You can download and run the notebook locally:
Table S3-4#
[1]:
import scipy.stats
import numpy as np
from statsmodels.stats.multicomp import pairwise_tukeyhsd
from statsmodels.sandbox.stats.multicomp import get_tukey_pvalue
import joblib
import pandas as pd
[2]:
decoding_results = pd.read_hdf("../data/Figure5Revision.h5", data="key")
[3]:
def get_data2(decoding_results, task, decoders, methods, window, modality, num_neurons):
if modality == "ca":
index = 0
elif modality == "np":
index = 1
accs = []
keys = []
for decoder, method in zip(decoders, methods):
key = f"{modality}_{method}_{window}"
if "joint" in method:
acc = np.array(decoding_results[task][decoder][key][num_neurons])[:, index]
else:
acc = np.array(decoding_results[task][decoder][key][num_neurons])
accs.append(acc)
keys.append([f"{key}_{decoder}"] * len(acc))
return np.concatenate(accs), np.concatenate(keys)
def concat_neurons(decoding_results, task, decoder, method, window, modality):
if modality == "ca":
index = 0
elif modality == "np":
index = 1
key = f"{modality}_{method}_{window}"
accs = []
for n in decoding_results[task][decoder][key].keys():
if "joint" in method:
accs.append(np.array(decoding_results[task][decoder][key][n])[:, index])
else:
accs.append(np.array(decoding_results[task][decoder][key][n]))
return np.concatenate(accs)
ANOVA for CEBRA, CEBRA-joint, baseline 330 ms (10 frame window):#
[4]:
np_total_stats = scipy.stats.f_oneway(
concat_neurons(decoding_results, "frame_id", "knn", "cebra", "330", "np"),
concat_neurons(decoding_results, "frame_id", "knn", "cebra_joint", "330", "np"),
concat_neurons(decoding_results, "frame_id", "knn", "baseline", "330", "np"),
concat_neurons(decoding_results, "frame_id", "bayes", "baseline", "330", "np"),
)
print(f"NP total stats \n {np_total_stats}")
NP total stats
F_onewayResult(statistic=1.2871516854445968, pvalue=0.27999880116247905)
ANOVA for CEBRA, CEBRA-joint, baseline 33 ms (1 frame window):#
[5]:
np_total_stats = scipy.stats.f_oneway(
concat_neurons(decoding_results, "frame_id", "knn", "cebra", "33", "np"),
concat_neurons(decoding_results, "frame_id", "knn", "cebra_joint", "33", "np"),
concat_neurons(decoding_results, "frame_id", "knn", "baseline", "33", "np"),
concat_neurons(decoding_results, "frame_id", "bayes", "baseline", "33", "np"),
)
print(f"NP total stats \n {np_total_stats}")
NP total stats
F_onewayResult(statistic=5.881619459851054, pvalue=0.0007278034882167102)
ANOVA for CEBRA, CEBRA-joint, baseline for each neuron numbers#
[6]:
num_neurons = [10, 30, 50, 100, 200, 400, 600, 800, 900, 1000]
for i in num_neurons:
print(f"For {i} neurons from np recording (330ms):")
np_data, np_keys = get_data2(
decoding_results,
"frame_id",
["knn", "knn", "knn", "bayes"],
["cebra", "cebra_joint", "baseline", "baseline"],
"330",
"np",
i,
)
stats = pairwise_tukeyhsd(
np_data.flatten(),
np_keys,
)
print(stats)
For 10 neurons from np recording (330ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
====================================================================================
group1 group2 meandiff p-adj lower upper reject
------------------------------------------------------------------------------------
np_baseline_330_bayes np_baseline_330_knn -5.7 0.5269 -17.4894 6.0894 False
np_baseline_330_bayes np_cebra_330_knn -4.1111 0.7529 -15.9005 7.6782 False
np_baseline_330_bayes np_cebra_joint_330_knn -8.0833 0.2429 -19.8727 3.706 False
np_baseline_330_knn np_cebra_330_knn 1.5889 0.9798 -10.2005 13.3782 False
np_baseline_330_knn np_cebra_joint_330_knn -2.3833 0.9371 -14.1727 9.406 False
np_cebra_330_knn np_cebra_joint_330_knn -3.9722 0.7713 -15.7616 7.8171 False
------------------------------------------------------------------------------------
For 30 neurons from np recording (330ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
====================================================================================
group1 group2 meandiff p-adj lower upper reject
