fix: make the emg merger func so it makes one df per session
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Skudalen
parent
aa27fb0aa4
commit
3eb838da54
@ -444,10 +444,9 @@ class CSV_handler:
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return self.data_container_dict
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# Retrieves df via the data_dict in the handler object
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def get_df_from_data_dict(self, subject_nr, which_arm, round, emg_nr):
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data_type = self.data_type
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container = self.data_container_dict.get(subject_nr)
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df = container.dict_list[round - 1].get(which_arm)[emg_nr - 1]
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def get_df_from_data_dict(self, subject_nr, which_arm, session, emg_nr):
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container:Data_container = self.data_container_dict.get(subject_nr)
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df = container.dict_list[session - 1].get(which_arm)[emg_nr - 1]
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return df
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# Loads in data to a CSV_handler. Choose data_type: hard, hardPP, soft og softPP as str.
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@ -497,38 +496,39 @@ class DL_data_handler:
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def get_emg_list(self, subject_nr, session_nr) -> list:
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list_of_emgs = []
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for emg_nr in range(8):
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df, _ = self.csv_handler.get_data(self.csv_handler, subject_nr, 'left', session_nr)
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df, _ = self.csv_handler.get_data(subject_nr, 'left', session_nr, emg_nr+1)
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list_of_emgs.append(df)
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for emg_nr in range(8):
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df, _ = self.csv_handler.get_data(self.csv_handler, subject_nr, 'right', session_nr)
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df, _ = self.csv_handler.get_data(subject_nr, 'right', session_nr, emg_nr+1)
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list_of_emgs.append(df)
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return list_of_emgs
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def make_subj_sample(list_of_emgs):
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def make_subj_sample(self, list_of_emgs):
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starting_point:DataFrame = list_of_emgs[0].rename(columns={'emg1':'emg'})
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print(starting_point)
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tot_session_df:DataFrame = None
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left_nr_remaining = len(list_of_emgs) - 1
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for i in range(left_nr_remaining):
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i += 1
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tot_session_df_list = []
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for i in range(2, 9):
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emg_str = get_emg_str(i)
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list_of_emgs[i].rename(columns={emg_str: 'emg'}, inplace=True)
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starting_point.append(list_of_emgs[i])
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df = list_of_emgs[i-1].rename(columns={emg_str: 'emg'})
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tot_session_df_list.append(df)
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for i in range(1, 9):
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emg_str = get_emg_str(i)
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df = list_of_emgs[7+i].rename(columns={emg_str: 'emg'})
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tot_session_df_list.append(df)
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tot_session_df = starting_point.append(tot_session_df_list, ignore_index=True, sort=True)
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return tot_session_df
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def store_samples(self, split_nr) -> None:
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for subject_nr in range(5):
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subj_samples = []
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#session_df_list = []
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for session_nr in range(4):
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list_of_emg = self.get_emg_list(self.csv_handler, subject_nr, session_nr)
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tot_session_df = self.make_subj_sample(list_of_emg)
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#session_df_list.append(tot_session_df)
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list_of_emg = self.get_emg_list(subject_nr+1, session_nr+1)
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tot_session_df, samplerate = self.make_subj_sample(list_of_emg)
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samples = np.array_split(tot_session_df, split_nr)
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for array in samples:
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subj_samples.append(DataFrame(array))
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df = DataFrame(array)
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samplerate = get_samplerate(df)
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subj_samples.append([df, samplerate])
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self.samples_per_subject[subject_nr] = subj_samples
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@ -143,9 +143,9 @@ def compare_with_wavelet_filter(data_frame):
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# Input: CSV_handler
