diff --git a/__pycache__/analysis_pmf.cpython-37.pyc b/__pycache__/analysis_pmf.cpython-37.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..0b4caf72889d24bf4325fbc9922b9fddd747dec8
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diff --git a/__pycache__/dyn_glm_chain_analysis.cpython-37.pyc b/__pycache__/dyn_glm_chain_analysis.cpython-37.pyc
index b4b56a55e7c7e3ff5cceb8da95a87d51c338cbac..740060e1aee1c905d0d6e98e7fb190b6806d36f6 100644
Binary files a/__pycache__/dyn_glm_chain_analysis.cpython-37.pyc and b/__pycache__/dyn_glm_chain_analysis.cpython-37.pyc differ
diff --git a/analysis_pmf.py b/analysis_pmf.py
index b07ba8a8e44f3f518bd19fc3d8e0b2a8aa2073e4..9a47f86eafebdd743f530024e2b605ce65a9b736 100644
--- a/analysis_pmf.py
+++ b/analysis_pmf.py
@@ -24,6 +24,17 @@ def pmf_type(pmf):
if __name__ == "__main__":
all_first_pmfs_typeless = pickle.load(open("all_first_pmfs_typeless.p", 'rb'))
all_pmfs = pickle.load(open("all_pmfs.p", 'rb'))
+ all_bias_flips = pickle.load(open("all_bias_flips.p", 'rb'))
+
+ # bias flips
+ plt.hist(all_bias_flips, bins=np.arange(0, max(all_bias_flips) + 1), color='grey', align='left')
+ plt.ylabel("# of mice")
+ plt.xlabel("Bias flips")
+ sns.despine()
+ plt.tight_layout()
+ plt.savefig("./meeting_figures/bias_flips.png")
+ plt.show()
+ quit()
fewer_states_side = []
for key in all_first_pmfs_typeless:
diff --git a/analysis_regression.py b/analysis_regression.py
index fe165ae1aded90bb19b0826ec79f7735284d2608..575f234c91dbf83c6f0082d3ac1aa05e743d765e 100644
--- a/analysis_regression.py
+++ b/analysis_regression.py
@@ -9,6 +9,7 @@ fontsize = 22
if __name__ == "__main__":
regressions = np.array(pickle.load(open("regressions.p", 'rb')))
+ regression_diffs = np.array(pickle.load(open("regression_diffs.p", 'rb')))
assert (regressions[:, 0] == np.sum(regressions[:, 2:], 1)).all()
@@ -50,3 +51,13 @@ if __name__ == "__main__":
plt.tight_layout()
plt.savefig("# of mice with regressions per type")
plt.show()
+
+ # histogram of regression diffs
+ plt.hist(regression_diffs, color='grey', bins=20)
+ plt.ylabel("# regressions", size=fontsize)
+ plt.xlabel("Reward rate diff", size=fontsize)
+
+ sns.despine()
+ plt.tight_layout()
+ plt.savefig("Regression diffs")
+ plt.show()
diff --git a/analysis_state_intros.py b/analysis_state_intros.py
index c00985af68fa992ce0fba0a42df16274370b7fa9..91b3250a7fee932274c8510534aa0e591912e9b7 100644
--- a/analysis_state_intros.py
+++ b/analysis_state_intros.py
@@ -6,8 +6,9 @@ fontsize = 16
def type_hist(data, title=''):
highest = int(data.max())
+ lowest = int(data.min())
if (data % 1 == 0).all():
- bins = np.arange(highest + 2) - 0.5
+ bins = np.arange(lowest, highest + 2) - 0.5
else:
bins = np.histogram(data)[1]
hist_max = 0
@@ -15,31 +16,35 @@ def type_hist(data, title=''):
hist_max = max(hist_max, np.histogram(data[:, i], bins)[0].max())
plt.subplot(3, 1, 1)
-
- if title != '':
- plt.title(title, size=fontsize + 4)
-
assert np.histogram(data[:, 0])[0].sum() == np.histogram(data[:, 0], bins)[0].sum()
plt.hist(data[:, 0], alpha=1/3, label="type 1", align='mid', bins=bins, color='grey')
- plt.xlim(-0.5, highest + 1)
+ plt.xlim(lowest - 0.5, highest + 1)
plt.ylim(0, hist_max + 1)
+ ax2 = plt.gca().twinx()
plt.ylabel("Type 1", size=fontsize)
+ ax2.set_yticks([])
plt.subplot(3, 1, 2)
assert np.histogram(data[:, 1])[0].sum() == np.histogram(data[:, 1], bins)[0].sum()
plt.hist(data[:, 1], alpha=1/3, label="type 2", align='mid', bins=bins, color='grey')
- plt.xlim(-0.5, highest + 1)
+ plt.xlim(lowest - 0.5, highest + 1)
plt.ylim(0, hist_max + 1)
+ ax2 = plt.gca().twinx()
plt.ylabel("Type 2", size=fontsize)
+ ax2.set_yticks([])
plt.subplot(3, 1, 3)
assert np.histogram(data[:, 2])[0].sum() == np.histogram(data[:, 2], bins)[0].sum()
plt.hist(data[:, 2], alpha=1/3, label="type 3", align='mid', bins=bins, color='grey')
- plt.xlim(-0.5, highest + 1)
+ plt.xlim(lowest - 0.5, highest + 1)
plt.ylim(0, hist_max + 1)
+ plt.xlabel(title, size=fontsize)
+ plt.ylabel("# of mice", size=fontsize)
+ ax2 = plt.gca().twinx()
plt.ylabel("Type 3", size=fontsize)
+ ax2.set_yticks([])
- # plt.legend()
+ plt.savefig(title)
plt.show()
diff --git a/behaviour_overview.py b/behaviour_overview.py
index 24180ed205a00a9cb7e864c39782d62c92f8d658..1a4899e65f47119af82ac806fd7babd966679c33 100644
