81 lines
2.5 KiB
Python
81 lines
2.5 KiB
Python
from Handle_emg_data import *
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from Signal_prep import *
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# PLOT FUNCTIONS:
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# Plots DataFrame objects
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def plot_df(df:DataFrame):
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lines = df.plot.line(x='timestamp')
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plt.show()
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# Plots ndarrays after transformations
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def plot_arrays(N, N_name, y, y_name):
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plt.plot(N, np.abs(y))
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plt.show()
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def plot_compare_two_df(df_old, old_name, df_new, new_name):
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x = get_xory_from_df('x', df_old)
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y1 = get_xory_from_df('y', df_old)
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y2 = get_xory_from_df('y', df_new)
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figure, axis = plt.subplots(1, 2)
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axis[0].plot(x, y1)
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axis[0].set_title(old_name)
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axis[1].plot(x, y2)
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axis[1].set_title(new_name)
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plt.show()
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# DATA FUNCTIONS:
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# The CSV_handler takes in data_type, but only for visuals.
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# E.g. handler = CSV_handler('soft')
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# Loads in data. Choose data_type: hard, hardPP, soft og softPP as str. Returns None
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def load_data(csv_handler:CSV_handler, data_type):
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switcher = {
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'hard': csv_handler.load_hard_original_emg_data(),
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'hardPP':csv_handler.load_hard_PP_emg_data(),
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'soft':csv_handler.load_soft_original_emg_data(),
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'softPP':csv_handler.load_soft_PP_emg_data(),
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}
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return switcher.get(data_type)
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# Retrieved data. Send in loaded csv_handler and data detailes you want. Returns DataFrame
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def get_data(csv_handler:CSV_handler, subject_nr, which_arm, session, emg_nr):
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data_frame = csv_handler.get_df_from_data_dict(subject_nr, which_arm, session, emg_nr)
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return data_frame
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#Takes in handler and detailes to denoise. Returns arrays and df
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def denoice_dataset(handler:Handler.CSV_handler, subject_nr, which_arm, round, emg_nr):
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df = handler.get_df_from_data_dict(subject_nr, which_arm, round, emg_nr)
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N = get_xory_from_df('x', df)
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N_trans, cA, cD = wavelet_db4(df)
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cA_filt, cD_filt = soft_threshold_filter(cA, cD)
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y_values = inverse_wavelet(df, cA_filt, cD_filt)
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df_new = Handler.make_df_from_xandy(N, y_values, emg_nr)
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return df_new
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# MAIN:
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def main():
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csv_handler = CSV_handler('hard')
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load_data(csv_handler, 'hard')
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data_frame = get_data(csv_handler, 1, 'left', 1, 1)
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N_trans, cA, cD = wavelet_db4(data_frame)
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data_frame_freq = make_df_from_xandy(N_trans, cA, 1)
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cA_filt, cD_filt = soft_threshold_filter(cA, cD)
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data_frame_freq_filt = make_df_from_xandy(N_trans, cD_filt, 1)
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plot_compare_two_df(data_frame_freq, 'Original data', data_frame_freq_filt, 'Analyzed data')
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return None
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main() |