------------------------------------------------------------------------------------
np_baseline_330_bayes np_baseline_330_knn -14.0167 0.016 -25.6823 -2.351 True
np_baseline_330_bayes np_cebra_330_knn -9.6278 0.1255 -21.2935 2.0379 False
np_baseline_330_bayes np_cebra_joint_330_knn -15.6278 0.0072 -27.2935 -3.9621 True
np_baseline_330_knn np_cebra_330_knn 4.3889 0.7083 -7.2768 16.0546 False
np_baseline_330_knn np_cebra_joint_330_knn -1.6111 0.9784 -13.2768 10.0546 False
np_cebra_330_knn np_cebra_joint_330_knn -6.0 0.4762 -17.6657 5.6657 False
------------------------------------------------------------------------------------
For 50 neurons from np recording (330ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
====================================================================================
group1 group2 meandiff p-adj lower upper reject
------------------------------------------------------------------------------------
np_baseline_330_bayes np_baseline_330_knn -15.7778 0.0358 -30.6554 -0.9002 True
np_baseline_330_bayes np_cebra_330_knn -9.1889 0.324 -24.0665 5.6887 False
np_baseline_330_bayes np_cebra_joint_330_knn -12.1833 0.1296 -27.0609 2.6943 False
np_baseline_330_knn np_cebra_330_knn 6.5889 0.5956 -8.2887 21.4665 False
np_baseline_330_knn np_cebra_joint_330_knn 3.5944 0.8989 -11.2832 18.4721 False
np_cebra_330_knn np_cebra_joint_330_knn -2.9944 0.9379 -17.8721 11.8832 False
------------------------------------------------------------------------------------
For 100 neurons from np recording (330ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
====================================================================================
group1 group2 meandiff p-adj lower upper reject
------------------------------------------------------------------------------------
np_baseline_330_bayes np_baseline_330_knn -17.5 0.0 -24.032 -10.968 True
np_baseline_330_bayes np_cebra_330_knn -4.3833 0.2589 -10.9153 2.1486 False
np_baseline_330_bayes np_cebra_joint_330_knn -3.8056 0.372 -10.3375 2.7264 False
np_baseline_330_knn np_cebra_330_knn 13.1167 0.0002 6.5847 19.6486 True
np_baseline_330_knn np_cebra_joint_330_knn 13.6944 0.0001 7.1625 20.2264 True
np_cebra_330_knn np_cebra_joint_330_knn 0.5778 0.9941 -5.9542 7.1098 False
------------------------------------------------------------------------------------
For 200 neurons from np recording (330ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
====================================================================================
group1 group2 meandiff p-adj lower upper reject
------------------------------------------------------------------------------------
np_baseline_330_bayes np_baseline_330_knn -11.7278 0.0 -16.0601 -7.3954 True
np_baseline_330_bayes np_cebra_330_knn 0.2833 0.9976 -4.049 4.6157 False
np_baseline_330_bayes np_cebra_joint_330_knn -1.3778 0.7999 -5.7101 2.9546 False
np_baseline_330_knn np_cebra_330_knn 12.0111 0.0 7.6788 16.3435 True
np_baseline_330_knn np_cebra_joint_330_knn 10.35 0.0 6.0177 14.6823 True
np_cebra_330_knn np_cebra_joint_330_knn -1.6611 0.6964 -5.9935 2.6712 False
------------------------------------------------------------------------------------
For 400 neurons from np recording (330ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
====================================================================================
group1 group2 meandiff p-adj lower upper reject
------------------------------------------------------------------------------------
np_baseline_330_bayes np_baseline_330_knn -6.7389 0.0004 -10.3943 -3.0835 True
np_baseline_330_bayes np_cebra_330_knn 2.4722 0.2531 -1.1832 6.1277 False
np_baseline_330_bayes np_cebra_joint_330_knn 2.6 0.2166 -1.0554 6.2554 False
np_baseline_330_knn np_cebra_330_knn 9.2111 0.0 5.5557 12.8665 True
np_baseline_330_knn np_cebra_joint_330_knn 9.3389 0.0 5.6835 12.9943 True
np_cebra_330_knn np_cebra_joint_330_knn 0.1278 0.9996 -3.5277 3.7832 False
------------------------------------------------------------------------------------