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# Output: None --> Plot
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def mfcc_3_plots_1_1_2(csv_handler:CSV_handler):
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df1, samplerate1 = get_data(csv_handler, 1, 'left', 1, 1)
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df2, samplerate2 = get_data(csv_handler, 1, 'left', 2, 1)
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df3, samplerate3 = get_data(csv_handler, 2, 'left', 1, 1)
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df1, samplerate1 = csv_handler.get_data( 1, 'left', 1, 1)
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df2, samplerate2 = csv_handler.get_data( 1, 'left', 2, 1)
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df3, samplerate3 = csv_handler.get_data( 2, 'left', 1, 1)
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#print(df1.head, samplerate1)
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#print(df2.head, samplerate2)
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#print(df3.head, samplerate3)
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@ -162,9 +162,9 @@ def mfcc_3_plots_1_1_2(csv_handler:CSV_handler):
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# Input: CSV_handler
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# Output: None --> Plot
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def mfcc_3_plots_3_3_4(csv_handler:CSV_handler):
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df1, samplerate1 = get_data(csv_handler, 3, 'left', 1, 1)
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df2, samplerate2 = get_data(csv_handler, 3, 'left', 2, 1)
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df3, samplerate3 = get_data(csv_handler, 4, 'left', 1, 1)
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df1, samplerate1 = csv_handler.get_data(3, 'left', 1, 1)
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df2, samplerate2 = csv_handler.get_data(3, 'left', 2, 1)
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df3, samplerate3 = csv_handler.get_data(4, 'left', 1, 1)
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#print(df1.head, samplerate1)
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#print(df2.head, samplerate2)
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#print(df3.head, samplerate3)
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@ -178,14 +178,14 @@ def mfcc_3_plots_3_3_4(csv_handler:CSV_handler):
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plot_3_mfcc(mfcc_feat1, label_1, mfcc_feat2, label_2, mfcc_feat3, label_3)
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def mfcc_all_emg_plots(csv_handler:CSV_handler):
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df1, samplerate1 = get_data(csv_handler, 1, 'left', 1, 1)
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df2, samplerate2 = get_data(csv_handler, 1, 'left', 1, 2)
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df3, samplerate3 = get_data(csv_handler, 1, 'left', 1, 3)
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df4, samplerate4 = get_data(csv_handler, 1, 'left', 1, 4)
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df5, samplerate5 = get_data(csv_handler, 1, 'left', 1, 5)
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df6, samplerate6 = get_data(csv_handler, 1, 'left', 1, 6)
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df7, samplerate7 = get_data(csv_handler, 1, 'left', 1, 7)
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df8, samplerate8 = get_data(csv_handler, 1, 'left', 1, 8)
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df1, samplerate1 = csv_handler.get_data( 1, 'left', 1, 1)
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df2, samplerate2 = csv_handler.get_data( 1, 'left', 1, 2)
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df3, samplerate3 = csv_handler.get_data( 1, 'left', 1, 3)
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df4, samplerate4 = csv_handler.get_data( 1, 'left', 1, 4)
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df5, samplerate5 = csv_handler.get_data( 1, 'left', 1, 5)
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df6, samplerate6 = csv_handler.get_data( 1, 'left', 1, 6)
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df7, samplerate7 = csv_handler.get_data( 1, 'left', 1, 7)
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df8, samplerate8 = csv_handler.get_data( 1, 'left', 1, 8)
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N1, mfcc_feat1 = mfcc_custom(df1, samplerate1, mfcc_windowsize, mfcc_stepsize)
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N2, mfcc_feat2 = mfcc_custom(df2, samplerate2, mfcc_windowsize, mfcc_stepsize)
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N3, mfcc_feat3 = mfcc_custom(df3, samplerate3, mfcc_windowsize, mfcc_stepsize)
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@ -212,10 +212,14 @@ def mfcc_all_emg_plots(csv_handler:CSV_handler):
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def main():
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csv_handler = CSV_handler()
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load_data(csv_handler, 'soft')
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csv_handler.load_data('soft')
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#print(csv_handler.get_data(1, 'left', 1, 1))
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dl_data_handler = DL_data_handler(csv_handler)
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dl_data_handler.store_samples(10)
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print(dl_data_handler.samples_per_subject)
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#dl_data_handler.store_samples(10)
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#print(dl_data_handler.samples_per_subject)
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emg_list = dl_data_handler.get_emg_list(1, 1)
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df = dl_data_handler.make_subj_sample(emg_list)
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print(df.head)
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main()
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