--- a/behaviour_overview.py
+++ b/behaviour_overview.py
@@ -5,7 +5,7 @@ from one.api import ONE
import pickle
-show = 1
+show = 0
def progression(data, contrasts, progression_variable='feedback', windowsize=6, upper_bound=None, title=None):
# looks somewhat irregular, red dots are not in middle of bump they cause, this is because distribution of specific contrasts is not uniform
@@ -47,13 +47,13 @@ def progression(data, contrasts, progression_variable='feedback', windowsize=6,
# plt.title(title, size=22)
# plt.savefig("temp {}".format(title).replace('/', '_'))
# plt.close()
- # if progression_variable == 'rt':
- # means = data.groupby('signed_contrast').mean()['rt']
- # stds = data.groupby('signed_contrast').std()['rt']
- # plt.errorbar(means.index, means.values, stds.values)
- # plt.title(title, size=22)
- # plt.savefig("temp {}".format(title).replace('/', '_'))
- # plt.show()
+ if progression_variable == 'rt':
+ means = data.groupby('signed_contrast').mean()['rt']
+ stds = data.groupby('signed_contrast').sem()['rt']
+ plt.errorbar(means.index, means.values, stds.values)
+ plt.title(title, size=22)
+ plt.savefig("temp {}".format(title).replace('/', '_'))
+ plt.close()
dataset_types = ['choice', 'contrastLeft', 'contrastRight', \
diff --git a/canonical_infos.json b/canonical_infos.json
index 5f8da99817e18fb2831226f46d3018b12ba8b064..c0868bc5f9a444da61e2e4c5010c9c759000ff3c 100644
--- a/canonical_infos.json
+++ b/canonical_infos.json
@@ -1 +1 @@
-{"SWC_023": {"seeds": ["302", "312", "304", "300", "315", "311", "308", "305", "303", "309", "306", "313", "307", "314", "301", "310"], "fit_nums": ["994", "913", "681", "816", "972", "790", "142", "230", "696", "537", "975", "773", "918", "677", "742", "745"], "chain_num": 4, "ignore": [12, 1, 15, 14, 8, 6, 4, 10]}, "SWC_021": {"seeds": ["415", "403", "412", "407", "409", "408", "405", "404", "410", "414", "401", "413", "402", "400", "406", "411"], "fit_nums": ["773", "615", "107", "583", "564", "354", "142", "184", "549", "185", "924", "907", "105", "531", "9", "812"], "chain_num": 9, "ignore": [14, 12, 0, 10, 9, 4, 5, 1]}, "ibl_witten_15": {"seeds": ["409", "410", "401", "415", "414", "403", "411", "404", "402", "405", "400", "412", "408", "407", "406", "413"], "fit_nums": ["411", "344", "496", "600", "716", "18", "527", "467", "898", "334", "309", "326", "133", "823", "740", "253"], "chain_num": 9, "ignore": [14, 13, 8, 4, 5, 12, 11, 9]}, "ibl_witten_13": {"seeds": ["302", "312", "313", "306", "315", "307", "311", "314", "309", "301", "308", "300", "304", "310", "303", "305"], "fit_nums": ["897", "765", "433", "641", "967", "599", "984", "259", "853", "385", "887", "619", "434", "964", "483", "891"], "chain_num": 4, "ignore": [3, 5, 15, 0, 2, 12, 11, 10]}, "KS016": {"seeds": ["315", "301", "309", "313", "302", "307", "303", "308", "311", "312", "314", "306", "310", "300", "305", "304"], "fit_nums": ["99", "57", "585", "32", "501", "558", "243", "413", "59", "757", "463", "172", "524", "957", "909", "292"], "chain_num": 4, "ignore": [0, 2, 14, 12, 1, 7, 11, 6]}, "KS003": {"seeds": ["404", "407", "413", "403", "414", "405", "400", "401", "402", "410", "415", "408", "411", "409", "406", "412"], "fit_nums": ["846", "256", "845", "945", "293", "406", "420", "109", "690", "421", "54", "866", "784", "81", "997", "665"], "chain_num": 9, "ignore": [8, 15, 0, 13, 7, 12, 11, 1]}, "ibl_witten_19": {"seeds": ["315", "311", "307", "314", "308", "300", "305", "301", "313", "304", "302", "310", "306", "312", "309", "303"], "fit_nums": ["179", "951", "613", "6", "623", "382", "458", "504", "406", "554", "5", "631", "746", "817", "265", "328"], "chain_num": 4, "ignore": [13, 4, 10, 9, 2, 1, 3, 6]}, "SWC_022": {"seeds": ["411", "403", "414", "409", "407", "412", "410", "413", "415", "404", "405", "400", "402", "401", "408", "406"], "fit_nums": ["408", "884", "62", "962", "744", "854", "635", "70", "320", "952", "8", "67", "231", "381", "536", "962"], "chain_num": 9, "ignore": [4, 8, 7, 9, 1, 2, 10, 6]}, "KS022": {"seeds": ["315", "300", "314", "301", "303", "302", "306", "308", "305", "310", "313", "312", "304", "307", "311", "309"], "fit_nums": ["899", "681", "37", "957", "629", "637", "375", "980", "810", "51", "759", "664", "420", "127", "259", "555"], "chain_num": 