Inspect DECalS GZ Dataset¶

gz_decals_volunteers_ab.csv and gz_decals_volunteers_c.csv avaliable at https://zenodo.org/record/4196267#.YE0oZ69KiUm

In [7]:

import numpy as np
import pandas as pd

f_ab = pd.read_csv("gz_decals_volunteers_ab.csv")
f_c = pd.read_csv("gz_decals_volunteers_c.csv")

print("Length of gz_decals_volunteers_ab.csv: ", len(f_ab))
print("Length of gz_decals_volunteers_c.csv: ", len(f_c))

Length of gz_decals_volunteers_ab.csv:  92960
Length of gz_decals_volunteers_c.csv:  253286

In [20]:

# overlaps between ab and c
print(np.sum(f_ab["in_gzd_c"]))
print(np.sum(f_c["in_gzd_ab"]))

32457
32457

In [6]:

f_ab.columns, f_c.columns

Out[6]:

(Index(['iauname', 'ra', 'dec', 'redshift', 'elpetro_absmag_r', 'sersic_nmgy_r',
        'petro_th50', 'petro_th90', 'petro_theta', 'upload_group',
        'active_learning_on', 'in_gzd_c', 'jpeg_loc',
        'smooth-or-featured_total-votes', 'smooth-or-featured_smooth',
        'smooth-or-featured_smooth_fraction',
        'smooth-or-featured_featured-or-disk',
        'smooth-or-featured_featured-or-disk_fraction',
        'smooth-or-featured_artifact', 'smooth-or-featured_artifact_fraction',
        'how-rounded_total-votes', 'how-rounded_completely',
        'how-rounded_completely_fraction', 'how-rounded_in-between',
        'how-rounded_in-between_fraction', 'how-rounded_cigar-shaped',
        'how-rounded_cigar-shaped_fraction', 'disk-edge-on_total-votes',
        'disk-edge-on_yes', 'disk-edge-on_yes_fraction', 'disk-edge-on_no',
        'disk-edge-on_no_fraction', 'edge-on-bulge_total-votes',
        'edge-on-bulge_rounded', 'edge-on-bulge_rounded_fraction',
        'edge-on-bulge_boxy', 'edge-on-bulge_boxy_fraction',
        'edge-on-bulge_none', 'edge-on-bulge_none_fraction', 'bar_total-votes',
        'bar_yes', 'bar_yes_fraction', 'bar_no', 'bar_no_fraction',
        'has-spiral-arms_total-votes', 'has-spiral-arms_yes',
        'has-spiral-arms_yes_fraction', 'has-spiral-arms_no',
        'has-spiral-arms_no_fraction', 'spiral-winding_total-votes',
        'spiral-winding_tight', 'spiral-winding_tight_fraction',
        'spiral-winding_medium', 'spiral-winding_medium_fraction',
        'spiral-winding_loose', 'spiral-winding_loose_fraction',
        'spiral-arm-count_total-votes', 'spiral-arm-count_1',
        'spiral-arm-count_1_fraction', 'spiral-arm-count_2',
        'spiral-arm-count_2_fraction', 'spiral-arm-count_3',
        'spiral-arm-count_3_fraction', 'spiral-arm-count_4',
        'spiral-arm-count_4_fraction', 'spiral-arm-count_more-than-4',
        'spiral-arm-count_more-than-4_fraction', 'bulge-size_total-votes',
        'bulge-size_none', 'bulge-size_none_fraction', 'bulge-size_obvious',
        'bulge-size_obvious_fraction', 'bulge-size_dominant',
        'bulge-size_dominant_fraction', 'merging_total-votes', 'merging_merger',
        'merging_merger_fraction', 'merging_tidal-debris',
        'merging_tidal-debris_fraction', 'merging_both',
        'merging_both_fraction', 'merging_neither', 'merging_neither_fraction'],
       dtype='object'),
 Index(['iauname', 'ra', 'dec', 'redshift', 'elpetro_absmag_r', 'sersic_nmgy_r',
        'petro_th50', 'petro_th90', 'petro_theta', 'upload_group',
        'active_learning_on', 'in_gzd_ab', 'png_loc',
        'smooth-or-featured_total-votes', 'smooth-or-featured_smooth',
        'smooth-or-featured_smooth_fraction',
        'smooth-or-featured_featured-or-disk',
        'smooth-or-featured_featured-or-disk_fraction',
        'smooth-or-featured_artifact', 'smooth-or-featured_artifact_fraction',
        'disk-edge-on_total-votes', 'disk-edge-on_yes',
        'disk-edge-on_yes_fraction', 'disk-edge-on_no',
        'disk-edge-on_no_fraction', 'has-spiral-arms_total-votes',
        'has-spiral-arms_yes', 'has-spiral-arms_yes_fraction',
        'has-spiral-arms_no', 'has-spiral-arms_no_fraction', 'bar_total-votes',
        'bar_strong', 'bar_strong_fraction', 'bar_weak', 'bar_weak_fraction',
        'bar_no', 'bar_no_fraction', 'bulge-size_total-votes',
        'bulge-size_dominant', 'bulge-size_dominant_fraction',
        'bulge-size_large', 'bulge-size_large_fraction', 'bulge-size_moderate',
        'bulge-size_moderate_fraction', 'bulge-size_small',
        'bulge-size_small_fraction', 'bulge-size_none',
        'bulge-size_none_fraction', 'how-rounded_total-votes',
        'how-rounded_round', 'how-rounded_round_fraction',
        'how-rounded_in-between', 'how-rounded_in-between_fraction',
        'how-rounded_cigar-shaped', 'how-rounded_cigar-shaped_fraction',
        'edge-on-bulge_total-votes', 'edge-on-bulge_boxy',
        'edge-on-bulge_boxy_fraction', 'edge-on-bulge_none',
        'edge-on-bulge_none_fraction', 'edge-on-bulge_rounded',
        'edge-on-bulge_rounded_fraction', 'spiral-winding_total-votes',
        'spiral-winding_tight', 'spiral-winding_tight_fraction',
        'spiral-winding_medium', 'spiral-winding_medium_fraction',
        'spiral-winding_loose', 'spiral-winding_loose_fraction',
        'spiral-arm-count_total-votes', 'spiral-arm-count_1',
        'spiral-arm-count_1_fraction', 'spiral-arm-count_2',
        'spiral-arm-count_2_fraction', 'spiral-arm-count_3',
        'spiral-arm-count_3_fraction', 'spiral-arm-count_4',
        'spiral-arm-count_4_fraction', 'spiral-arm-count_more-than-4',
        'spiral-arm-count_more-than-4_fraction', 'spiral-arm-count_cant-tell',
        'spiral-arm-count_cant-tell_fraction', 'merging_total-votes',
        'merging_none', 'merging_none_fraction', 'merging_minor-disturbance',
        'merging_minor-disturbance_fraction', 'merging_major-disturbance',
        'merging_major-disturbance_fraction', 'merging_merger',
        'merging_merger_fraction'],
       dtype='object'))

