diff --git a/MARBLE/__init__.py b/MARBLE/__init__.py
index 39fc9571..3735f76f 100644
--- a/MARBLE/__init__.py
+++ b/MARBLE/__init__.py
@@ -1,4 +1,5 @@
"""MARBLE main functions."""
+
from MARBLE.main import net
from MARBLE.postprocessing import distribution_distances
from MARBLE.postprocessing import embed_in_2D
diff --git a/MARBLE/dataloader.py b/MARBLE/dataloader.py
index 3a49a796..3ab73ba8 100644
--- a/MARBLE/dataloader.py
+++ b/MARBLE/dataloader.py
@@ -1,4 +1,5 @@
"""Data loader module."""
+
import torch
from torch_cluster import random_walk
from torch_geometric.loader import NeighborSampler as NS
diff --git a/MARBLE/dynamics.py b/MARBLE/dynamics.py
index c80bafc8..4c0ec8ee 100644
--- a/MARBLE/dynamics.py
+++ b/MARBLE/dynamics.py
@@ -2,6 +2,7 @@
TODO: clean this up
"""
+
import sys
import numpy as np
diff --git a/MARBLE/geometry.py b/MARBLE/geometry.py
index 9271d47e..a01e2def 100644
--- a/MARBLE/geometry.py
+++ b/MARBLE/geometry.py
@@ -1,4 +1,5 @@
"""Geometry module."""
+
import numpy as np
import ot
import scipy.sparse as sp
@@ -196,7 +197,7 @@ def compute_distribution_distances(clusters=None, data=None, slices=None):
centroid_distances: distances between cluster centroids
"""
s = slices
-
+ pdists, cdists = None, None
if clusters is not None:
# compute discrete measures supported on cluster centroids
labels = clusters["labels"]
@@ -231,7 +232,7 @@ def compute_distribution_distances(clusters=None, data=None, slices=None):
for j in range(i + 1, nl):
mu, nu = bins_dataset[i], bins_dataset[j]
- if data is not None:
+ if data is not None and pdists is not None:
cdists = pdists[s[i] : s[i + 1], s[j] : s[j + 1]]
dist[i, j] = ot.emd2(mu, nu, cdists)
@@ -355,7 +356,7 @@ def manifold_dimension(Sigma, frac_explained=0.9):
return int(dim_man)
-def fit_graph(x, graph_type="cknn", par=1, delta=1.0, metric='euclidean'):
+def fit_graph(x, graph_type="cknn", par=1, delta=1.0, metric="euclidean"):
"""Fit graph to node positions"""
if graph_type == "cknn":
diff --git a/MARBLE/layers.py b/MARBLE/layers.py
index 52b4d7b6..d635ed75 100644
--- a/MARBLE/layers.py
+++ b/MARBLE/layers.py
@@ -1,4 +1,5 @@
"""Layer module."""
+
import torch
from torch import nn
from torch_geometric.nn.conv import MessagePassing
diff --git a/MARBLE/lib/cknn.py b/MARBLE/lib/cknn.py
index 65cd11e7..fbf63a65 100644
--- a/MARBLE/lib/cknn.py
+++ b/MARBLE/lib/cknn.py
@@ -1,4 +1,5 @@
"""Module imported and adapted from https://github.com/chlorochrule/cknn."""
+
import numpy as np
from scipy.sparse import csr_matrix
from scipy.spatial.distance import pdist
diff --git a/MARBLE/main.py b/MARBLE/main.py
index 4d1ad183..e10658d2 100644
--- a/MARBLE/main.py
+++ b/MARBLE/main.py
@@ -1,4 +1,5 @@
"""Main network"""
+
import glob
import os
import warnings
@@ -77,6 +78,7 @@ def __init__(self, data, loadpath=None, params=None, verbose=True):
self.setup_layers()
self.loss = loss_fun()
self.reset_parameters()
+ self.timestamp = None
if verbose:
utils.print_settings(self)
@@ -172,7 +174,7 @@ def setup_layers(self):
cum_channels = s * (1 - d ** (o + 1)) // (1 - d)
if not self.params["include_self"]:
cum_channels -= s
-
+
if self.params["inner_product_features"]:
cum_channels //= s
if s == 1:
@@ -350,7 +352,7 @@ def fit(self, data, outdir=None, verbose=False):
self.timestamp = datetime.now().strftime("%Y%m%d-%H%M%S")
- print("\n---- Timestamp: {}".format(self.timestamp))
+ print(f"\n---- Timestamp: {self.timestamp}")
# load to gpu (if possible)
# pylint: disable=self-cls-assignment
diff --git a/MARBLE/plotting.py b/MARBLE/plotting.py
index c6c06674..9b7c8f31 100644
--- a/MARBLE/plotting.py
+++ b/MARBLE/plotting.py
@@ -1,4 +1,5 @@
"""Plotting module."""
+
import matplotlib
import matplotlib.pyplot as plt
import networkx as nx
@@ -182,6 +183,8 @@ def embedding(
emb = data.emb_2D
elif isinstance(data, np.ndarray) or torch.is_tensor(data):
emb = data
+ else:
+ raise TypeError
dim = emb.shape[1]
assert dim in [2, 3], f"Embedding dimension is {dim} which cannot be displayed."
@@ -531,7 +534,7 @@ def trajectories(
Args:
X (np array): Positions
V (np array): Velocities
- ax (matplotlib axes object): If specificed, it will plot on existing axes. The default is None
+ ax (matplotlib axes object): If specificed, it will plot on existing axes. Default is None
style (string): Plotting style. 'o' for scatter plot or '-' for line plot
node_feature: Color lines. The default is None
lw (int): Line width
@@ -605,9 +608,7 @@ def trajectories(
X, V = X[skip], V[skip]
plot_arrows(X, V, ax, c, width=lw, scale=scale)
else:
- raise Exception(
- "Data dimension is: {}. It needs to be 2 or 3 to allow plotting.".format(dim)
- )
+ raise Exception(f"Data dimension is: {dim}. It needs to be 2 or 3 to allow plotting.")
set_axes(ax, axes_visible=axes_visible)
@@ -690,7 +691,7 @@ def create_axis(*args, fig=None):
elif dim == 3:
ax = fig.add_subplot(*args, projection="3d")
else:
- raise Exception("Data dimension is {}. We can only plot 2D or 3D data.".format(dim))
+ raise Exception(f"Data dimension is {dim}. We can only plot 2D or 3D data.")
return fig, ax
diff --git a/MARBLE/postprocessing.py b/MARBLE/postprocessing.py
index b60ee880..542cd411 100644
--- a/MARBLE/postprocessing.py
+++ b/MARBLE/postprocessing.py
@@ -1,4 +1,5 @@
"""Postprocessing module."""