4, "ignore": [10, 1, 0, 13, 5, 9, 12, 3]}, "CSH_ZAD_017": {"seeds": ["401", "409", "405", "403", "415", "404", "402", "411", "410", "414", "408", "406", "413", "412", "400", "407"], "fit_nums": ["883", "803", "637", "806", "356", "804", "662", "654", "684", "350", "947", "460", "569", "976", "103", "713"], "chain_num": 9, "ignore": [3, 4, 6, 7, 5, 0, 15, 12]}, "CSH_ZAD_025": {"seeds": ["303", "311", "307", "312", "313", "314", "308", "315", "305", "306", "304", "302", "309", "310", "301", "300"], "fit_nums": ["581", "148", "252", "236", "581", "838", "206", "756", "449", "288", "756", "593", "733", "633", "418", "563"], "chain_num": 4, "ignore": [8, 10, 13, 5, 12, 9, 7, 1]}, "ibl_witten_17": {"seeds": ["406", "415", "408", "413", "402", "405", "409", "400", "414", "401", "412", "407", "404", "410", "403", "411"], "fit_nums": ["827", "797", "496", "6", "444", "823", "384", "873", "634", "27", "811", "142", "207", "322", "756", "275"], "chain_num": 9, "ignore": [9, 0, 1, 7, 11, 3, 10, 8]}, "ibl_witten_18": {"seeds": ["311", "310", "303", "314", "302", "309", "305", "307", "312", "300", "308", "306", "315", "313", "304", "301"], "fit_nums": ["236", "26", "838", "762", "826", "409", "496", "944", "280", "704", "930", "419", "637", "896", "876", "297"], "chain_num": 4, "ignore": [11, 0, 4, 2, 12, 13, 8, 3]}, "CSHL_018": {"seeds": ["302", "310", "306", "300", "314", "307", "309", "313", "311", "308", "304", "301", "312", "303", "305", "315"], "fit_nums": ["843", "817", "920", "900", "226", "36", "472", "676", "933", "453", "116", "263", "269", "897", "568", "438"], "chain_num": 4, "ignore": [15, 4, 8, 0, 5, 10, 12, 11]}, "GLM_Sim_06": {"seeds": ["313", "309", "302", "303", "305", "314", "300", "315", "311", "306", "304", "310", "301", "312", "308", "307"], "fit_nums": ["9", "786", "286", "280", "72", "587", "619", "708", "360", "619", "311", "189", "60", "708", "939", "733"], "chain_num": 2, "ignore": [15, 9, 8, 14, 1, 12, 10, 3]}, "ZM_1897": {"seeds": ["304", "308", "305", "311", "315", "314", "307", "306", "300", "303", "313", "310", "301", "312", "302", "309"], "fit_nums": ["549", "96", "368", "509", "424", "897", "287", "426", "968", "93", "725", "513", "837", "581", "989", "374"], "chain_num": 4, "ignore": [0, 14, 5, 8, 7, 11, 13, 10]}, "CSHL_020": {"seeds": ["305", "309", "313", "302", "314", "310", "300", "307", "315", "306", "312", "304", "311", "301", "303", "308"], "fit_nums": ["222", "306", "243", "229", "584", "471", "894", "238", "986", "660", "494", "657", "896", "459", "100", "283"], "chain_num": 4, "ignore": [6, 5, 9, 15, 0, 8, 4, 13]}, "CSHL054": {"seeds": ["401", "415", "409", "410", "414", "413", "407", "405", "406", "408", "411", "400", "412", "402", "403", "404"], "fit_nums": ["901", "734", "609", "459", "574", "793", "978", "66", "954", "906", "954", "111", "292", "850", "266", "967"], "chain_num": 9, "ignore": [5, 12, 7, 10, 11, 2, 6, 4]}, "CSHL_014": {"seeds": ["305", "311", "309", "300", "313", "310", "307", "306", "304", "312", "308", "302", "314", "303", "301", "315"], "fit_nums": ["371", "550", "166", "24", "705", "385", "870", "884", "831", "546", "404", "722", "287", "564", "613", "783"], "chain_num": 4, "ignore": [15, 0, 3, 4, 7, 6, 1, 11]}, "CSHL062": {"seeds": ["307", "313", "310", "303", "306", "312", "308", "305", "311", "314", "304", "302", "300", "301", "315", "309"], "fit_nums": ["846", "371", "94", "888", "499", "229", "546", "432", "71", "989", "986", "91", "935", "314", "975", "481"], "chain_num": 4, "ignore": [14, 6, 3, 11, 15, 13, 4, 12]}, "CSH_ZAD_001": {"seeds": ["313", "309", "311", "312", "305", "310", "315", "300", "314", "304", "301", "302", "308", "303", "306", "307"], "fit_nums": ["468", "343", "314", "544", "38", "120", "916", "170", "305", "569", "502", "496", "452", "336", "559", "572"], "chain_num": 4, "ignore": [12, 8, 5, 1, 9, 3, 13, 15]}, "NYU-06": {"seeds": ["314", "309", "306", "305", "312", "303", "307", "304", "300", "302", "310", "301", "315", "308", "313", "311"], "fit_nums": ["950", "862", "782", "718", "427", "645", "827", "612", "821", "834", "595", "929", "679", "668", "648", "869"], "chain_num": 4, "ignore": [8, 2, 7, 12, 3, 4, 13, 