.965517 0.0 420.161536 ... 1093.499255 \n",
- "1 1086.103448 154.655172 0.0 405.918282 ... 1105.498848 \n",
- "2 1101.965517 154.448276 0.0 621.234621 ... 1096.191550 \n",
- "3 964.517241 156.275862 0.0 604.314062 ... 1109.461108 \n",
- "4 988.793103 156.689655 0.0 621.894784 ... 1116.886435 \n",
- "5 962.413793 154.620690 0.0 582.049414 ... 1097.642029 \n",
- "6 977.793103 155.689655 0.0 490.743492 ... 1103.469694 \n",
- "7 1053.137931 155.206897 0.0 543.021672 ... 1098.895944 \n",
- "8 1088.137931 155.206897 0.0 550.272692 ... 1098.811295 \n",
- "9 989.655172 155.482759 0.0 721.666425 ... 1093.719571 \n",
- "10 941.689655 156.034483 0.0 694.099169 ... 1095.696681 \n",
- "11 933.724138 156.586207 0.0 888.230272 ... 1116.847724 \n",
- "12 1017.379310 155.068966 0.0 754.196895 ... 1096.386558 \n",
- "13 1008.413793 155.620690 0.0 440.318131 ... 1109.284871 \n",
- "14 929.206897 156.310345 0.0 590.365254 ... 1114.259855 \n",
- "15 942.482759 155.724138 0.0 649.404782 ... 1102.171084 \n",
- "20 880.655172 156.482759 0.0 893.454657 ... 1116.600000 \n",
- "21 1076.344828 155.517241 0.0 458.838046 ... 1104.800000 \n",
- "22 897.689655 157.034483 0.0 470.497080 ... 1119.400000 \n",
- "23 1098.620690 154.931034 0.0 592.401505 ... 1094.118720 \n",
- "29 994.000000 155.000000 0.0 456.152251 ... 1106.767618 \n",
- "30 1036.241379 156.862069 0.0 255.318114 ... 1107.643370 \n",
- "31 1013.310345 156.965517 0.0 436.132729 ... 1129.200000 \n",
- "32 982.310345 154.965517 0.0 577.742883 ... 1095.675132 \n",
- "33 905.137931 155.206897 0.0 649.318737 ... 1097.460896 \n",
- "34 1057.758621 157.137931 0.0 655.724105 ... 1114.703701 \n",
- "35 1044.965517 157.448276 0.0 748.066741 ... 1124.719141 \n",
- "36 1087.344828 156.517241 0.0 841.535961 ... 1109.706764 \n",
- "37 1112.137931 156.206897 0.0 276.163618 ... 1111.915912 \n",
- "38 982.000000 157.000000 0.0 571.214509 ... 1109.820157 \n",
- ".. ... ... ... ... ... ... \n",
- "671 1086.137931 156.206897 0.0 632.908006 ... 1110.268764 \n",
- "672 1057.793103 157.689655 0.0 645.909817 ... 1124.857383 \n",
- "673 1082.689655 156.034483 0.0 700.074170 ... 1099.126282 \n",
- "674 1075.241379 156.862069 0.0 725.075456 ... 1119.261458 \n",
- "675 981.310345 155.965517 0.0 755.446807 ... 1106.191859 \n",
- "676 1052.689655 156.034483 0.0 764.588041 ... 1107.924573 \n",
- "677 1048.655172 156.482759 0.0 781.709838 ... 1108.199904 \n",
- "678 1042.620690 156.931034 0.0 795.340905 ... 1109.292493 \n",
- "679 990.206897 156.310345 0.0 396.236259 ... 1111.365832 \n",
- "680 1151.551724 154.827586 0.0 448.366521 ... 1100.302468 \n",
- "682 1023.793103 156.689655 0.0 595.178536 ... 1115.942244 \n",
- "683 971.793103 157.689655 0.0 858.687902 ... 1119.588686 \n",
- "684 1135.137931 157.206897 0.0 460.247098 ... 1117.957937 \n",