+
import numpy as np
from MARBLE import geometry as g
diff --git a/MARBLE/preprocessing.py b/MARBLE/preprocessing.py
index b56ea33b..e6a526e3 100644
--- a/MARBLE/preprocessing.py
+++ b/MARBLE/preprocessing.py
@@ -1,4 +1,5 @@
"""Preprocessing module."""
+
import torch
from torch_geometric.data import Batch
from torch_geometric.data import Data
@@ -16,14 +17,13 @@ def construct_dataset(
graph_type="cknn",
k=20,
delta=1.0,
- n_eigenvalues=None,
frac_geodesic_nb=1.5,
spacing=0.0,
number_of_resamples=1,
var_explained=0.9,
local_gauges=False,
seed=None,
- metric='euclidean'
+ metric="euclidean",
):
"""Construct PyG dataset from node positions and features.
@@ -35,8 +35,6 @@ def construct_dataset(
graph_type: type of nearest-neighbours graph: cknn (default), knn or radius
k: number of nearest-neighbours to construct the graph
delta: argument for cknn graph construction to decide the radius for each points.
- n_eigenvalues: number of eigenvalue/eigenvector pairs to compute (None means all,
- but this can be slow)
frac_geodesic_nb: number of geodesic neighbours to fit the gauges to
to map to tangent space k*frac_geodesic_nb
stop_crit: stopping criterion for furthest point sampling
@@ -44,7 +42,7 @@ def construct_dataset(
var_explained: fraction of variance explained by the local gauges
local_gauges: is True, it will try to compute local gauges if it can (signal dim is > 2,
embedding dimension is > 2 or dim embedding is not dim of manifold)
- seed: Specify for reproducibility in the furthest point sampling.
+ seed: Specify for reproducibility in the furthest point sampling.
The default is None, which means a random starting vertex.
"""
@@ -78,9 +76,11 @@ def construct_dataset(
sample_ind, _ = g.furthest_point_sampling(a, spacing=spacing, start_idx=start_idx)
sample_ind, _ = torch.sort(sample_ind) # this will make postprocessing easier
a_, v_, l_, m_ = a[sample_ind], v[sample_ind], l[sample_ind], m[sample_ind]
-
+
# fit graph to point cloud
- edge_index, edge_weight = g.fit_graph(a_, graph_type=graph_type, par=k, delta=delta, metric=metric)
+ edge_index, edge_weight = g.fit_graph(
+ a_, graph_type=graph_type, par=k, delta=delta, metric=metric
+ )
# define data object
data_ = Data(
@@ -113,7 +113,7 @@ def construct_dataset(
n_geodesic_nb=k * frac_geodesic_nb,
var_explained=var_explained,
)
-
+
def _compute_geometric_objects(
data,
diff --git a/MARBLE/smoothing.py b/MARBLE/smoothing.py
index 4d4f5f3b..16ab1d9b 100644
--- a/MARBLE/smoothing.py
+++ b/MARBLE/smoothing.py
@@ -1,5 +1,4 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
+"""Smoothing module."""
import torch
diff --git a/MARBLE/utils.py b/MARBLE/utils.py
index a848984e..73bd4509 100644
--- a/MARBLE/utils.py
+++ b/MARBLE/utils.py
@@ -1,4 +1,5 @@
"""Utils module."""
+
import multiprocessing
from functools import partial
from typing import NamedTuple
diff --git a/examples/macaque_reaching/.virtual_documents/analysis.ipynb b/examples/macaque_reaching/.virtual_documents/analysis.ipynb
deleted file mode 100644
index cd98ba87..00000000
--- a/examples/macaque_reaching/.virtual_documents/analysis.ipynb
+++ /dev/null
@@ -1,244 +0,0 @@
-
-
-
-!pip install plotly
-
-import numpy as np
-import pandas as pd
-
-import matplotlib.pylab as pl
-import plotly.express as px
-import matplotlib.pyplot as plt
-import plotly
-import plotly.graph_objs as go
-from sklearn.decomposition import PCA
-
-import pickle
-
-from sklearn.metrics import pairwise_distances
-import torch.nn as nn
-import torch
-
-from MARBLE import geometry
-
-
-
-
-
-# insert the pickle file of results that you want to visualise
-!mkdir data
-!wget -nc https://dataverse.harvard.edu/api/access/datafile/7062022 -O data/marble_embeddings_20ms_out20.pkl
-with open('./data/marble_embeddings_20ms_out20.pkl', 'rb') as handle:
- data = pickle.load(handle)
-
-# extracting the various sub lists of data
-distance_matrices = data[0]
-embeddings = data[1]
-timepoints = data[2]
-labels = data[3]
-sample_inds = data[4]
-trial_ids = data[5]
-
-# assigning the condition labels
-conditions=['DownLeft','Left','UpLeft','Up','UpRight','Right','DownRight']
-
-# load the LFADS data (inside the kinematics data file)
-!wget -nc https://dataverse.harvard.edu/api/access/datafile/6969885 -O data/kinematics.pkl
-kinematic_data = pickle.load(open('data/kinematics.pkl','rb'))
-
-
-
-
-
-colors = pl.cm.viridis(np.linspace(0,1,7))
-
-# Configure Plotly to be rendered inline in the notebook.
-plotly.offline.init_notebook_mode()
-
-# looping over 10 different sessions
-examples = [5,6,8,11,14,15,18,23,26,32] # these sessions were used in Figure S7
-for i in range(len(examples)):
- d = examples[i]
- emb = embeddings[d]
- label = labels[d]
- time = np.hstack(timepoints[d])
- # Configure the trace.