11]}, "KS019": {"seeds": ["404", "401", "411", "408", "400", "403", "410", "413", "402", "407", "415", "409", "406", "414", "412", "405"], "fit_nums": ["682", "4", "264", "200", "250", "267", "737", "703", "132", "855", "922", "686", "85", "176", "54", "366"], "chain_num": 9, "ignore": [12, 14, 1, 2, 4, 7, 10, 15]}, "CSHL049": {"seeds": ["411", "402", "414", "408", "409", "410", "413", "407", "406", "401", "404", "405", "403", "415", "400", "412"], "fit_nums": ["104", "553", "360", "824", "749", "519", "347", "228", "863", "671", "140", "883", "701", "445", "627", "898"], "chain_num": 9, "ignore": [10, 11, 6, 7, 12, 13, 1, 8]}, "ibl_witten_14": {"seeds": ["310", "311", "304", "306", "300", "302", "314", "313", "303", "308", "301", "309", "305", "315", "312", "307"], "fit_nums": ["563", "120", "85", "712", "277", "871", "183", "661", "505", "598", "210", "89", "310", "638", "564", "998"], "chain_num": 4, "ignore": [11, 14, 6, 13, 5, 12, 15, 8]}, "KS014": {"seeds": ["301", "310", "302", "312", "313", "308", "307", "303", "305", "300", "314", "306", "311", "309", "304", "315"], "fit_nums": ["668", "32", "801", "193", "269", "296", "74", "24", "270", "916", "21", "250", "342", "451", "517", "293"], "chain_num": 4, "ignore": [9, 11, 0, 1, 14, 2, 12, 13]}, "CSHL059": {"seeds": ["306", "309", "300", "304", "314", "303", "315", "311", "313", "305", "301", "307", "302", "312", "310", "308"], "fit_nums": ["821", "963", "481", "999", "986", "45", "551", "605", "701", "201", "629", "261", "972", "407", "165", "9"], "chain_num": 4, "ignore": [9, 3, 5, 15, 6, 10, 2, 1]}, "GLM_Sim_13": {"seeds": ["310", "303", "308", "306", "300", "312", "301", "313", "305", "311", "315", "304", "314", "309", "307", "302"], "fit_nums": ["982", "103", "742", "524", "614", "370", "926", "456", "133", "143", "302", "80", "395", "549", "579", "944"], "chain_num": 2, "ignore": [12, 4, 11, 6, 7, 14, 0, 1]}, "CSHL_007": {"seeds": ["314", "303", "308", "313", "301", "300", "302", "305", "315", "306", "310", "309", "311", "304", "307", "312"], "fit_nums": ["462", "703", "345", "286", "480", "313", "986", "165", "201", "102", "322", "894", "960", "438", "330", "169"], "chain_num": 4, "ignore": [3, 12, 4, 5, 2, 0, 13, 1]}, "CSH_ZAD_011": {"seeds": ["314", "311", "303", "300", "305", "310", "306", "301", "302", "315", "304", "309", "308", "312", "313", "307"], "fit_nums": ["320", "385", "984", "897", "315", "120", "320", "945", "475", "403", "210", "412", "695", "564", "664", "411"], "chain_num": 4, "ignore": [0, 2, 14, 11, 7, 10, 13, 9]}, "KS021": {"seeds": ["309", "312", "304", "310", "303", "311", "314", "302", "305", "301", "306", "300", "308", "315", "313", "307"], "fit_nums": ["874", "943", "925", "587", "55", "136", "549", "528", "349", "211", "401", "84", "225", "545", "153", "382"], "chain_num": 4, "ignore": [11, 12, 0, 8, 2, 14, 5, 1]}, "GLM_Sim_15": {"seeds": ["303", "312", "305", "308", "309", "302", "301", "310", "313", "315", "311", "314", "307", "306", "304", "300"], "fit_nums": ["769", "930", "328", "847", "899", "714", "144", "518", "521", "873", "914", "359", "242", "343", "45", "364"], "chain_num": 2, "ignore": [8, 1, 0, 3, 2, 5, 10, 4]}, "CSHL_015": {"seeds": ["301", "302", "307", "310", "309", "311", "304", "312", "300", "308", "313", "305", "314", "315", "306", "303"], "fit_nums": ["717", "705", "357", "539", "604", "971", "669", "76", "45", "413", "510", "122", "190", "821", "368", "472"], "chain_num": 4, "ignore": [7, 6, 10, 2, 15, 13, 1, 3]}, "ibl_witten_16": {"seeds": ["304", "313", "309", "314", "312", "307", "305", "301", "306", "310", "300", "315", "308", "311", "303", "302"], "fit_nums": ["392", "515", "696", "270", "7", "583", "880", "674", "23", "576", "579", "695", "149", "854", "184", "875"], "chain_num": 4, "ignore": [3, 12, 2, 6, 10, 14, 4, 1]}, "KS015": {"seeds": ["315", "305", "309", "303", "314", "310", "311", "312", "313", "300", "307", "308", "304", "301", "302", "306"], "fit_nums": ["257", "396", "387", "435", "133", "164", "403", "8", "891", "650", "111", "557", "473", "229", "842", "196"], "chain_num": 4, "ignore": [7, 8, 0, 10, 2, 3, 12, 9]}, "GLM_Sim_12": {"seeds": ["304", "312", "306", "303", "310", "302", "300", "305", "308", "313", "307", "311", "315", "301", "314", "309"], "fit_nums": ["971", "550", "255", "195", "952", "486", "841", "535", "559", "37", "654", "213", "864", "506", "732", "550"], "chain_num": 