- "685 1068.344828 155.517241 0.0 587.482919 ... 1112.711838 \n",
- "686 1066.068966 156.103448 0.0 604.643507 ... 1112.445867 \n",
- "687 1009.620690 155.931034 0.0 702.957444 ... 1114.940614 \n",
- "688 1007.517241 157.275862 0.0 515.551501 ... 1120.240436 \n",
- "689 1060.586207 156.379310 0.0 549.044910 ... 1107.498102 \n",
- "690 1101.000000 157.000000 0.0 691.834696 ... 1110.947158 \n",
- "691 1177.448276 157.172414 0.0 831.437672 ... 1119.009857 \n",
- "692 825.068966 156.103448 0.0 847.916431 ... 1111.058926 \n",
- "693 1093.310345 157.965517 0.0 409.419252 ... 1117.148392 \n",
- "694 980.517241 156.275862 0.0 485.997866 ... 1111.499027 \n",
- "695 959.586207 156.379310 0.0 582.174969 ... 1106.676526 \n",
- "696 1038.103448 157.655172 0.0 676.977150 ... 1113.565348 \n",
- "697 1109.137931 155.206897 0.0 790.531189 ... 1110.282291 \n",
- "698 1064.551724 157.827586 0.0 702.317044 ... 1118.654296 \n",
- "699 1135.000000 156.000000 0.0 625.111769 ... 1102.408133 \n",
- "700 1010.482759 158.724138 0.0 512.170327 ... 1131.587287 \n",
- "701 1033.000000 157.000000 0.0 381.341079 ... 1128.232664 \n",
+ " Int Bgnd Overlap Fit X ... Fit 1DY Amp \\\n",
+ "0 929.482759 156.724138 0.0 273.611529 ... 458.238985 \n",
+ "1 1088.965517 157.448276 0.0 561.670084 ... 538.669693 \n",
+ "2 994.689655 156.034483 0.0 580.952632 ... 474.944450 \n",
+ "3 1078.758621 156.137931 0.0 661.210969 ... 573.873523 \n",
+ "4 1114.344828 155.517241 0.0 688.928409 ... 573.285018 \n",
+ ".. ... ... ... ... ... ... \n",
+ "697 1011.482759 156.724138 0.0 443.672897 ... 488.622705 \n",
+ "698 1139.068966 155.103448 0.0 495.364856 ... 555.487871 \n",
+ "699 1039.551724 155.827586 0.0 679.920239 ... 527.393239 \n",
+ "700 879.655172 159.482759 0.0 538.100846 ... 470.865194 \n",
+ "701 930.793103 155.689655 0.0 2208.290804 ... 485.761771 \n",
"\n",
- " Fit 1DY Amp Fit 1DY Sigma Fit 1DY Err Y Fit 1DY Err Bgnd \\\n",
- "0 508.252606 0.312139 0.103103 26.253539 \n",
- "1 514.754031 0.331926 0.101591 28.355951 \n",
- "2 538.829575 0.241266 4.316591 36.436919 \n",
- "3 474.886648 0.630456 0.148201 57.304560 \n",
- "4 481.397476 0.506071 0.086492 29.975207 \n",
- "5 488.252904 0.538629 0.084605 40.812566 \n",
- "6 500.356070 0.399609 0.100550 32.163226 \n",
- "7 529.864196 0.418802 0.120588 36.819578 \n",
- "8 558.660467 0.456903 0.128809 49.949282 \n",
- "9 514.481501 0.483063 0.079516 31.786930 \n",
- "10 510.561617 0.541708 0.074494 31.902716 \n",
- "11 453.032965 0.398586 0.128360 32.448946 \n",
- "12 535.147048 0.425993 0.105169 37.418580 \n",
- "13 484.502950 0.495199 0.116470 40.360772 \n",
- "14 456.090506 0.400615 0.138576 38.189751 \n",
- "15 492.901205 0.507314 0.120197 40.417481 \n",
- "20 427.900000 0.018695 0.000000 0.000000 \n",