In [33]:

import numpy as np
import pandas as pd

f_ab = pd.read_csv("gz_decals_volunteers_ab.csv")
result = np.genfromtxt("edges_result_c.csv")
len(np.where(result[f_ab["in_gzd_c"]] == 0)[0])

Out[33]:

In [11]:

import matplotlib.pyplot as plt
from mw_plot import mw_radec

fig = plt.figure(figsize=(10, 5))
ax = fig.gca()
ax.scatter(f["ra"], f["dec"], c=f["redshift"], s=1)
ra, dec = mw_radec()
ax.plot(ra, dec, c="k", ls="--")
ax.set_title("gz_decals_volunteers_ab", fontsize=20)
ax.set_xlim(0, 360)
ax.set_ylim(-90, 90)
ax.set_xlabel("RA", fontsize=20)
ax.set_ylabel("DEC", fontsize=20)
ax.minorticks_on()
ax.tick_params(labelsize=15, width=2, length=10, which="major")
ax.tick_params(width=1, length=5, which="minor")

fig = plt.figure(figsize=(10, 5))
ax = fig.gca()
ax.scatter(f2["ra"], f2["dec"], c=f2["redshift"], s=1)
ra, dec = mw_radec()
ax.plot(ra, dec, c="k", ls="--")
ax.set_title("gz_decals_volunteers_c", fontsize=20)
ax.set_xlim(0, 360)
ax.set_ylim(-90, 90)
ax.set_xlabel("RA", fontsize=20)
ax.set_ylabel("DEC", fontsize=20)
ax.minorticks_on()
ax.tick_params(labelsize=15, width=2, length=10, which="major")
ax.tick_params(width=1, length=5, which="minor")


fig = plt.figure(figsize=(10, 5))
ax = fig.gca()
ax.scatter(
    f["ra"][f["in_gzd_c"]], f["dec"][f["in_gzd_c"]], c=f["redshift"][f["in_gzd_c"]], s=1
)
ra, dec = mw_radec()
ax.plot(ra, dec, c="k", ls="--")
ax.set_title("gz_decals_volunteers_* overlaps", fontsize=20)
ax.set_xlim(0, 360)
ax.set_ylim(-90, 90)
ax.set_xlabel("RA", fontsize=20)
ax.set_ylabel("DEC", fontsize=20)
ax.minorticks_on()
ax.tick_params(labelsize=15, width=2, length=10, which="major")
ax.tick_params(width=1, length=5, which="minor")