2, "ignore": [0, 7, 15, 14, 3, 10, 11, 13]}, "GLM_Sim_11": {"seeds": ["300", "312", "310", "315", "302", "313", "314", "311", "308", "303", "309", "307", "306", "304", "301", "305"], "fit_nums": ["477", "411", "34", "893", "195", "293", "603", "5", "887", "281", "956", "73", "346", "640", "532", "688"], "chain_num": 2}, "GLM_Sim_10": {"seeds": ["301", "300", "306", "305", "307", "309", "312", "314", "311", "315", "304", "313", "303", "308", "302", "310"], "fit_nums": ["391", "97", "897", "631", "239", "652", "19", "448", "807", "35", "972", "469", "280", "562", "42", "706"], "chain_num": 2, "ignore": 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\ No newline at end of file
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"847", "899", "714", "144", "518", "521", "873", "914", "359", "242", "343", "45", "364"], "chain_num": 2, "ignore": [8, 1, 0, 3, 2, 5, 10, 4]}, "CSHL_015": {"seeds": ["301", "302", "307", "310", "309", "311", "304", "312", "300", "308", "313", "305", "314", "315", "306", "303"], "fit_nums": ["717", "705", "357", "539", "604", "971", "669", "76", "45", "413", "510", "122", "190", "821", "368", "472"], "chain_num": 4, "ignore": [7, 6, 10, 2, 15, 13, 1, 3]}, "ibl_witten_16": {"seeds": ["304", "313", "309", "314", "312", "307", "305", "301", "306", "310", "300", "315", "308", "311", "303", "302"], "fit_nums": ["392", "515", "696", "270", "7", "583", "880", "674", "23", "576", "579", "695", "149", "854", "184", "875"], "chain_num": 4, "ignore": [3, 12, 2, 6, 10, 14, 4, 1]}, "KS015": {"seeds": ["315", "305", "309", "303", "314", "310", "311", "312", "313", "300", "307", "308", "304", "301", "302", "306"], "fit_nums": ["257", "396", "387", "435", "133", "164", "403", "8", "891", "650", "111", "557", "473", "229", "842", "196"], "chain_num": 4, "ignore": [7, 8, 0, 10, 2, 3, 12, 9]}, "GLM_Sim_12": {"seeds": ["304", "312", "306", "303", "310", "302", "300", "305", "308", "313", "307", "311", "315", "301", "314", "309"], "fit_nums": ["971", "550", "255", "195", "952", "486", "841", "535", "559", "37", "654", "213", "864", "506", "732", "550"], "chain_num": 2, "ignore": [0, 7, 15, 14, 3, 10, 11, 13]}, "GLM_Sim_11": {"seeds": ["300", "312", "310", "315", "302", "313", "314", "311", "308", "303", "309", "307", "306", "304", "301", "305"], "fit_nums": ["477", "411", "34", "893", "195", "293", "603", "5", "887", "281", "956", "73", "346", "640", "532", "688"], "chain_num": 2}, "GLM_Sim_10": {"seeds": ["301", "300", "306", "305", "307", "309", "312", "314", "311", "315", "304", "313", "303", "308", "302", "310"], "fit_nums": ["391", "97", "897", "631", "239", "652", "19", "448", "807", "35", "972", "469", "280", "562", "42", "706"], "chain_num": 2, "ignore": [1, 9, 15, 3, 13, 12, 7, 11]}, "CSH_ZAD_026": {"seeds": ["312", "313", "308", "310", "303", "307", "302", "305", "300", "315", "306", "301", "311", "304", "314", "309"], "fit_nums": ["699", "87", "537", "628", "797", "511", "459", "770", "969", "240", "504", "948", "295", "506", "25", "378"], "chain_num": 4, "ignore": [12, 13, 4, 11, 8, 3, 15, 0]}, "KS023": {"seeds": ["304", "313", "306", "309", "300", "314", "302", "310", "303", "315", "307", "308", "301", "311", "305", "312"], "fit_nums": ["698", "845", "319", "734", "908", "507", "45", "499", "175", "108", "419", "443", "116", "779", "159", "231"], "chain_num": 4, "ignore": [8, 10, 1, 13, 4, 15, 14, 7]}, "GLM_Sim_05": {"seeds": ["301", "315", "300", "302", "305", "304", "313", "314", "311", "309", "306", "307", "308", "310", "303", "312"], "fit_nums": ["425", "231", "701", "375", "343", "902", "623", "125", "921", "637", "393", "964", "678", "930", "796", "42"], "chain_num": 2, "ignore": [11, 2, 5, 1, 4, 9, 15, 12]}, "CSHL061": {"seeds": ["305", "315", "304", "303", "309", "310", "302", "300", "314", "306", "311", "313", "301", "308", "307", "312"], "fit_nums": ["396", "397", "594", "911", "308", "453", "686", "552", "103", "209", "128", "892", "345", "925", "777", "396"], "chain_num": 4, "ignore": [11, 13, 7, 15, 14, 3, 0, 