For 600 neurons from np recording (330ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
====================================================================================
group1 group2 meandiff p-adj lower upper reject
------------------------------------------------------------------------------------
np_baseline_330_bayes np_baseline_330_knn -6.6944 0.0002 -10.1351 -3.2538 True
np_baseline_330_bayes np_cebra_330_knn 2.4722 0.2095 -0.9685 5.9129 False
np_baseline_330_bayes np_cebra_joint_330_knn 2.2222 0.2884 -1.2185 5.6629 False
np_baseline_330_knn np_cebra_330_knn 9.1667 0.0 5.726 12.6073 True
np_baseline_330_knn np_cebra_joint_330_knn 8.9167 0.0 5.476 12.3573 True
np_cebra_330_knn np_cebra_joint_330_knn -0.25 0.9967 -3.6907 3.1907 False
------------------------------------------------------------------------------------
For 800 neurons from np recording (330ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
===================================================================================
group1 group2 meandiff p-adj lower upper reject
-----------------------------------------------------------------------------------
np_baseline_330_bayes np_baseline_330_knn -6.4944 0.0001 -9.6586 -3.3302 True
np_baseline_330_bayes np_cebra_330_knn 1.85 0.3691 -1.3142 5.0142 False
np_baseline_330_bayes np_cebra_joint_330_knn 2.4278 0.1668 -0.7364 5.592 False
np_baseline_330_knn np_cebra_330_knn 8.3444 0.0 5.1802 11.5086 True
np_baseline_330_knn np_cebra_joint_330_knn 8.9222 0.0 5.758 12.0864 True
np_cebra_330_knn np_cebra_joint_330_knn 0.5778 0.9524 -2.5864 3.742 False
-----------------------------------------------------------------------------------
For 900 neurons from np recording (330ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
===================================================================================
group1 group2 meandiff p-adj lower upper reject
-----------------------------------------------------------------------------------
np_baseline_330_bayes np_baseline_330_knn -6.4389 0.0003 -9.865 -3.0128 True
np_baseline_330_bayes np_cebra_330_knn 1.9611 0.3867 -1.465 5.3872 False
np_baseline_330_bayes np_cebra_joint_330_knn 2.0444 0.3522 -1.3816 5.4705 False
np_baseline_330_knn np_cebra_330_knn 8.4 0.0 4.9739 11.8261 True
np_baseline_330_knn np_cebra_joint_330_knn 8.4833 0.0 5.0572 11.9094 True
np_cebra_330_knn np_cebra_joint_330_knn 0.0833 0.9999 -3.3428 3.5094 False
-----------------------------------------------------------------------------------
For 1000 neurons from np recording (330ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
===================================================================================
group1 group2 meandiff p-adj lower upper reject
-----------------------------------------------------------------------------------
np_baseline_330_bayes np_baseline_330_knn -5.2222 0.0018 -8.5376 -1.9068 True
np_baseline_330_bayes np_cebra_330_knn 1.7167 0.4707 -1.5987 5.032 False
np_baseline_330_bayes np_cebra_joint_330_knn 1.9167 0.3785 -1.3987 5.232 False
np_baseline_330_knn np_cebra_330_knn 6.9389 0.0001 3.6235 10.2543 True
np_baseline_330_knn np_cebra_joint_330_knn 7.1389 0.0001 3.8235 10.4543 True
np_cebra_330_knn np_cebra_joint_330_knn 0.2 0.9981 -3.1154 3.5154 False
-----------------------------------------------------------------------------------
[7]:
num_neurons = [10, 30, 50, 100, 200, 400, 600, 800, 900, 1000]
for i in num_neurons:
print(f"For {i} neurons from np recording (33ms):")
np_data, np_keys = get_data2(
decoding_results,
"frame_id",
["knn", "knn", "knn", "bayes"],
["cebra", "cebra_joint", "baseline", "baseline"],
"33",
"np",
i,
)
stats = pairwise_tukeyhsd(np_data.flatten(), np_keys)
print(stats)
For 10 neurons from np recording (33ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
================================================================================
group1 group2 meandiff p-adj lower upper reject
--------------------------------------------------------------------------------