- data = []
-
- for i in range(7):
- trace = go.Scatter3d(
- x=emb[label==i,0],
- y=emb[label==i,1],
- z=emb[label==i,2],
- mode='markers',
- marker={
- 'size': 1,
- 'opacity': 1,
- 'color':'rgb({},{},{})'.format(colors[i,0],colors[i,1],colors[i,2]), # set color to an array/list of desired values
- },
- )
- data.append(trace)
-
- # Configure the layout.
- layout = go.Layout(
- paper_bgcolor='rgba(0,0,0,0)',
- plot_bgcolor='rgba(0,0,0,0)',
- xaxis=dict(showgrid=False,showline=False),
- yaxis=dict(showgrid=False,showline=False)
- )
-
- plot_figure = go.Figure(data=data, layout=layout)
- plot_figure.update_scenes(xaxis_visible=False, yaxis_visible=False,zaxis_visible=False )
-
- # Render the plot.
- plot_figure.show()
-
-
-
-
-
-colors = pl.cm.viridis(np.linspace(0,1,7))
-
-# Configure Plotly to be rendered inline in the notebook.
-plotly.offline.init_notebook_mode()
-
-examples = [5,6,8,11,14,15,18,23,26,32]
-
-for i in range(len(examples)):
- d = examples[i]
-
-
- lfads_data = [[] for cond in conditions]
- all_data = []
- for c,cond in enumerate(conditions):
- for t in kinematic_data[d].keys():
- if kinematic_data[d][t]['condition']==cond:
- meh = kinematic_data[d][t]['lfads_factors']
- lfads_data[c].append(meh)
- all_data.append(meh)
-
- lfads_data = [np.hstack(u) for u in lfads_data]
- all_data = np.hstack(all_data)
-
- # need to PCA high dimension lfads data
- pca = PCA(n_components=3)
- pca.fit(all_data.T)
-
-
- # Configure the trace.
- data = []
-
- for i in range(7):
- emb = pca.transform(lfads_data[i].T)
- trace = go.Scatter3d(
- x=emb[:,0],
- y=emb[:,1],
- z=emb[:,2],
- mode='markers',
- marker={
- 'size': 1,
- 'opacity': 1,
- 'color':'rgb({},{},{})'.format(colors[i,0],colors[i,1],colors[i,2]), # set color to an array/list of desired values
- },
- )
- data.append(trace)
-
- # Configure the layout.
- layout = go.Layout(
- paper_bgcolor='rgba(0,0,0,0)',
- plot_bgcolor='rgba(0,0,0,0)',
- xaxis=dict(showgrid=False,showline=False),
- yaxis=dict(showgrid=False,showline=False)
- )
-
- #data = [trace]
-
- plot_figure = go.Figure(data=data, layout=layout)
- plot_figure.update_scenes(xaxis_visible=False, yaxis_visible=False,zaxis_visible=False )
-
- # Render the plot.
- plot_figure.show()
- #plotly.offline.iplot(plot_figure)
-
-
-
-
-
-
-
-
-# plot average distance matrix based on clustering
-plt.figure()
-plt.imshow(np.mean(np.dstack(distance_matrices),2)); plt.colorbar()
-
-emb_MDS, _ = geometry.embed(np.mean(np.dstack(distance_matrices),2), embed_typ = 'MDS')
-plt.figure()
-plt.scatter(emb_MDS[:,0],emb_MDS[:,1],c=np.linspace(0,6,7))
-
-
-
-
-
-# we first need to compute distance matrices for lfads
-
-distance_matrices_lfads = []
-
-# loop over sessions and compute distance matrices
-for d in range(len(embeddings)):
-
- lfads_data = [[] for cond in conditions]
- for t in kinematic_data[d].keys():
- for c,cond in enumerate(conditions):
- if kinematic_data[d][t]['condition'] == cond:
- meh = kinematic_data[d][t]['lfads_factors']
- lfads_data[c].append(meh)
-
- lfads_data = [np.hstack(u).T for u in lfads_data]
-
- distances = np.zeros([len(conditions), len(conditions)])
- for i in range(len(conditions)):
- for j in range(len(conditions)):
- if i == j:
- distances[i,j] = 0
- else:
- distances[i,j] = pairwise_distances(lfads_data[i], lfads_data[j]).mean()
-
- distances = distances/np.std(distances)
- distance_matrices_lfads.append(distances)
-
-
-# plot average distance matrix based on clustering
-plt.figure()
-plt.imshow(np.mean(np.dstack(distance_matrices_lfads),2))
-plt.colorbar()
-
-emb_MDS, _ = geometry.embed(np.mean(np.dstack(distance_matrices_lfads),2), embed_typ='MDS')
-plt.figure()
-plt.scatter(emb_MDS[:,0], emb_MDS[:,1], c=np.linspace(0,6,7))
-
-
-
-
-
-
-
-
-examples = [5,6,8,11,14,15,18,23,26,32] # same chosen sessions as earlier
-fig, axs = plt.subplots(4,len(examples),figsize=(15,5))
-
-# loop over example sessions
-for i,idx in enumerate(examples):
-
- # plot distance matrix for marble
- axs[0, i].imshow(distance_matrices[idx])
-
- # plot distance matrix for LFADS
- axs[1, i].imshow(distance_matrices_lfads[idx])
-
- # plot MDS embedding of MARBLE distance matrix
- emb_MDS, _ = geometry.embed(distance_matrices[idx], embed_typ = 'MDS')
- axs[2, i].scatter(emb_MDS[:,0],emb_MDS[:,1],c=np.linspace(0,6,7))
-
- # plot MDS embedding of LFADS distance matrix
- emb_MDS, _ = geometry.embed(distance_matrices_lfads[idx], embed_typ = 'MDS')
- axs[3, i].scatter(emb_MDS[:,0],emb_MDS[:,1],c=np.linspace(0,6,7))
diff --git a/examples/macaque_reaching/plot_vector_fields.ipynb b/examples/macaque_reaching/plot_vector_fields.ipynb
index 4137e08b..dbc0645c 100644
--- a/examples/macaque_reaching/plot_vector_fields.ipynb
+++ b/examples/macaque_reaching/plot_vector_fields.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": null,
"id": "c9dbe513",
"metadata": {},
"outputs": [],
@@ -29,33 +29,10 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": null,
"id": "5fd6f954",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
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- "Resolving dataverse.harvard.edu (dataverse.harvard.edu)... 34.202.108.237, 52.44.148.164, 54.208.155.175\n",
- "Connecting to dataverse.harvard.edu (dataverse.harvard.edu)|34.202.108.237|:443... connected.\n",
- "HTTP request sent, awaiting response... 303 See Other\n",
- "Location: https://dvn-cloud.s3.amazonaws.com/10.7910/DVN/KTE4PC/186a1ff26a0-91ca6b72e715?response-content-disposition=attachment%3B%20filename%2A%3DUTF-8%27%27conditions_spiking_data.mat&response-content-type=application%2Fx-hdf5&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240516T090542Z&X-Amz-SignedHeaders=host&X-Amz-Expires=3600&X-Amz-Credential=AKIAIEJ3NV7UYCSRJC7A%2F20240516%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=fb54a9d2dc1f8f7d019638d2887a1b4974ff16c9091ae824f8def4bfab57573f [following]\n",