4]}, "CSHL051": {"seeds": ["303", "310", "306", "302", "309", "305", "313", "308", "300", "314", "311", "307", "312", "304", "315", "301"], "fit_nums": ["69", "186", "49", "435", "103", "910", "705", "367", "303", "474", "596", "334", "929", "796", "616", "790"], "chain_num": 4, "ignore": [15, 12, 8, 13, 0, 2, 4, 5]}, "GLM_Sim_14": {"seeds": ["310", "311", "309", "313", "314", "300", "302", "304", "305", "306", "307", "312", "303", "301", "315", "308"], "fit_nums": ["616", "872", "419", "106", "940", "986", "599", "704", "218", "808", "244", "825", "448", "397", "552", "316"], "chain_num": 2, "ignore": [7, 11, 2, 15, 0, 13, 5, 10]}, "GLM_Sim_11_trick": {"seeds": ["411", "400", "408", "409", "415", "413", "410", "412", "406", "414", "403", "404", "401", "405", "407", "402"], "fit_nums": ["95", "508", "886", "384", "822", "969", "525", "382", "489", "436", "344", "537", "251", "223", "458", "401"], "chain_num": 2}, "GLM_Sim_16": {"seeds": ["302", "311", "303", "307", "313", "308", "309", "300", "305", "315", "304", "310", "312", "301", "314", "306"], "fit_nums": ["914", "377", "173", "583", "870", "456", "611", "697", "13", "713", "159", "248", "617", "37", "770", "780"], "chain_num": 2, "ignore": [4, 10, 5, 0, 13, 8, 6, 7]}, "ZM_3003": {"seeds": ["300", "304", "307", "312", "305", "310", "311", "314", "303", "308", "313", "301", "315", "309", "306", "302"], "fit_nums": ["603", "620", "657", "735", "357", "390", "119", "33", "62", "617", "209", "810", "688", "21", "744", "426"], "chain_num": 4, "ignore": [14, 7, 12, 1, 3, 4, 11, 8]}, "CSH_ZAD_022": {"seeds": ["305", "310", "311", "315", "303", "312", "314", "313", "307", "302", "300", "304", "301", "308", "306", "309"], "fit_nums": ["143", "946", "596", "203", "576", "403", "900", "65", "478", "325", "282", "513", "460", "42", "161", "970"], "chain_num": 4, "ignore": [9, 12, 4, 8, 3, 7, 0, 1]}, "GLM_Sim_07": {"seeds": ["300", "309", "302", "304", "305", "312", "301", "311", "315", "314", "308", "307", "303", "310", "306", "313"], "fit_nums": ["724", "701", "118", "230", "648", "426", "689", "114", "832", "731", "592", "519", "559", "938", "672", "144"], "chain_num": 1}, "KS017": {"seeds": ["311", "310", "306", "309", "303", "302", "308", "300", "313", "301", "314", "307", "315", "304", "312", "305"], "fit_nums": ["97", "281", "808", "443", "352", "890", "703", "468", "780", "708", "674", "27", "345", "23", "939", "457"], "chain_num": 4, "ignore": [0, 13, 8, 1, 12, 5, 10, 9]}, "GLM_Sim_11_sub": {"seeds": ["410", "414", "413", "404", "409", "415", "406", "408", "402", "411", "400", "405", "403", "407", "412", "401"], "fit_nums": ["830", "577", "701", "468", "929", "374", "954", "749", "937", "488", "873", "416", "612", "792", "461", "488"], "chain_num": 2}}
\ No newline at end of file
diff --git a/dyn_glm_chain_analysis.py b/dyn_glm_chain_analysis.py
index 4924143b4f44716c903d7e798a60125d432c262e..410e2cdc3fb938dc9bea4ed69cb5b5b578531d86 100644
--- a/dyn_glm_chain_analysis.py
+++ b/dyn_glm_chain_analysis.py
@@ -21,7 +21,7 @@ import time
import multiprocessing as mp
from mcmc_chain_analysis import state_size_helper, state_num_helper, gamma_func, alpha_func, ll_func, r_hat_array_comp, rank_inv_normal_transform, eval_r_hat, eval_simple_r_hat
import pandas as pd
-from pmf_analysis import pmf_type, type2color
+from analysis_pmf import pmf_type, type2color
colors = np.genfromtxt('colors.csv', delimiter=',')
@@ -587,6 +587,33 @@ def contrasts_plot(test, state_sets, subject, save=False, show=False, dpi='figur
return cnas
+def bias_flips(states_by_session, pmfs, durs):
+ state_counter = {}
+ prev_bias = 0
+ bias_flips = 0
+
+ for sess in range(states_by_session.shape[1]):
+ states = np.where(states_by_session[:, sess])[0]
+
+ for s in states:
+ if s not in state_counter:
+ state_counter[s] = -1
+ state_counter[s] += 1
+
+ if s == np.argmax(states_by_session[:, sess]):
+ bias = np.mean(pmfs[s][1][state_counter[s]][pmfs[s][0]])
+ if bias < 0.45:
+ if prev_bias == 1:
+ print("sess {}".format(sess))
+ bias_flips += 1
+ prev_bias = -1
+ elif bias > 0.55:
+ if prev_bias == -1:
+ print("sess {}".format(sess))
+ bias_flips += 1
+ prev_bias = 1
+ return bias_flips
+
def pmf_regressions(states_by_session, pmfs, durs):
# find out whether pmfs regressed
state_perfs = {}
@@ -594,6 +621,7 @@ def pmf_regressions(states_by_session, pmfs, durs):
current_best_state = -1