- "21 526.200000 0.077331 0.000000 0.000000 \n",
- "22 417.100000 0.136043 0.000000 0.000000 \n",
- "23 625.084479 0.481506 0.130866 55.457228 \n",
- "29 478.313337 0.377102 0.152233 33.858355 \n",
- "30 544.748219 0.554336 0.084614 45.102855 \n",
- "31 462.800000 0.006187 0.000000 0.000000 \n",
- "32 497.137039 0.461906 0.062738 21.163969 \n",
- "33 457.386865 0.437609 0.095305 27.500346 \n",
- "34 545.537046 0.499389 0.094650 35.552546 \n",
- "35 493.483006 0.306299 0.405806 46.439272 \n",
- "36 571.026327 0.519580 0.061840 32.836968 \n",
- "37 544.794308 0.457416 0.099840 36.496358 \n",
- "38 497.629452 0.412375 0.097737 29.574554 \n",
- ".. ... ... ... ... \n",
- "671 557.059327 0.419958 0.108895 37.893910 \n",
- "672 526.499159 0.469312 0.111436 38.863205 \n",
- "673 581.058335 0.625984 0.094013 44.317610 \n",
- "674 538.584899 0.550901 0.137903 54.994456 \n",
- "675 503.829576 0.648917 0.108616 42.889716 \n",
- "676 521.763995 0.432075 0.106922 35.637831 \n",
- "677 561.800336 0.513844 0.133115 51.083793 \n",
- "678 550.476276 0.471851 0.106863 39.062195 \n",
- "679 490.719588 0.453774 0.159617 50.872140 \n",
- "680 578.441361 0.426965 0.110783 38.354568 \n",
- "682 491.202145 0.375539 0.232090 50.236569 \n",
- "683 482.939599 0.487928 0.106033 34.922005 \n",
- "684 551.147219 0.373745 0.089110 29.211597 \n",
- "685 505.008565 0.292056 0.733994 39.967273 \n",
- "686 518.939464 0.401281 0.120874 35.771493 \n",
- "687 471.207852 0.395244 0.156519 47.083007 \n",
- "688 487.158475 0.372125 0.151717 40.879181 \n",
- "689 541.756643 0.440809 0.079297 33.813444 \n",
- "690 580.684946 0.432508 0.091075 34.473980 \n",
- "691 575.965501 0.325518 0.293754 46.448215 \n",
- "692 410.793758 0.408191 0.151318 38.109252 \n",
- "693 570.980628 0.396708 0.107102 38.754794 \n",
- "694 482.253404 0.366533 0.154727 30.304850 \n",
- "695 501.632179 0.546339 0.083071 39.160233 \n",
- "696 534.021281 0.437600 0.108556 38.770061 \n",
- "697 530.011981 0.372053 0.164724 37.333326 \n",
- "698 525.209962 0.394913 0.114720 33.448964 \n",
- "699 587.071535 0.411462 0.144985 52.731564 \n",
- "700 485.944494 0.448043 0.081109 31.996918 \n",
- "701 477.685675 0.383153 0.182186 43.237689 \n",
+ " Fit 1DY Sigma Fit 1DY Bgnd Fit 1DY Err Y Fit 1DY Err Amp \\\n",
+ "0 0.453043 1114.074576 0.088090 56.627072 \n",
+ "1 0.389961 1118.094373 0.075424 36.920352 \n",
+ "2 0.250000 1112.587300 0.000000 0.000000 \n",
+ "3 0.528529 1097.178994 0.070953 61.358638 \n",
+ "4 0.445840 1096.918566 0.077442 59.672009 \n",
+ ".. ... ... ... ... \n",
+ "697 0.250000 1114.964941 0.000000 0.000000 \n",
+ "698 0.365816 1107.574894 0.185802 80.100534 \n",
+ "699 0.494927 1105.601932 0.081214 65.228055 \n",
+ "700 0.608059 1127.181411 0.127116 74.724424 \n",