- "--2024-05-16 11:05:42-- https://dvn-cloud.s3.amazonaws.com/10.7910/DVN/KTE4PC/186a1ff26a0-91ca6b72e715?response-content-disposition=attachment%3B%20filename%2A%3DUTF-8%27%27conditions_spiking_data.mat&response-content-type=application%2Fx-hdf5&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240516T090542Z&X-Amz-SignedHeaders=host&X-Amz-Expires=3600&X-Amz-Credential=AKIAIEJ3NV7UYCSRJC7A%2F20240516%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=fb54a9d2dc1f8f7d019638d2887a1b4974ff16c9091ae824f8def4bfab57573f\n",
- "Resolving dvn-cloud.s3.amazonaws.com (dvn-cloud.s3.amazonaws.com)... 16.182.107.105, 52.216.95.139, 54.231.194.217, ...\n",
- "Connecting to dvn-cloud.s3.amazonaws.com (dvn-cloud.s3.amazonaws.com)|16.182.107.105|:443... connected.\n",
- "HTTP request sent, awaiting response... 200 OK\n",
- "Length: 92990658 (89M) [application/x-hdf5]\n",
- "Saving to: ‘data/conditions_spiking_data.mat’\n",
- "\n",
- "data/conditions_spi 100%[===================>] 88.68M 1.20MB/s in 41s \n",
- "\n",
- "2024-05-16 11:06:24 (2.16 MB/s) - ‘data/conditions_spiking_data.mat’ saved [92990658/92990658]\n",
- "\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"# load data compiled into matlab cell array\n",
"!wget -nc https://dataverse.harvard.edu/api/access/datafile/6963157 -O data/conditions_spiking_data.mat\n",
@@ -64,61 +41,10 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": null,
"id": "c578b742",
"metadata": {},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "bd50650e4e4f4a65997a9165e8e906af",
- "version_major": 2,
- "version_minor": 0
- },
- "image/png": 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- "version_minor": 0
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",
- "text/html": [
- "\n",
- " \n",
- "
\n",
- " Figure\n",
- "
\n",
- "
\n",
- "
\n",
- " "
- ],
- "text/plain": [
- "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"trial = 1\n",
"session = 9\n",
@@ -144,18 +70,10 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": null,
"id": "4424eb17",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "File ‘data/raw_data_session_9_3D.pkl’ already there; not retrieving.\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"!wget -nc https://dataverse.harvard.edu/api/access/datafile/7062086 -O data/raw_data_session_9_3D.pkl\n",
"pos, vel, time, _ = pickle.load(open('data/raw_data_session_9_3D.pkl','rb'))"
@@ -163,36 +81,10 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": null,
"id": "8d8a958a",
"metadata": {},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "fdd020c516694b4ea9a16e20a7c7e3e5",
- "version_major": 2,
- "version_minor": 0
- },
- "image/png": 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",
- "text/html": [
- "\n",
- " \n",
- "
\n",
- " Figure\n",
- "
\n",
- "
\n",
- "
\n",
- " "
- ],
- "text/plain": [
- "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"fig = plt.figure(figsize=(10,5))\n",
"n_traj=10\n",
@@ -226,117 +118,20 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": null,
"id": "e3b0b713",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "---- Embedding dimension: 3\n",
- "---- Signal dimension: 3\n",
- "\n",
- "\n",
- "---- Computing kernels ... Done \n",
- "---- Computing eigendecomposition ... Done \n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"data = MARBLE.construct_dataset(pos, features=vel, graph_type='cknn', k=10, stop_crit=0.05, local_gauges=False)"
]
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": null,
"id": "fb29a0b4",
"metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/Users/arnaudon/base/lib/python3.10/site-packages/ipympl/backend_nbagg.py:336: UserWarning: constrained_layout not applied because axes sizes collapsed to zero. Try making figure larger or axes decorations smaller.\n",
- " self.figure.savefig(buf, format='png', dpi='figure')\n"
- ]
- },
- {
- "data": {
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- "model_id": "5c6d518091dd4f4b8403fbcdce68b97a",
- "version_major": 2,
- "version_minor": 0
- },
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",
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- ],
+ "outputs": [],
"source": [
"data_plot = data.to_data_list()\n",
"for i in [1,4,6]:\n",
@@ -374,7 +169,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.9.13"
+ "version": "3.10.14"
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diff --git a/examples/macaque_reaching/sensitivity_analysis.ipynb b/examples/macaque_reaching/sensitivity_analysis.ipynb
index 5459f660..f441a778 100644
--- a/examples/macaque_reaching/sensitivity_analysis.ipynb
+++ b/examples/macaque_reaching/sensitivity_analysis.ipynb
@@ -12,80 +12,24 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": null,
"id": "fad76ae4-0f2a-4cb8-8a1c-41972819185e",
"metadata": {
"tags": []
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Requirement already satisfied: statannotations in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (0.6.0)\n",
- "Requirement already satisfied: ipympl in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (0.9.3)\n",
- "Requirement already satisfied: seaborn<0.12,>=0.9.0 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from statannotations) (0.11.2)\n",
- "Requirement already satisfied: pandas<2.0.0,>=0.23.0 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from statannotations) (1.5.3)\n",
- "Requirement already satisfied: matplotlib>=2.2.2 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from statannotations) (3.5.2)\n",
- "Requirement already satisfied: numpy>=1.12.1 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from statannotations) (1.23.3)\n",
- "Requirement already satisfied: scipy>=1.1.0 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from statannotations) (1.13.0)\n",
- "Requirement already satisfied: pillow in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipympl) (9.2.0)\n",
- "Requirement already satisfied: ipython-genutils in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipympl) (0.2.0)\n",
- "Requirement already satisfied: ipywidgets<9,>=7.6.0 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipympl) (8.1.1)\n",