counter = 0
types = [0, 0, 0]
+ diffs = []
for sess in range(states_by_session.shape[1]):
states = np.where(states_by_session[:, sess])[0]
@@ -616,8 +644,9 @@ def pmf_regressions(states_by_session, pmfs, durs):
types[2] += 1
a, b = state_perfs[np.argmax(states_by_session[:, sess])], state_perfs[current_best_state]
print("Regression in session {} during {:.2f}% of session ({:.2f} instead of {:.2f})".format(sess + 1, np.max(states_by_session[:, sess]) * 100, a, b))
+ diffs.append(b - a)
- return [counter, states_by_session.shape[1], *types]
+ return [counter, states_by_session.shape[1], *types], diffs
def control_flow(test, indices, trials, func_init, first_for, second_for, end_first_for):
# Generalised control flow for iterating over samples of mode across individually across sessions
@@ -1227,6 +1256,9 @@ def find_good_chains_unsplit_greedy(chains1, chains2, chains3, chains4, reduce_t
print("Without removals: {}".format(r_hat))
mins[0] = r_hat
+ r_hats = []
+ solutions = []
+
to_del = []
for i in range(delete_n):
r_hat_min = 50
@@ -1247,10 +1279,16 @@ def find_good_chains_unsplit_greedy(chains1, chains2, chains3, chains4, reduce_t
print("Removed: {}".format(to_del))
mins[i + 1] = r_hat_min
+ r_hats.append(r_hat_min)
+ solutions.append(to_del.copy())
+
if simple:
r_hat_local = eval_r_hat([np.delete(chains1, to_del, axis=0), np.delete(chains2, to_del, axis=0), np.delete(chains3, to_del, axis=0), np.delete(chains4, to_del, axis=0)])
print("Minimum over everything is {} (removed {})".format(r_hat_local, i + 1))
- return to_del, r_hat_min
+
+ best = np.argmin(r_hats)
+
+ return solutions[best], r_hats[best]
if __name__ == "__main__":
@@ -1261,7 +1299,7 @@ if __name__ == "__main__":
elif fit_type == 'prebias':
loading_info = json.load(open("canonical_infos.json", 'r'))
r_hats = json.load(open("canonical_info_r_hats.json", 'r'))
- subjects = list(loading_info.keys())
+ subjects = ['SWC_021', 'ibl_witten_15', 'ibl_witten_13', 'KS003', 'ibl_witten_19', 'SWC_022', 'CSH_ZAD_017'] # list(loading_info.keys())
r_hats = {}
@@ -1273,7 +1311,6 @@ if __name__ == "__main__":
check_r_hats = False
if check_r_hats:
- subjects = list(loading_info.keys())
for subject in subjects:
if subject.startswith('GLM_Sim_07') or subject.startswith('GLM_Sim_11'):
continue
@@ -1440,7 +1477,7 @@ if __name__ == "__main__":
r_hats = json.load(open("canonical_info_r_hats.json", 'r'))
no_good_pcas = ['NYU-06', 'SWC_023']
subjects = list(loading_info.keys())
- subjects = ['KS014']
+ # subjects = ['SWC_021', 'ibl_witten_15', 'ibl_witten_13', 'KS003', 'ibl_witten_19', 'SWC_022', 'CSH_ZAD_017']
# meh pmfs: KS021
print(subjects)
@@ -1479,12 +1516,17 @@ if __name__ == "__main__":
all_intros_div = []
all_states_per_type = []
regressions = []
+ regression_diffs = []
+ all_bias_flips = []
for subject in subjects:
if subject.startswith('GLM_Sim_') or subject == 'ibl_witten_18':
continue
+ if subject in ['SWC_021', 'ibl_witten_15', 'ibl_witten_13', 'KS003', 'ibl_witten_19', 'SWC_022', 'CSH_ZAD_017']:
+ continue
+
print(subject)
try:
@@ -1500,9 +1542,14 @@ if __name__ == "__main__":
# training overview
states, pmfs, durs, _, contrast_intro_type, intros_by_type, undiv_intros, states_per_type = state_development(test, [s for s in state_sets if len(s) > 40], mode_indices, show=0, separate_pmf=1, type_coloring=True)
- regression = pmf_regressions(states, pmfs, durs)
+
+ # b_flips = bias_flips(states, pmfs, durs)
+ # all_bias_flips.append(b_flips)
+
+ regression, diffs = pmf_regressions(states, pmfs, durs)
+ regression_diffs += diffs
regressions.append(regression)
- quit()
+ continue
# compare_pmfs(test, [s for s in state_sets if len(s) > 40], mode_indices, [4, 5], states, pmfs, title="{} convergence pmf".format(subject))
# compare_weights(test, [s for s in state_sets if len(s) > 40], mode_indices, [4, 5], states, title="{} convergence weights".format(subject))
# quit()
@@ -1720,7 +1767,6 @@ if __name__ == "__main__":
except FileNotFoundError as e:
print(e)
- continue
print('no canoncial result')
print(r_hats[subject])
if r_hats[subject] >= 1.05:
@@ -1749,17 +1795,12 @@ if __name__ == "__main__":
except Exception:
break
save_id = "{}_fittype_{}_var_{}_{}_{}.p".format(subject, fit_type, fit_variance, seed, fit_num).replace('.', '_')