In [16]:

fig = plt.figure(figsize=(10, 5))
ax = fig.gca()
ax.hist(f["smooth-or-featured_total-votes"], range=(0, 70), bins=35, alpha=0.5)
ax.hist(f2["smooth-or-featured_total-votes"], range=(0, 70), bins=35, alpha=0.5)

Out[16]:

(array([1.45100e+03, 8.11100e+03, 1.42093e+05, 1.72050e+04, 9.41300e+03,
        5.96400e+03, 4.10100e+03, 2.58700e+03, 1.24100e+03, 5.86000e+02,
        2.91000e+02, 2.15000e+02, 2.46000e+02, 2.21000e+02, 2.24000e+02,
        4.04000e+02, 1.30800e+03, 3.03300e+03, 6.85700e+03, 2.23840e+04,
        1.20200e+04, 8.18000e+02, 5.58000e+02, 5.71000e+02, 6.61000e+02,
        5.32000e+02, 4.47000e+02, 2.64000e+02, 1.69000e+02, 1.16000e+02,
        9.20000e+01, 9.80000e+01, 7.70000e+01, 9.40000e+01, 1.43000e+02]),
 array([ 0.,  2.,  4.,  6.,  8., 10., 12., 14., 16., 18., 20., 22., 24.,
        26., 28., 30., 32., 34., 36., 38., 40., 42., 44., 46., 48., 50.,
        52., 54., 56., 58., 60., 62., 64., 66., 68., 70.]),
 <BarContainer object of 35 artists>)

In [39]:

import numpy as np
import pandas as pd

f = pd.read_csv("gz_decals_volunteers_c.csv")
result = np.genfromtxt("edges_result_c.csv")
len(np.where(result[f["in_gzd_ab"]] == 0)[0])

Out[39]:

In [40]:

np.sum(f2["smooth-or-featured_total-votes"][result == 0] > 20)

Out[40]:

Inspect BCNN results¶

Source: https://arxiv.org/pdf/2102.08414.pdf

In [6]:

import numpy as np
import pandas as pd

f_bcnn = pd.read_parquet("gz_decals_auto_posteriors.parquet")
f_bcnn

Out[6]:

	iauname	smooth-or-featured_smooth_concentration	smooth-or-featured_featured-or-disk_concentration	smooth-or-featured_artifact_concentration	disk-edge-on_yes_concentration	disk-edge-on_no_concentration	has-spiral-arms_yes_concentration	has-spiral-arms_no_concentration	bar_strong_concentration	bar_weak_concentration	...	disk-edge-on_proportion_volunteers_asked	has-spiral-arms_proportion_volunteers_asked	bar_proportion_volunteers_asked	bulge-size_proportion_volunteers_asked	how-rounded_proportion_volunteers_asked	edge-on-bulge_proportion_volunteers_asked	spiral-winding_proportion_volunteers_asked	spiral-arm-count_proportion_volunteers_asked	merging_proportion_volunteers_asked	file_loc
0	J223253.27-005423.9	[18.8731, 22.7141, 20.7146, 18.2101, 20.091, 1...	[39.0552, 51.8402, 43.3618, 49.3892, 43.879, 4...	[3.5365, 3.58, 3.7669, 3.2913, 3.9583, 3.2235,...	[3.501, 5.4355, 4.2553, 4.0008, 4.7009, 5.2416...	[42.9519, 36.9419, 42.9178, 57.9632, 34.6256, ...	[5.0956, 4.2247, 4.4058, 8.8174, 4.3745, 3.958...	[4.0325, 6.3041, 5.5175, 3.8162, 5.7515, 5.471...	[10.8883, 22.3576, 15.8604, 19.8254, 20.8928, ...	[6.6697, 6.7961, 7.1283, 9.6206, 6.4508, 5.426...	...	0.661460	0.590545	0.590545	0.590545	0.287243	0.070915	0.285699	0.285699	1.0	dr5/png/J223/J223253.27-005423.9.png
1	J223445.65-010456.2	[100.2998, 100.9084, 98.8625, 96.6109, 95.5195...	[11.3494, 11.9764, 11.8131, 13.3513, 10.6898, ...	[21.192, 21.4996, 19.7249, 21.2485, 21.661, 22...	[7.3492, 11.0223, 7.2616, 6.4169, 5.3163, 6.09...	[100.9746, 100.9995, 100.9881, 93.2174, 99.654...	[1.066, 1.0411, 1.1538, 1.1333, 1.1911, 1.0931...	[48.0764, 67.1999, 42.7396, 49.795, 34.2735, 4...	[1.0816, 1.021, 1.0374, 1.2873, 1.2634, 1.0353...	[2.2426, 1.9689, 2.1154, 3.1913, 2.7703, 1.957...	...	0.092655	0.086753	0.086753	0.086753	0.736395	0.005903	0.002457	0.002457	1.0	dr5/png/J223/J223445.65-010456.2.png
2	J223515.21-003519.5	[100.6286, 99.8829, 100.1223, 99.6535, 99.7411...	[9.5877, 12.1126, 10.7685, 10.212, 9.5006, 11....	[13.8786, 12.557, 12.7363, 13.4321, 13.8922, 1...	[7.2084, 7.5475, 9.4287, 7.4908, 8.8195, 6.983...	[99.0, 100.9875, 100.8836, 99.2058, 100.2806, ...	[1.1055, 1.1696, 1.1697, 1.2031, 1.174, 1.2169...	[43.6163, 41.2119, 40.3802, 36.7099, 41.3417, ...	[1.3803, 1.0141, 1.029, 1.5132, 1.1614, 1.1021...	[2.8964, 1.9269, 2.0382, 3.2041, 2.4041, 2.269...	...	0.090191	0.083193	0.083193	0.083193	0.802817	0.006998	0.002955	0.002955	1.0	dr5/png/J223/J223515.21-003519.5.png
3	J223402.99+001117.3	[71.2866, 82.2588, 75.9155, 66.3959, 77.7713, ...	[6.4053, 6.2552, 5.9803, 5.4375, 6.469, 5.3874...	[8.545, 8.136, 10.5003, 9.1182, 7.9304, 9.0336...	[7.1974, 12.0605, 6.5911, 6.3696, 11.9035, 4.4...	[28.5018, 36.8346, 24.632, 21.1756, 52.8328, 2...	[3.0817, 2.7644, 2.375, 2.474, 4.4556, 2.6432,...	[14.0236, 14.9046, 19.2895, 11.8857, 14.4581, ...	[2.9977, 2.5995, 2.9434, 2.555, 2.4383, 2.8204...	[6.9935, 7.3001, 6.3014, 6.4472, 9.795, 5.5185...	...	0.084932	0.070696	0.070696	0.070696	0.818003	0.014236	0.016018	0.016018	1.0	dr5/png/J223/J223402.99+001117.3.png
4	J223710.17-005700.4	[43.4332, 41.4422, 35.893, 50.8412, 40.0915, 3...	[11.328, 14.0638, 10.8818, 15.8887, 11.1832, 1...	[8.1987, 6.5369, 7.4544, 8.9742, 8.0949, 5.511...	[4.7779, 4.7764, 3.994, 4.4643, 5.0072, 3.6229...	[44.1802, 40.3991, 36.5893, 37.2032, 35.2251, ...	[2.5664, 3.0394, 2.5884, 2.7524, 2.4275, 3.717...	[10.6808, 9.1973, 8.9464, 14.7528, 8.8792, 9.3...	[1.4609, 1.675, 1.5845, 1.8152, 1.6327, 1.4944...	[6.4947, 6.9151, 6.4102, 7.1318, 5.835, 8.1248...	...	0.235732	0.213149	0.213149	0.213149	0.655672	0.022583	0.051664	0.051664	1.0	dr5/png/J223/J223710.17-005700.4.png