- "Requirement already satisfied: traitlets<6 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipympl) (5.7.1)\n",
- "Requirement already satisfied: ipython<9 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipympl) (8.15.0)\n",
- "Requirement already satisfied: pickleshare in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipython<9->ipympl) (0.7.5)\n",
- "Requirement already satisfied: prompt-toolkit!=3.0.37,<3.1.0,>=3.0.30 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipython<9->ipympl) (3.0.43)\n",
- "Requirement already satisfied: stack-data in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipython<9->ipympl) (0.2.0)\n",
- "Requirement already satisfied: backcall in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipython<9->ipympl) (0.2.0)\n",
- "Requirement already satisfied: pygments>=2.4.0 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipython<9->ipympl) (2.17.2)\n",
- "Requirement already satisfied: decorator in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipython<9->ipympl) (5.1.1)\n",
- "Requirement already satisfied: jedi>=0.16 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipython<9->ipympl) (0.18.1)\n",
- "Requirement already satisfied: exceptiongroup in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipython<9->ipympl) (1.2.0)\n",
- "Requirement already satisfied: typing-extensions in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipython<9->ipympl) (4.3.0)\n",
- "Requirement already satisfied: matplotlib-inline in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipython<9->ipympl) (0.1.6)\n",
- "Requirement already satisfied: pexpect>4.3 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipython<9->ipympl) (4.8.0)\n",
- "Requirement already satisfied: widgetsnbextension~=4.0.9 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipywidgets<9,>=7.6.0->ipympl) (4.0.9)\n",
- "Requirement already satisfied: jupyterlab-widgets~=3.0.9 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipywidgets<9,>=7.6.0->ipympl) (3.0.9)\n",
- "Requirement already satisfied: comm>=0.1.3 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from ipywidgets<9,>=7.6.0->ipympl) (0.2.1)\n",
- "Requirement already satisfied: kiwisolver>=1.0.1 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from matplotlib>=2.2.2->statannotations) (1.4.2)\n",
- "Requirement already satisfied: fonttools>=4.22.0 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from matplotlib>=2.2.2->statannotations) (4.25.0)\n",
- "Requirement already satisfied: cycler>=0.10 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from matplotlib>=2.2.2->statannotations) (0.11.0)\n",
- "Requirement already satisfied: packaging>=20.0 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from matplotlib>=2.2.2->statannotations) (21.3)\n",
- "Requirement already satisfied: pyparsing>=2.2.1 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from matplotlib>=2.2.2->statannotations) (3.0.9)\n",
- "Requirement already satisfied: python-dateutil>=2.7 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from matplotlib>=2.2.2->statannotations) (2.8.2)\n",
- "Requirement already satisfied: pytz>=2020.1 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from pandas<2.0.0,>=0.23.0->statannotations) (2022.1)\n",
- "Requirement already satisfied: parso<0.9.0,>=0.8.0 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from jedi>=0.16->ipython<9->ipympl) (0.8.3)\n",
- "Requirement already satisfied: ptyprocess>=0.5 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from pexpect>4.3->ipython<9->ipympl) (0.7.0)\n",
- "Requirement already satisfied: wcwidth in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from prompt-toolkit!=3.0.37,<3.1.0,>=3.0.30->ipython<9->ipympl) (0.2.5)\n",
- "Requirement already satisfied: six>=1.5 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from python-dateutil>=2.7->matplotlib>=2.2.2->statannotations) (1.16.0)\n",
- "Requirement already satisfied: asttokens in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from stack-data->ipython<9->ipympl) (2.0.5)\n",
- "Requirement already satisfied: executing in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from stack-data->ipython<9->ipympl) (0.8.3)\n",
- "Requirement already satisfied: pure-eval in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from stack-data->ipython<9->ipympl) (0.2.2)\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"!pip install statannotations ipympl"
]
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": null,
"id": "cae68224-84f6-43fd-82f4-bba80b806780",
"metadata": {
"tags": []
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "The autoreload extension is already loaded. To reload it, use:\n",
- " %reload_ext autoreload\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2\n",
@@ -114,36 +58,12 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": null,
"id": "c2883f5a-4789-49e2-8d43-1b3946c3a4fd",
"metadata": {
"tags": []
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "mkdir: cannot create directory ‘data’: File exists\n",
- "--2024-05-16 10:51:31-- https://dataverse.harvard.edu/api/access/datafile/6969885\n",
- "Resolving dataverse.harvard.edu (dataverse.harvard.edu)... 52.44.148.164, 54.208.155.175, 34.202.108.237\n",
- "Connecting to dataverse.harvard.edu (dataverse.harvard.edu)|52.44.148.164|:443... connected.\n",
- "HTTP request sent, awaiting response... 303 See Other\n",
- "Location: https://dvn-cloud.s3.amazonaws.com/10.7910/DVN/KTE4PC/186b7fe5793-1cea5dcce735?response-content-disposition=attachment%3B%20filename%2A%3DUTF-8%27%27kinematics.pkl&response-content-type=application%2Foctet-stream&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240516T085131Z&X-Amz-SignedHeaders=host&X-Amz-Expires=3600&X-Amz-Credential=AKIAIEJ3NV7UYCSRJC7A%2F20240516%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=28125bc046c127d5ed8398cdc68f2dba267f520fab690b2ab3a4a95a6629700b [following]\n",