+ "701 0.467539 1097.068066 0.098517 67.829987 \n",
"\n",
- " Fit 1DY Err Amp Fit 1DY Err Sigma Fit 1DY Fnorm Fit 1DY Outcome \\\n",
- "0 60.158020 0.069012 52.504719 1.0 \n",
- "1 64.984595 0.070844 56.703423 1.0 \n",
- "2 91.550083 32.959735 67.112929 1.0 \n",
- "3 154.585735 0.295398 96.603504 1.0 \n",
- "4 73.447801 0.135327 56.630157 1.0 \n",
- "5 108.042770 0.243970 70.634564 1.0 \n",
- "6 73.918261 0.077556 64.180041 1.0 \n",
- "7 86.817982 0.182875 71.991010 1.0 \n",
- "8 122.295460 0.258280 94.435836 1.0 \n",
- "9 79.623711 0.176833 58.737061 1.0 \n",
- "10 82.245723 0.159986 57.088848 1.0 \n",
- "11 75.042754 0.141255 64.440571 1.0 \n",
- "12 86.223485 0.081596 74.516921 1.0 \n",
- "13 98.674259 0.188192 76.414441 1.0 \n",
- "14 87.945946 0.124043 76.088707 1.0 \n",
- "15 95.191889 0.107709 79.101274 1.0 \n",
- "20 0.000000 0.000000 67.000362 1.0 \n",
- "21 0.000000 0.000000 89.875352 1.0 \n",
- "22 0.000000 0.000000 60.784475 1.0 \n",
- "23 129.617053 0.116519 109.216285 1.0 \n",
- "29 78.557026 0.208666 67.069470 1.0 \n",
- "30 120.113679 0.234642 77.432071 1.0 \n",
- "31 0.000000 0.000000 57.055895 1.0 \n",
- "32 49.095959 0.051086 41.928703 1.0 \n",
- "33 64.020880 0.101128 54.330325 1.0 \n",
- "34 85.326069 0.120142 68.465884 1.0 \n",
- "35 106.569395 0.470930 92.771266 1.0 \n",
- "36 85.551982 0.168772 58.012925 1.0 \n",
- "37 84.710523 0.085531 72.273027 1.0 \n",
- "38 68.310271 0.094148 58.788831 1.0 \n",
- ".. ... ... ... ... \n",
- "671 87.563318 0.101660 75.301427 1.0 \n",
- "672 91.407331 0.122481 76.144492 1.0 \n",
- "673 119.068509 0.185341 75.148472 1.0 \n",
- "674 137.690527 0.213442 101.672030 1.0 \n",
- "675 116.212026 0.204382 71.834789 1.0 \n",
- "676 82.530928 0.100346 70.697827 1.0 \n",
- "677 120.281822 0.113699 99.998052 1.0 \n",
- "678 92.162224 0.122435 76.337030 1.0 \n",
- "679 118.915461 0.169476 100.176423 1.0 \n",
- "680 91.260271 0.183982 74.420448 1.0 \n",
- "682 119.940035 0.523692 97.188684 1.0 \n",
- "683 81.618647 0.090380 68.776410 1.0 \n",
- "684 67.036329 0.069593 58.354918 1.0 \n",
- "685 93.206055 1.681534 78.850929 1.0 \n",
- "686 82.680614 0.128249 71.069433 1.0 \n",
- "687 108.155295 0.118587 93.985862 1.0 \n",
- "688 93.887567 0.133204 81.612991 1.0 \n",
- "689 85.527737 0.249038 61.834024 1.0 \n",
- "690 79.672233 0.078615 68.497810 1.0 \n",
- "691 106.959308 0.402060 92.545915 1.0 \n",
- "692 87.861849 0.137417 75.861360 1.0 \n",
- "693 89.053756 0.083175 77.341988 1.0 \n",
- "694 70.844097 0.264721 59.672041 1.0 \n",
- "695 103.268304 0.218174 68.123255 1.0 \n",
- "696 89.516732 0.086456 77.089727 1.0 \n",
- "697 87.336348 0.277827 73.469657 1.0 \n",
- "698 77.250742 0.122625 66.496099 1.0 \n",
- "699 121.606810 0.130626 104.947206 1.0 \n",