np_baseline_33_bayes np_baseline_33_knn -1.7333 0.6751 -6.1089 2.6423 False
np_baseline_33_bayes np_cebra_33_knn 0.3556 0.9954 -4.02 4.7312 False
np_baseline_33_bayes np_cebra_joint_33_knn 0.6667 0.9714 -3.7089 5.0423 False
np_baseline_33_knn np_cebra_33_knn 2.0889 0.5371 -2.2867 6.4645 False
np_baseline_33_knn np_cebra_joint_33_knn 2.4 0.4225 -1.9756 6.7756 False
np_cebra_33_knn np_cebra_joint_33_knn 0.3111 0.9969 -4.0645 4.6867 False
--------------------------------------------------------------------------------
For 30 neurons from np recording (33ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
==================================================================================
group1 group2 meandiff p-adj lower upper reject
----------------------------------------------------------------------------------
np_baseline_33_bayes np_baseline_33_knn -3.2222 0.6128 -10.6673 4.2229 False
np_baseline_33_bayes np_cebra_33_knn 1.3111 0.957 -6.134 8.7562 False
np_baseline_33_bayes np_cebra_joint_33_knn 1.8444 0.8921 -5.6007 9.2895 False
np_baseline_33_knn np_cebra_33_knn 4.5333 0.3356 -2.9118 11.9784 False
np_baseline_33_knn np_cebra_joint_33_knn 5.0667 0.2484 -2.3784 12.5118 False
np_cebra_33_knn np_cebra_joint_33_knn 0.5333 0.9968 -6.9118 7.9784 False
----------------------------------------------------------------------------------
For 50 neurons from np recording (33ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
=================================================================================
group1 group2 meandiff p-adj lower upper reject
---------------------------------------------------------------------------------
np_baseline_33_bayes np_baseline_33_knn -6.6222 0.0232 -12.446 -0.7985 True
np_baseline_33_bayes np_cebra_33_knn 1.4444 0.8918 -4.3793 7.2682 False
np_baseline_33_bayes np_cebra_joint_33_knn 1.7556 0.8238 -4.0682 7.5793 False
np_baseline_33_knn np_cebra_33_knn 8.0667 0.0055 2.2429 13.8904 True
np_baseline_33_knn np_cebra_joint_33_knn 8.3778 0.004 2.554 14.2015 True
np_cebra_33_knn np_cebra_joint_33_knn 0.3111 0.9987 -5.5126 6.1349 False
---------------------------------------------------------------------------------
For 100 neurons from np recording (33ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
==================================================================================
group1 group2 meandiff p-adj lower upper reject
----------------------------------------------------------------------------------
np_baseline_33_bayes np_baseline_33_knn -11.3778 0.0 -16.2363 -6.5192 True
np_baseline_33_bayes np_cebra_33_knn -5.3778 0.0275 -10.2363 -0.5192 True
np_baseline_33_bayes np_cebra_joint_33_knn -0.3111 0.9977 -5.1696 4.5474 False
np_baseline_33_knn np_cebra_33_knn 6.0 0.0132 1.1415 10.8585 True
np_baseline_33_knn np_cebra_joint_33_knn 11.0667 0.0 6.2081 15.9252 True
np_cebra_33_knn np_cebra_joint_33_knn 5.0667 0.0395 0.2081 9.9252 True
----------------------------------------------------------------------------------
For 200 neurons from np recording (33ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
==================================================================================
group1 group2 meandiff p-adj lower upper reject
----------------------------------------------------------------------------------
np_baseline_33_bayes np_baseline_33_knn -11.6444 0.0005 -18.0394 -5.2495 True
np_baseline_33_bayes np_cebra_33_knn 3.7333 0.3703 -2.6617 10.1283 False
np_baseline_33_bayes np_cebra_joint_33_knn 8.8 0.0058 2.405 15.195 True
np_baseline_33_knn np_cebra_33_knn 15.3778 0.0 8.9828 21.7728 True
np_baseline_33_knn np_cebra_joint_33_knn 20.4444 0.0 14.0495 26.8394 True
np_cebra_33_knn np_cebra_joint_33_knn 5.0667 0.1478 -1.3283 11.4617 False
----------------------------------------------------------------------------------
For 400 neurons from np recording (33ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