- "--2024-05-16 10:51:32-- https://dvn-cloud.s3.amazonaws.com/10.7910/DVN/KTE4PC/186b7fe5793-1cea5dcce735?response-content-disposition=attachment%3B%20filename%2A%3DUTF-8%27%27kinematics.pkl&response-content-type=application%2Foctet-stream&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240516T085131Z&X-Amz-SignedHeaders=host&X-Amz-Expires=3600&X-Amz-Credential=AKIAIEJ3NV7UYCSRJC7A%2F20240516%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=28125bc046c127d5ed8398cdc68f2dba267f520fab690b2ab3a4a95a6629700b\n",
- "Resolving dvn-cloud.s3.amazonaws.com (dvn-cloud.s3.amazonaws.com)... 52.216.58.145, 52.216.245.148, 52.217.116.73, ...\n",
- "Connecting to dvn-cloud.s3.amazonaws.com (dvn-cloud.s3.amazonaws.com)|52.216.58.145|:443... connected.\n",
- "HTTP request sent, awaiting response... 200 OK\n",
- "Length: 91102657 (87M) [application/octet-stream]\n",
- "Saving to: ‘data/kinematics.pkl’\n",
- "\n",
- "data/kinematics.pkl 100%[===================>] 86.88M 22.2MB/s in 4.4s \n",
- "\n",
- "2024-05-16 10:51:36 (19.6 MB/s) - ‘data/kinematics.pkl’ saved [91102657/91102657]\n",
- "\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"!mkdir data\n",
"!wget -nc https://dataverse.harvard.edu/api/access/datafile/6969885 -O data/kinematics.pkl\n",
@@ -162,99 +82,12 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": null,
"id": "e9bc422a",
"metadata": {
"tags": []
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
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- "HTTP request sent, awaiting response... 303 See Other\n",
- "Location: https://dvn-cloud.s3.amazonaws.com/10.7910/DVN/KTE4PC/18f80857c78-3880d865fa45?response-content-disposition=attachment%3B%20filename%2A%3DUTF-8%27%27marble_embeddings_out20_pca5_25ms.pkl&response-content-type=application%2Foctet-stream&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240516T085138Z&X-Amz-SignedHeaders=host&X-Amz-Expires=3600&X-Amz-Credential=AKIAIEJ3NV7UYCSRJC7A%2F20240516%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=9242385a0b7d689c2d35f28f56e37ac12e98c0c588243ddb156ba7a939c7a29b [following]\n",
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- "Resolving dvn-cloud.s3.amazonaws.com (dvn-cloud.s3.amazonaws.com)... 52.216.58.145, 52.216.245.148, 52.217.116.73, ...\n",
- "Connecting to dvn-cloud.s3.amazonaws.com (dvn-cloud.s3.amazonaws.com)|52.216.58.145|:443... connected.\n",
- "HTTP request sent, awaiting response... 200 OK\n",
- "Length: 26253472 (25M) [application/octet-stream]\n",
- "Saving to: ‘data/marble_embeddings_out20_pca5_25ms.pkl’\n",
- "\n",
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- "\n",
- "2024-05-16 10:51:40 (17.5 MB/s) - ‘data/marble_embeddings_out20_pca5_25ms.pkl’ saved [26253472/26253472]\n",
- "\n",
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- "Resolving dataverse.harvard.edu (dataverse.harvard.edu)... 52.44.148.164, 54.208.155.175, 34.202.108.237\n",
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- "HTTP request sent, awaiting response... 303 See Other\n",
- "Location: https://dvn-cloud.s3.amazonaws.com/10.7910/DVN/KTE4PC/18f808573ee-4a3a189e768e?response-content-disposition=attachment%3B%20filename%2A%3DUTF-8%27%27marble_embeddings_out20_pca5_50ms.pkl&response-content-type=application%2Foctet-stream&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240516T085141Z&X-Amz-SignedHeaders=host&X-Amz-Expires=3600&X-Amz-Credential=AKIAIEJ3NV7UYCSRJC7A%2F20240516%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=b06ca109a19605900f1cdd64c1d1aa55d6014c1f30993686665956d85d57178b [following]\n",
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- "Resolving dvn-cloud.s3.amazonaws.com (dvn-cloud.s3.amazonaws.com)... 52.216.58.145, 52.216.245.148, 52.217.116.73, ...\n",
- "Connecting to dvn-cloud.s3.amazonaws.com (dvn-cloud.s3.amazonaws.com)|52.216.58.145|:443... connected.\n",
- "HTTP request sent, awaiting response... 200 OK\n",
- "Length: 26253512 (25M) [application/octet-stream]\n",
- "Saving to: ‘data/marble_embeddings_out20_pca5_50ms.pkl’\n",
- "\n",
- "data/marble_embeddi 100%[===================>] 25.04M 19.0MB/s in 1.3s \n",
- "\n",
- "2024-05-16 10:51:43 (19.0 MB/s) - ‘data/marble_embeddings_out20_pca5_50ms.pkl’ saved [26253512/26253512]\n",
- "\n",
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- "Resolving dataverse.harvard.edu (dataverse.harvard.edu)... 52.44.148.164, 54.208.155.175, 34.202.108.237\n",
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- "HTTP request sent, awaiting response... 303 See Other\n",
- "Location: https://dvn-cloud.s3.amazonaws.com/10.7910/DVN/KTE4PC/18779e1f75a-375f58ac6830?response-content-disposition=attachment%3B%20filename%2A%3DUTF-8%27%27marble_embeddings_out20_pca5_100ms.pkl&response-content-type=application%2Foctet-stream&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240516T085144Z&X-Amz-SignedHeaders=host&X-Amz-Expires=3600&X-Amz-Credential=AKIAIEJ3NV7UYCSRJC7A%2F20240516%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=bd571ee66ac2cd69962a7c9194dcedce5171eaab30b8084f719fbcfbc5de5d5f [following]\n",
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- "Resolving dvn-cloud.s3.amazonaws.com (dvn-cloud.s3.amazonaws.com)... 52.216.58.145, 52.216.245.148, 52.217.116.73, ...\n",
- "Connecting to dvn-cloud.s3.amazonaws.com (dvn-cloud.s3.amazonaws.com)|52.216.58.145|:443... connected.\n",
- "HTTP request sent, awaiting response... 200 OK\n",
- "Length: 53892495 (51M) [application/octet-stream]\n",
- "Saving to: ‘data/marble_embeddings_out20_pca5_100ms.pkl’\n",
- "\n",
- "data/marble_embeddi 100%[===================>] 51.40M 21.0MB/s in 2.4s \n",
- "\n",
- "2024-05-16 10:51:47 (21.0 MB/s) - ‘data/marble_embeddings_out20_pca5_100ms.pkl’ saved [53892495/53892495]\n",
- "\n",
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- "Resolving dataverse.harvard.edu (dataverse.harvard.edu)... 54.208.155.175, 52.44.148.164, 34.202.108.237\n",
