ms762wu/EMG_Biometrics_2021
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fix: fix the dl_data_handler so it does

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not create NaN values in the samples
This commit is contained in:
Skudalen 2021-07-01 17:56:20 +02:00
parent 500018b6aa
commit d0978aa2b3
3 changed files with 70 additions and 23 deletions
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64
Handle_emg_data.py
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@ -1,7 +1,10 @@
from numpy.core.arrayprint import IntegerFormat
from numpy.lib import math
import pandas as pd
from pathlib import Path
import numpy as np
from pandas.core.frame import DataFrame
from math import floor
#from Present_data import get_data
class Data_container:
@ -43,6 +46,9 @@ class CSV_handler:
def store_df_in_container(self, filename:str, emg_nr:int, which_arm:str, data_container:Data_container, round:int):
df = self.get_time_emg_table(filename, emg_nr+1)
if df.isnull().values.any():
print('NaN in: subject', data_container.subject_nr, 'arm:', which_arm, 'session:', round, 'emg nr:', emg_nr)
# Places the data correctly:
if round == 1:
if which_arm == 'left':
@ -484,7 +490,8 @@ class DL_data_handler:
def __init__(self, csv_handler:CSV_handler) -> None:
self.csv_handler = csv_handler
self.samples_per_subject = {1: [], # Should med 4 sessions * split nr of samples per person
# Should med 4 sessions * split nr of samples per person. Each sample is structured like [sample_df, samplerate]
self.samples_per_subject = {1: [],
2: [],
3: [],
4: [],
@ -503,21 +510,41 @@ class DL_data_handler:
for emg_nr in range(8):
df, _ = self.csv_handler.get_data(subject_nr, 'right', session_nr, emg_nr+1)
list_of_emgs.append(DataFrame(df[get_emg_str(emg_nr+1)]))
return list_of_emgs # list of emg data where first element also has timestamp column
def make_subj_sample(self, list_of_emgs):
# starting_point:DataFrame = list_of_emgs[0].rename(columns={'emg1':'emg'})
def make_subj_sample(self, list_of_emgs_):
# Test and fix if the emgs have different size
list_of_emgs = []
length_left_emgs = int(len(list_of_emgs_[0].index))
length_right_emgs = int(len(list_of_emgs_[-1].index))
if length_left_emgs < length_right_emgs:
for i in range(16):
new_emg_df = list_of_emgs_[i].head(length_left_emgs)
list_of_emgs.append(new_emg_df)
elif length_right_emgs < length_left_emgs:
for i in range(16):
new_emg_df = list_of_emgs_[i].head(length_right_emgs)
list_of_emgs.append(new_emg_df)
else:
list_of_emgs = list_of_emgs_
tot_session_df_list = []
for i in range(8):
#emg_str = get_emg_str(i)
df = list_of_emgs[i] # .rename(columns={emg_str: 'emg'})
df = list_of_emgs[i]
tot_session_df_list.append(df)
for i in range(1, 9):
emg_str_old = get_emg_str(i)
emg_str_new = get_emg_str(8+i)
df:DataFrame = list_of_emgs[7+i].rename(columns={emg_str_old: emg_str_new})
df = list_of_emgs[7+i].rename(columns={emg_str_old: emg_str_new})
tot_session_df_list.append(df)
tot_session_df = pd.concat(tot_session_df_list, axis=1)
tot_session_df = pd.concat(tot_session_df_list, axis=1, ignore_index=True)
# TESTING FOR NAN
if tot_session_df.isnull().values.any():
print('NaN in: where? THERE')
print(length_left_emgs, length_right_emgs)
#print(tot_session_df_list)
return tot_session_df
@ -527,10 +554,25 @@ class DL_data_handler:
for session_nr in range(4):
list_of_emg = self.get_emg_list(subject_nr+1, session_nr+1)
tot_session_df = self.make_subj_sample(list_of_emg)
# TESTING FOR NAN
if tot_session_df.isnull().values.any():
print('NaN in: subject', subject_nr+1, 'session:', session_nr+1, 'where? AFTER MAKE')
samples = np.array_split(tot_session_df.to_numpy(), split_nr)
for array in samples:
df = DataFrame(array).rename(columns={0:'timestamp'})
'''
# TESTING FOR NAN
if df.isnull().values.any():
print('NaN in: subject', subject_nr+1, 'session:', session_nr+1, 'where? AFTER SPLIT')
'''
df_finished, samplerate = self.reshape_session_df_to_signal(df)
'''
# TESTING FOR NAN
if df_finished.isnull().values.any():
print('NaN in: subject', subject_nr+1, 'session:', session_nr+1, 'where? AFTER RESHAPE')
'''
subj_samples.append([df_finished, samplerate])
self.samples_per_subject[subject_nr+1] = subj_samples
@ -567,10 +609,10 @@ def make_df_from_xandy(x, y, emg_nr):
# Help: returns the samplerate of a df
def get_samplerate(df:DataFrame):
min, max = get_min_max_timestamp(df)
#print(min, max)
if max > 60:
seconds = max - 60 - min
#print(seconds)
samples = len(df['timestamp'])
#print(samples)
else:
seconds = max - min
samples = len(df.index)
samplerate = samples / seconds
return samplerate

25
Present_data.py
View File

@ -100,13 +100,13 @@ def plot_all_emg_mfcc(data_list:list, label_list:list):
plt.show()
def pretty(dict, indent=0):
def pretty(dict):
for key, value in dict.items():
print('\t' * indent + str(key))
if isinstance(value, dict):
pretty(value, indent+1)
else:
print('\t' * (indent+1) + str(value))
print('Subject', key, 'samples:')
print('\t\t Number av samples:', len(value))
print('\t\t EX sample nr 1:')
print('\t\t\t Type:', type(value[0][0]), type(value[0][1]))
print('\t\t\t Sample:', value[0][0], value[0][1])
# DATA FUNCTIONS: --------------------------------------------------------------:
@ -134,6 +134,13 @@ def mfcc_custom(df:DataFrame, samplesize, windowsize, stepsize, nr_coefficients,
return N, base.mfcc(y, samplesize, windowsize, stepsize, nr_coefficients, nr_mel_filters)
def test_for_NaN(dict, samples_per_person):
for key, value in dict.items():
for i in range(samples_per_person):
df = value[i][0]
#print(df)
print(df.isnull())
# CASE FUNTIONS ----------------------------------------------------------------:
# Takes in a df and compares the FFT and the wavelet denoising of the FFT
@ -225,10 +232,8 @@ def main():
dl_data_handler.store_samples(10)
dict = dl_data_handler.samples_per_subject
test_session_df = dict.get(1)[0]
print(test_session_df)
df, _ = dl_data_handler.reshape_session_df_to_signal(test_session_df)
print(df[:50])

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__pycache__/Handle_emg_data.cpython-38.pyc
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