diff --git a/Test_functions.py b/Test_functions.py index 1668128..91f2411 100644 --- a/Test_functions.py +++ b/Test_functions.py @@ -1,6 +1,6 @@ -from Handle_emg_data import CSV_handler, get_min_max_timestamp +from Handle_emg_data import * import matplotlib.pyplot as plt -import Signal_prep +from Signal_prep import * def test_df_extraction(emg_nr): handler = CSV_handler() @@ -12,7 +12,7 @@ def test_df_extraction(emg_nr): return subject1_left_emg1, emg_nr def test_load_func(): - test_dict = Signal_prep.load_user_emg_data() + test_dict = load_user_emg_data() subject2_container = test_dict[2] print(subject2_container.data_dict['left'][1]) @@ -29,24 +29,23 @@ def test_fft_prep(): file = "/Exp20201205_2myo_hardTypePP/HaluskaMarek_20201207_1810/myoLeftEmg.csv" df = handler.get_time_emg_table(file, 1) - x, y, d = Signal_prep.prep_df_for_trans(df) - print(x) - print(y) def test_plot_wavelet_both_ways(): handler = CSV_handler() file = "/Exp20201205_2myo_hardTypePP/HaluskaMarek_20201207_1810/myoLeftEmg.csv" df = handler.get_time_emg_table(file, 1) - N = handler.get_xory_from_df('x', df) - #plot_df(df) + N = get_xory_from_df('x', df) + plot_df(df) #print(len(N)) #print(len(get_xory_from_df('y', df))) - x, cA, cD = handler.wavelet_db4_denoising(df) - #plot_arrays(x, cA) + x, cA, cD = wavelet_db4_denoising(df) + plot_arrays(x, cA) #print(len(cA)) cA_filt, cD_filt = soft_threshold_filter(cA, cD) - #plot_arrays(x, cA_filt) + plot_arrays(x, cA_filt) #print(len(cA_filt)) - y_new_values = handler.inverse_wavelet(df, cA, cD) + y_new_values = inverse_wavelet(df, cA, cD) #print(len(y_new_values)) - handler.plot_arrays(N, y_new_values) \ No newline at end of file + plot_arrays(N, y_new_values) + +test_plot_wavelet_both_ways() \ No newline at end of file diff --git a/__pycache__/Signal_prep.cpython-38.pyc b/__pycache__/Signal_prep.cpython-38.pyc index fe0eed3..2a578c0 100644 Binary files a/__pycache__/Signal_prep.cpython-38.pyc and b/__pycache__/Signal_prep.cpython-38.pyc differ