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- "Location: https://dvn-cloud.s3.amazonaws.com/10.7910/DVN/KTE4PC/18f80871a31-36951753e64a?response-content-disposition=attachment%3B%20filename%2A%3DUTF-8%27%27marble_embeddings_out20_pca7_100ms.pkl&response-content-type=application%2Foctet-stream&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240516T085147Z&X-Amz-SignedHeaders=host&X-Amz-Expires=3600&X-Amz-Credential=AKIAIEJ3NV7UYCSRJC7A%2F20240516%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=8aa447205ed052109fa2520f9095ef23f9db67cef78950eff25d18df50b0ace4 [following]\n",
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- "Resolving dvn-cloud.s3.amazonaws.com (dvn-cloud.s3.amazonaws.com)... 52.217.122.129, 52.217.227.41, 52.217.36.244, ...\n",
- "Connecting to dvn-cloud.s3.amazonaws.com (dvn-cloud.s3.amazonaws.com)|52.217.122.129|:443... connected.\n",
- "HTTP request sent, awaiting response... 200 OK\n",
- "Length: 30110824 (29M) [application/octet-stream]\n",
- "Saving to: ‘data/marble_embeddings_out20_pca7_100ms.pkl’\n",
- "\n",
- "data/marble_embeddi 100%[===================>] 28.72M 20.1MB/s in 1.4s \n",
- "\n",
- "2024-05-16 10:51:49 (20.1 MB/s) - ‘data/marble_embeddings_out20_pca7_100ms.pkl’ saved [30110824/30110824]\n",
- "\n",
- "--2024-05-16 10:51:50-- https://dataverse.harvard.edu/api/access/datafile/10209905\n",
- "Resolving dataverse.harvard.edu (dataverse.harvard.edu)... 54.208.155.175, 52.44.148.164, 34.202.108.237\n",
- "Connecting to dataverse.harvard.edu (dataverse.harvard.edu)|54.208.155.175|:443... connected.\n",
- "HTTP request sent, awaiting response... 303 See Other\n",
- "Location: https://dvn-cloud.s3.amazonaws.com/10.7910/DVN/KTE4PC/18f80858697-bffef1f72524?response-content-disposition=attachment%3B%20filename%2A%3DUTF-8%27%27marble_embeddings_out20_pca10_100ms.pkl&response-content-type=application%2Foctet-stream&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240516T085150Z&X-Amz-SignedHeaders=host&X-Amz-Expires=3600&X-Amz-Credential=AKIAIEJ3NV7UYCSRJC7A%2F20240516%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=aa463412b6a8e69eec961baf3fd5966812ae1fda6a1125852f833793fe5e7bfd [following]\n",
- "--2024-05-16 10:51:50-- https://dvn-cloud.s3.amazonaws.com/10.7910/DVN/KTE4PC/18f80858697-bffef1f72524?response-content-disposition=attachment%3B%20filename%2A%3DUTF-8%27%27marble_embeddings_out20_pca10_100ms.pkl&response-content-type=application%2Foctet-stream&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240516T085150Z&X-Amz-SignedHeaders=host&X-Amz-Expires=3600&X-Amz-Credential=AKIAIEJ3NV7UYCSRJC7A%2F20240516%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=aa463412b6a8e69eec961baf3fd5966812ae1fda6a1125852f833793fe5e7bfd\n",
- "Resolving dvn-cloud.s3.amazonaws.com (dvn-cloud.s3.amazonaws.com)... 52.217.122.129, 52.217.227.41, 52.217.36.244, ...\n",
- "Connecting to dvn-cloud.s3.amazonaws.com (dvn-cloud.s3.amazonaws.com)|52.217.122.129|:443... connected.\n",
- "HTTP request sent, awaiting response... 200 OK\n",
- "Length: 28872338 (28M) [application/octet-stream]\n",
- "Saving to: ‘data/marble_embeddings_out20_pca10_100ms.pkl’\n",
- "\n",
- "data/marble_embeddi 100%[===================>] 27.53M 5.08MB/s in 14s \n",
- "\n",
- "2024-05-16 10:52:04 (1.98 MB/s) - ‘data/marble_embeddings_out20_pca10_100ms.pkl’ saved [28872338/28872338]\n",
- "\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"!wget -nc https://dataverse.harvard.edu/api/access/datafile/10209904 -O data/marble_embeddings_out20_pca5_25ms.pkl\n",
"\n",
@@ -295,7 +128,7 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": null,
"id": "a1638c8f-f4b7-450b-a16c-981a74353417",
"metadata": {
"tags": []
@@ -328,7 +161,7 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": null,
"id": "b77a49a6",
"metadata": {
"tags": []
@@ -419,73 +252,12 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": null,
"id": "75da5f8b",
"metadata": {
"tags": []
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "p-value annotation legend:\n",
- " ns: 5.00e-02 < p <= 1.00e+00\n",
- " *: 1.00e-02 < p <= 5.00e-02\n",
- " **: 1.00e-03 < p <= 1.00e-02\n",
- " ***: 1.00e-04 < p <= 1.00e-03\n",
- " ****: p <= 1.00e-04\n",
- "\n",
- "marble_5 vs. marble_7: Wilcoxon test (paired samples), P_val:4.768e-05 Stat=8.000e+00\n",
- "Warning: cannot get the text bounding box. Falling back to a fixed y offset. Layout may be not optimal.\n",
- "marble_5 vs. marble_10: Wilcoxon test (paired samples), P_val:1.907e-05 Stat=5.000e+00\n",
- "Warning: cannot get the text bounding box. Falling back to a fixed y offset. Layout may be not optimal.\n",
- "marble_5 vs. marble_5_25: Wilcoxon test (paired samples), P_val:1.907e-06 Stat=0.000e+00\n",
- "Warning: cannot get the text bounding box. Falling back to a fixed y offset. Layout may be not optimal.\n",
- "marble_5 vs. marble_5_50: Wilcoxon test (paired samples), P_val:8.202e-05 Stat=1.000e+01\n",
- "Warning: cannot get the text bounding box. Falling back to a fixed y offset. Layout may be not optimal.\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "(,\n",
- " [,\n",
- " ,\n",
- " ,\n",
- " ])"
- ]
- },
- "execution_count": 21,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "f858d974c40b4a6fbcd95d5e1d826c79",
- "version_major": 2,
- "version_minor": 0
- },
- "image/png": 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- "text/html": [
- "\n",
- " \n",
- "
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- " Figure\n",
- "
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- "
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- "
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- " "
- ],
- "text/plain": [
- "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"results = pd.DataFrame(data=np.vstack([ r2_marble_vel_5, r2_marble_vel_7, r2_marble_vel_10, r2_marble_vel_5_25, r2_marble_vel_5_50]).T,columns=['marble_5','marble_7','marble_10','marble_5_25', 'marble_5_50'])\n",
"results = results.melt()\n",
@@ -522,7 +294,7 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": null,
"id": "91f2c2a7",
"metadata": {
"tags": []
@@ -566,48 +338,12 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": null,
"id": "90c62030",
"metadata": {