- # for file in os.listdir("./dynamic_GLMiHMM_crossvals/infos_new/"):
- # if file.startswith("{}_".format(subject)) and file.endswith("_{}_{}_{}_{}.json".format(fit_type, fit_variance, seed, fit_num)):
- # print("Taking fit infos from {}".format(file))
- # fit_infos = json.load(open("./dynamic_GLMiHMM_crossvals/infos_new/" + file, 'r'))
- # sample_lls = fit_infos['ll']
print("Loaded")
result = MCMC_result(samples[::25], infos=info_dict,
data=samples[0].datas, sessions=fit_type, fit_variance=fit_variance,
- dur=dur, save_id=save_id) # , sample_lls=sample_lls)
+ dur=dur, save_id=save_id)
results.append(result)
test = MCMC_result_list(results, summary_info)
pickle.dump(test, open("multi_chain_saves/canonical_result_{}_{}.p".format(subject, fit_type), 'wb'))
@@ -1789,13 +1830,14 @@ if __name__ == "__main__":
# pickle.dump(all_intros_div, open("all_intros_div.p", 'wb'))
# pickle.dump(all_states_per_type, open("all_states_per_type.p", 'wb'))
# pickle.dump(regressions, open("regressions.p", 'wb'))
+ # pickle.dump(regression_diffs, open("regression_diffs.p", 'wb'))
+ # pickle.dump(all_bias_flips, open("all_bias_flips.p", 'wb'))
#
# a = [x for x, y in zip(all_pmf_asymms, all_pmf_diffs) if y >= 0.2]
# b = [y for x, y in zip(all_pmf_asymms, all_pmf_diffs) if y >= 0.2]
# plt.hist2d(a, b, bins=40)
# plt.show()
-
if True:
abs_state_durs = np.array(abs_state_durs)
# pickle.dump(abs_state_durs, open("multi_chain_saves/abs_state_durs.p", 'wb'))
diff --git a/index_mice.py b/index_mice.py
index ebb58b840677ea1ffc0cdd34584d08c4403b3a75..e821de0e2e86ea42e5859cc88e8c545179cea4e8 100644
--- a/index_mice.py
+++ b/index_mice.py
@@ -42,7 +42,7 @@ for filename in os.listdir("./dynamic_GLMiHMM_crossvals/"):
for s in prebias_subinfo.keys():
- if len(prebias_subinfo[s]["fit_nums"]) == 48:
+ if len(prebias_subinfo[s]["fit_nums"]) == 48 or len(prebias_subinfo[s]["fit_nums"]) == 32:
new_fit_nums = []
new_seeds = []
for fit_num, seed in zip(prebias_subinfo[s]["fit_nums"], prebias_subinfo[s]["seeds"]):
@@ -51,23 +51,23 @@ for s in prebias_subinfo.keys():
new_seeds.append(seed)
prebias_subinfo[s]["fit_nums"] = new_fit_nums
prebias_subinfo[s]["seeds"] = new_seeds
- if s == 'ibl_witten_13':
- new_fit_nums = []
- new_seeds = []
- for fit_num, seed in zip(prebias_subinfo[s]["fit_nums"], prebias_subinfo[s]["seeds"]):
- if int(seed) < 316:
- new_fit_nums.append(fit_num)
- new_seeds.append(seed)
- prebias_subinfo[s]["fit_nums"] = new_fit_nums
- prebias_subinfo[s]["seeds"] = new_seeds
+ # if s == 'ibl_witten_13':
+ # new_fit_nums = []
+ # new_seeds = []
+ # for fit_num, seed in zip(prebias_subinfo[s]["fit_nums"], prebias_subinfo[s]["seeds"]):
+ # if int(seed) < 316:
+ # new_fit_nums.append(fit_num)
+ # new_seeds.append(seed)
+ # prebias_subinfo[s]["fit_nums"] = new_fit_nums
+ # prebias_subinfo[s]["seeds"] = new_seeds
big = []
non_big = []
sim_subjects = []
for s in prebias_subinfo.keys():
- # assert len(sub_info[s]["seeds"]) in [16, 32]
- # assert len(sub_info[s]["fit_nums"]) in [16, 32]
+ assert len(prebias_subinfo[s]["seeds"]) in [16, 32]
+ assert len(prebias_subinfo[s]["fit_nums"]) in [16, 32]
print(s, len(prebias_subinfo[s]["fit_nums"]))
if len(prebias_subinfo[s]["fit_nums"]) == 32:
big.append(s)
diff --git a/process_many_chains.py b/process_many_chains.py
index 88840671866206bcdee29ba09c549eb8181bae00..cf8061356316a47aae18dedf91b2d0b4b2b27e9c 100644
--- a/process_many_chains.py
+++ b/process_many_chains.py
@@ -9,7 +9,7 @@ import json
from dyn_glm_chain_analysis import MCMC_result
import matplotlib.pyplot as plt
import time
-from mcmc_chain_analysis import state_size_helper, state_num_helper, ll_helper
+from mcmc_chain_analysis import state_size_helper, state_num_helper
fit_type = ['prebias', 'bias', 'all', 'prebias_plus', 'zoe_style'][0]
@@ -17,7 +17,7 @@ if fit_type == 'bias':
loading_info = json.load(open("canonical_infos_bias.json", 'r'))
elif fit_type == 'prebias':
loading_info = json.load(open("canonical_infos.json", 'r'))
-subjects = ['GLM_Sim_11_trick'] # list(loading_info.keys())
+subjects = ['SWC_021', 'ibl_witten_15', 'ibl_witten_13', 'KS003', 'ibl_witten_19', 'SWC_022', 'CSH_ZAD_017'] # list(loading_info.keys())
fit_variance = [0.03, 0.002, 0.0005, 'uniform', 0, 0.008][0]
func1 = state_num_helper(0.2)