Stimic - Analysis - Stim count

jeu. 08 novembre 2018 by Martin Deudon

Download the notebook : stimic_stim_count.py

Count Stim¶

This notebook show how to count the number of stimulations in function of the different stimulation paremeters from the Stimulation Event File

In [1]:

%matplotlib inline
import matplotlib
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_context('paper')
sns.set()
import re

In [2]:

stim_spreadsheet_path = r'..\data\p42_KR01_stimulations_all.xlsx'
patient_id = 'KR01'

Read the Excel sheet with pandas¶

In [3]:

pd.set_option('display.width', 500)
df = pd.read_excel(stim_spreadsheet_path)
df.style.set_properties(**{'font-size':'5'})
df.head()

Out[3]:

	ID	file	type	time	channelind	channelname	freq	intensity	duration	effect	channelname_bipolar	time-micro	channelname-micro	channelind-micro	filepath-micro
0	P42_KR01	KR01_stim1_clean_clean_raw	Stim 1 Hz	174.4736	96	EEG GC1	1	1.5	10	RAS	EEG GC1-EEG GC2	217.1523	[]	[]	path\to\file
1	P42_KR01	KR01_stim1_clean_clean_raw	Stim 1 Hz	174.4834	97	EEG GC2	1	1.5	10	RAS	EEG GC1-EEG GC2	217.1621	[]	[]	path\to\file
2	P42_KR01	KR01_stim1_clean_clean_raw	Stim 1 Hz	234.5498	97	EEG GC2	1	2.0	10	RAS	EEG GC2-EEG GC3	277.2285	[]	[]	path\to\file
3	P42_KR01	KR01_stim1_clean_clean_raw	Stim 1 Hz	234.5566	98	EEG GC3	1	2.0	10	RAS	EEG GC2-EEG GC3	277.2353	[]	[]	path\to\file
4	P42_KR01	KR01_stim1_clean_clean_raw	Stim 1 Hz	274.1533	98	EEG GC3	1	3.0	20	RAS	EEG GC3-EEG GC4	316.8320	[]	[]	path\to\file

Plot the number of stimulation in function of the frequency, intensity and channel :¶

In [4]:

f = plt.figure(figsize=(16, 12))
ax1 = f.add_subplot(131)
sns.countplot(df['freq'], ax=ax1)
ax2 = f.add_subplot(132)
sns.countplot(df['intensity'], ax=ax2)
ax2.set(title=patient_id)
ax3 = f.add_subplot(133)
sns.countplot(y='channelname', data=df, orient='h', ax=ax3)

Out[4]:

<matplotlib.axes._subplots.AxesSubplot at 0xb0de668>

Another way to count the stimulations, in function of the channel and frequency :¶

In [5]:

f = plt.figure(figsize=(13, 13))
ax = f.add_subplot(111)
ax.set(title=patient_id)
sns.countplot(y='channelname_bipolar', hue='freq', data=df, orient='h', ax=ax)

Out[5]:

<matplotlib.axes._subplots.AxesSubplot at 0xb1b06a0>