"tags": []
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "(0.0, 1.0)"
- ]
- },
- "execution_count": 23,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "4fe11b99bb884f0bbe0880ef96afc49e",
- "version_major": 2,
- "version_minor": 0
- },
- "image/png": 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",
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- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"f, ax = plt.subplots(figsize=(4,4))\n",
"sns.despine(bottom=True, left=True)\n",
@@ -650,7 +386,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.9.13"
+ "version": "3.10.14"
}
},
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diff --git a/examples/rat_hippocampus/decoding.ipynb b/examples/rat_hippocampus/decoding.ipynb
index 95b97576..5deccd93 100644
--- a/examples/rat_hippocampus/decoding.ipynb
+++ b/examples/rat_hippocampus/decoding.ipynb
@@ -11,49 +11,11 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": null,
"metadata": {
"scrolled": true
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Requirement already satisfied: cebra in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (0.4.0)\n",
- "Requirement already satisfied: statannotations in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (0.6.0)\n",
- "Requirement already satisfied: elephant in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (1.1.0)\n",
- "Requirement already satisfied: scikit-learn in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from cebra) (1.1.2)\n",
- "Requirement already satisfied: torch in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from cebra) (1.12.1)\n",
- "Requirement already satisfied: literate-dataclasses in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from cebra) (0.0.6)\n",
- "Requirement already satisfied: scipy in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from cebra) (1.13.0)\n",
- "Requirement already satisfied: joblib in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from cebra) (1.1.0)\n",
- "Requirement already satisfied: matplotlib in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from cebra) (3.5.2)\n",
- "Requirement already satisfied: requests in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from cebra) (2.28.1)\n",
- "Requirement already satisfied: tqdm in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from cebra) (4.64.1)\n",
- "Requirement already satisfied: numpy>=1.12.1 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from statannotations) (1.23.3)\n",
- "Requirement already satisfied: pandas<2.0.0,>=0.23.0 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from statannotations) (1.5.3)\n",
- "Requirement already satisfied: seaborn<0.12,>=0.9.0 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from statannotations) (0.11.2)\n",
- "Requirement already satisfied: neo>=0.10.0 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from elephant) (0.13.1)\n",
- "Requirement already satisfied: six>=1.10.0 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from elephant) (1.16.0)\n",
- "Requirement already satisfied: quantities>=0.14.1 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from elephant) (0.15.0)\n",
- "Requirement already satisfied: cycler>=0.10 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from matplotlib->cebra) (0.11.0)\n",
- "Requirement already satisfied: pyparsing>=2.2.1 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from matplotlib->cebra) (3.0.9)\n",
- "Requirement already satisfied: kiwisolver>=1.0.1 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from matplotlib->cebra) (1.4.2)\n",
- "Requirement already satisfied: fonttools>=4.22.0 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from matplotlib->cebra) (4.25.0)\n",
- "Requirement already satisfied: packaging>=20.0 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from matplotlib->cebra) (21.3)\n",
- "Requirement already satisfied: pillow>=6.2.0 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from matplotlib->cebra) (9.2.0)\n",
- "Requirement already satisfied: python-dateutil>=2.7 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from matplotlib->cebra) (2.8.2)\n",
- "Requirement already satisfied: pytz>=2020.1 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from pandas<2.0.0,>=0.23.0->statannotations) (2022.1)\n",
- "Requirement already satisfied: idna<4,>=2.5 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from requests->cebra) (3.4)\n",
- "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from requests->cebra) (1.26.11)\n",
- "Requirement already satisfied: certifi>=2017.4.17 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from requests->cebra) (2023.11.17)\n",
- "Requirement already satisfied: charset-normalizer<3,>=2 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from requests->cebra) (2.0.4)\n",
- "Requirement already satisfied: threadpoolctl>=2.0.0 in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from scikit-learn->cebra) (2.2.0)\n",
- "Requirement already satisfied: typing_extensions in /mnt/scratch/lts2/gosztolai/miniconda3/envs/MARBLE/lib/python3.9/site-packages (from torch->cebra) (4.3.0)\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"! pip install cebra statannotations elephant\n",
"\n",
@@ -80,18 +42,9 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": null,
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "mkdir: cannot create directory ‘data’: File exists\n",
- "File ‘data/rat_data.pkl’ already there; not retrieving.\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"!mkdir data\n",
"!wget -nc https://dataverse.harvard.edu/api/access/datafile/7609512 -O data/rat_data.pkl\n",
@@ -111,7 +64,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@@ -130,30 +83,9 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": null,
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Text(0.5, 0, 'Time (s)')"
- ]
- },
- "execution_count": 4,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
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