- "700 81.168340 0.252711 58.325609 1.0 \n",
- "701 100.115573 0.228040 85.784511 1.0 \n",
+ " Fit 1DY Err Sigma Fit 1DY Err Bgnd Fit 1DY Fnorm Fit 1DY Outcome \\\n",
+ "0 13.336450 24.193443 47.590981 1.0 \n",
+ "1 -1.051179 15.039644 28.362212 1.0 \n",
+ "2 -0.000000 0.000000 44.684418 1.0 \n",
+ "3 0.625010 25.122727 47.609856 1.0 \n",
+ "4 -17.099031 23.541572 42.950304 1.0 \n",
+ ".. ... ... ... ... \n",
+ "697 -0.000000 0.000000 45.393635 1.0 \n",
+ "698 -1.237257 34.342047 67.744320 1.0 \n",
+ "699 0.894261 27.625279 53.952159 1.0 \n",
+ "700 1.117238 27.908166 47.554277 1.0 \n",
+ "701 2.816057 28.752354 56.194272 1.0 \n",
"\n",
" Fit 1DY StdErr \n",
- "0 10.908338 \n",
- "1 16.114720 \n",
- "2 6.801699 \n",
- "3 39.398138 \n",
- "4 5.423303 \n",
- "5 12.172359 \n",
- "6 12.909384 \n",
- "7 20.330219 \n",
- "8 18.083250 \n",
- "9 10.614651 \n",
- "10 11.156777 \n",
- "11 13.476929 \n",
- "12 5.818569 \n",
- "13 29.027280 \n",
- "14 18.673171 \n",
- "15 21.185688 \n",
- "20 11.360751 \n",
- "21 25.421775 \n",
- "22 26.889899 \n",
- "23 27.847612 \n",
- "29 28.363174 \n",
- "30 18.166078 \n",
- "31 18.697593 \n",
- "32 9.488707 \n",
- "33 15.887303 \n",
- "34 22.044265 \n",
- "35 17.643117 \n",
- "36 15.803290 \n",
- "37 4.892489 \n",
- "38 10.853542 \n",
+ "0 24.500075 \n",
+ "1 9.266898 \n",
+ "2 13.463239 \n",
+ "3 16.828770 \n",
+ "4 8.064309 \n",
".. ... \n",
- "671 16.229361 \n",
- "672 9.498773 \n",
- "673 26.293033 \n",
- "674 39.152334 \n",
- "675 27.995577 \n",
- "676 15.415361 \n",
- "677 32.577847 \n",
- "678 12.250614 \n",
- "679 17.744427 \n",
- "680 12.151409 \n",
- "682 21.304024 \n",
- "683 11.378250 \n",
- "684 15.262243 \n",
- "685 17.654968 \n",
- "686 23.951140 \n",
- "687 17.707398 \n",
- "688 22.523244 \n",
- "689 13.432322 \n",
- "690 18.246232 \n",
- "691 11.369412 \n",
- "692 16.577163 \n",
- "693 24.419955 \n",
- "694 18.483093 \n",
- "695 14.400256 \n",
- "696 5.221564 \n",
- "697 15.321962 \n",
- "698 16.210270 \n",
- "699 11.485270 \n",
- "700 7.451864 \n",
- "701 30.701460 \n",
+ "697 18.256193 \n",
+ "698 17.947386 \n",
+ "699 18.435903 \n",
+ "700 18.455631 \n",
+ "701 14.521217 \n",
"\n",
- "[685 rows x 44 columns]"
+ "[692 rows x 44 columns]"
]
},
- "execution_count": 54,
+ "execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
@@ -2191,29 +761,27 @@
},
{
"cell_type": "code",
- "execution_count": 55,
+ "execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- ""
+ ""
]
},
- "execution_count": 55,
+ "execution_count": 17,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
- "image/png": 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\n",
+ "image/png": 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",
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