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
32384	J001337.43+000452.1	[67.7433, 84.424, 84.8966, 83.9573, 86.8592, 7...	[11.562, 13.4767, 13.9497, 10.9446, 12.2329, 2...	[9.6548, 6.8379, 7.114, 7.8292, 8.6322, 6.4615...	[16.3985, 20.8138, 19.8201, 19.7369, 23.5123, ...	[9.4029, 16.2425, 18.4072, 18.9661, 23.1136, 2...	[1.7114, 1.691, 1.9243, 1.4504, 1.6875, 2.2791...	[20.6379, 23.9128, 21.7502, 23.3827, 23.8051, ...	[2.0453, 1.4662, 1.6341, 1.4274, 1.749, 1.9699...	[4.3362, 4.3049, 4.6915, 3.3292, 4.1179, 5.237...	...	0.153957	0.082965	0.082965	0.082965	0.777463	0.070993	0.006416	0.006416	1.0	dr1_dr2/png/dr1/standard/J001337.43+000452.1_s...
32395	J223508.28+011340.5	[68.4051, 85.4626, 91.1203, 83.9974, 83.508, 8...	[16.8923, 18.2325, 16.4421, 15.4108, 15.5776, ...	[9.8857, 11.059, 10.0127, 9.1231, 10.6405, 7.9...	[6.0075, 6.854, 5.5798, 5.4997, 6.2705, 5.6255...	[88.8639, 99.5492, 100.1795, 97.721, 96.8299, ...	[1.9275, 1.7466, 1.5295, 1.8133, 1.8386, 1.525...	[17.8638, 29.1938, 26.4577, 21.0713, 22.8124, ...	[2.3162, 1.3677, 1.3124, 1.63, 1.8459, 1.2441,...	[5.9198, 3.8474, 4.2065, 5.7181, 5.03, 4.1204,...	...	0.150940	0.141512	0.141512	0.141512	0.769009	0.009428	0.009174	0.009174	1.0	dr1_dr2/png/dr1/standard/J223508.28+011340.5_s...
32400	J213415.99+004744.7	[53.6906, 66.3875, 75.5105, 86.4555, 77.1451, ...	[5.7626, 5.8208, 6.8413, 5.107, 5.5284, 8.1889...	[11.6139, 11.4402, 11.1756, 12.6454, 16.0694, ...	[5.7782, 7.1751, 8.5044, 10.4739, 6.473, 7.818...	[68.8265, 59.3757, 82.0642, 85.2741, 61.355, 8...	[2.6144, 1.8933, 2.0671, 2.0869, 2.0434, 1.772...	[12.3967, 14.1108, 17.7524, 18.9317, 28.4264, ...	[1.7331, 1.8838, 1.6962, 1.6845, 1.8427, 1.473...	[5.8635, 4.8032, 5.5664, 5.2405, 5.1976, 4.421...	...	0.083774	0.075413	0.075413	0.075413	0.803327	0.008362	0.009586	0.009586	1.0	dr1_dr2/png/dr1/standard/J213415.99+004744.7_s...
32414	J001256.27+005121.3	[59.7611, 53.7724, 68.7907, 58.497, 56.2669, 6...	[6.9416, 7.8052, 11.1623, 7.1202, 6.087, 8.549...	[14.5371, 6.835, 10.0627, 15.3858, 16.9394, 12...	[6.2388, 8.3735, 10.6855, 8.4419, 7.099, 11.69...	[22.8611, 28.084, 13.1044, 27.069, 28.8843, 36...	[2.4179, 2.5794, 1.6888, 2.579, 2.7639, 2.0147...	[14.8038, 6.7618, 16.5057, 18.3261, 15.2266, 1...	[2.2764, 1.6518, 2.2439, 2.0834, 2.7373, 1.949...	[5.9472, 6.2228, 4.6899, 6.3801, 6.457, 5.4855...	...	0.119879	0.076095	0.076095	0.076095	0.738587	0.043785	0.009014	0.009014	1.0	dr1_dr2/png/dr1/standard/J001256.27+005121.3_s...
32425	J234157.85+001630.4	[76.8053, 65.2413, 83.0316, 72.333, 78.9273, 7...	[2.9644, 4.5037, 4.8394, 4.8625, 3.1996, 5.657...	[12.5323, 9.9339, 15.3535, 16.4668, 14.6077, 1...	[7.105, 5.3481, 6.9868, 6.2596, 6.3779, 6.1305...	[93.9294, 74.0191, 82.483, 65.3796, 79.5011, 8...	[1.4772, 2.0824, 1.6304, 1.6615, 1.4618, 1.589...	[8.7991, 8.9731, 15.2782, 13.8636, 12.3599, 9....	[1.0777, 1.939, 1.9246, 1.9893, 1.6029, 1.6065...	[2.8861, 5.665, 4.6244, 5.4976, 3.9354, 3.7907...	...	0.053759	0.048387	0.048387	0.048387	0.776371	0.005371	0.006071	0.006071	1.0	dr1_dr2/png/dr1/standard/J234157.85+001630.4_s...

313789 rows × 80 columns