==================================================================================
group1 group2 meandiff p-adj lower upper reject
----------------------------------------------------------------------------------
np_baseline_33_bayes np_baseline_33_knn -6.0 0.0044 -10.2102 -1.7898 True
np_baseline_33_bayes np_cebra_33_knn 4.5111 0.0336 0.3009 8.7213 True
np_baseline_33_bayes np_cebra_joint_33_knn 23.7333 0.0 19.5231 27.9436 True
np_baseline_33_knn np_cebra_33_knn 10.5111 0.0 6.3009 14.7213 True
np_baseline_33_knn np_cebra_joint_33_knn 29.7333 0.0 25.5231 33.9436 True
np_cebra_33_knn np_cebra_joint_33_knn 19.2222 0.0 15.012 23.4324 True
----------------------------------------------------------------------------------
For 600 neurons from np recording (33ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
==================================================================================
group1 group2 meandiff p-adj lower upper reject
----------------------------------------------------------------------------------
np_baseline_33_bayes np_baseline_33_knn -6.8444 0.0125 -12.3415 -1.3474 True
np_baseline_33_bayes np_cebra_33_knn 2.4 0.6063 -3.097 7.897 False
np_baseline_33_bayes np_cebra_joint_33_knn 26.5333 0.0 21.0363 32.0304 True
np_baseline_33_knn np_cebra_33_knn 9.2444 0.001 3.7474 14.7415 True
np_baseline_33_knn np_cebra_joint_33_knn 33.3778 0.0 27.8807 38.8748 True
np_cebra_33_knn np_cebra_joint_33_knn 24.1333 0.0 18.6363 29.6304 True
----------------------------------------------------------------------------------
For 800 neurons from np recording (33ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
==================================================================================
group1 group2 meandiff p-adj lower upper reject
----------------------------------------------------------------------------------
np_baseline_33_bayes np_baseline_33_knn -9.3778 0.0006 -14.6758 -4.0798 True
np_baseline_33_bayes np_cebra_33_knn 9.0667 0.0008 3.7687 14.3647 True
np_baseline_33_bayes np_cebra_joint_33_knn 22.9111 0.0 17.6131 28.2091 True
np_baseline_33_knn np_cebra_33_knn 18.4444 0.0 13.1464 23.7425 True
np_baseline_33_knn np_cebra_joint_33_knn 32.2889 0.0 26.9909 37.5869 True
np_cebra_33_knn np_cebra_joint_33_knn 13.8444 0.0 8.5464 19.1425 True
----------------------------------------------------------------------------------
For 900 neurons from np recording (33ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
==================================================================================
group1 group2 meandiff p-adj lower upper reject
----------------------------------------------------------------------------------
np_baseline_33_bayes np_baseline_33_knn -11.0 0.0004 -16.9047 -5.0953 True
np_baseline_33_bayes np_cebra_33_knn 8.3111 0.0048 2.4065 14.2158 True
np_baseline_33_bayes np_cebra_joint_33_knn 22.4667 0.0 16.562 28.3713 True
np_baseline_33_knn np_cebra_33_knn 19.3111 0.0 13.4065 25.2158 True
np_baseline_33_knn np_cebra_joint_33_knn 33.4667 0.0 27.562 39.3713 True
np_cebra_33_knn np_cebra_joint_33_knn 14.1556 0.0 8.2509 20.0602 True
----------------------------------------------------------------------------------
For 1000 neurons from np recording (33ms):
Multiple Comparison of Means - Tukey HSD, FWER=0.05
==================================================================================
group1 group2 meandiff p-adj lower upper reject
----------------------------------------------------------------------------------
np_baseline_33_bayes np_baseline_33_knn -10.0889 0.0 -14.5064 -5.6713 True
np_baseline_33_bayes np_cebra_33_knn 15.4667 0.0 11.0491 19.8842 True
np_baseline_33_bayes np_cebra_joint_33_knn 22.3778 0.0 17.9602 26.7953 True
np_baseline_33_knn np_cebra_33_knn 25.5556 0.0 21.138 29.9731 True
np_baseline_33_knn np_cebra_joint_33_knn 32.4667 0.0 28.0491 36.8842 True
np_cebra_33_knn np_cebra_joint_33_knn 6.9111 0.0019 2.4936 11.3287 True
----------------------------------------------------------------------------------