Fixed RAPIDS bug: error when IBI.csv is empty.
parent
fbf6a77dfc
commit
d300f0f8f0
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@ -114,7 +114,7 @@ sn_profile_*/
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settings.dcf
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settings.dcf
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tests/fakedata_generation/
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tests/fakedata_generation/
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site/
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site/
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credentials.yaml
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!credentials.yaml
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# Docker container and other files
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# Docker container and other files
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.devcontainer
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.devcontainer
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@ -3,7 +3,7 @@
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########################################################################################################################
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########################################################################################################################
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# See https://www.rapids.science/latest/setup/configuration/#participant-files
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# See https://www.rapids.science/latest/setup/configuration/#participant-files
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PIDS: [p02, p03] #p01, p02, p03]
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PIDS: [p03] #p01, p02, p03]
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# See https://www.rapids.science/latest/setup/configuration/#automatic-creation-of-participant-files
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# See https://www.rapids.science/latest/setup/configuration/#automatic-creation-of-participant-files
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CREATE_PARTICIPANT_FILES:
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CREATE_PARTICIPANT_FILES:
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@ -0,0 +1,7 @@
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PSQL_STRAW:
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database: staw
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user: staw_db
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password: kizi-x2yf-mate
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host: 212.235.208.113
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port: 5432
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@ -111,7 +111,7 @@ dependencies:
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- biosppy==0.8.0
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- biosppy==0.8.0
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- cached-property==1.5.2
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- cached-property==1.5.2
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- configargparse==0.15.1
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- configargparse==0.15.1
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- cr-features==0.1.11
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- cr-features==0.1.13
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- cycler==0.11.0
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- cycler==0.11.0
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- decorator==4.4.2
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- decorator==4.4.2
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- fonttools==4.33.2
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- fonttools==4.33.2
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@ -68,8 +68,11 @@ def extract_empatica_data(data, sensor):
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elif sensor == 'EMPATICA_INTER_BEAT_INTERVAL':
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elif sensor == 'EMPATICA_INTER_BEAT_INTERVAL':
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df = pd.read_csv(sensor_data_file, names=['timestamp', column], header=None)
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df = pd.read_csv(sensor_data_file, names=['timings', column], header=None)
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df['timings'] = df['timestamp']
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df['timestamp'] = df['timings']
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if df.empty:
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df = df.set_index('timestamp')
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return df
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timestampstart = float(df['timestamp'][0])
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timestampstart = float(df['timestamp'][0])
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df['timestamp'] = (df['timestamp'][1:len(df)]).astype(float) + timestampstart
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df['timestamp'] = (df['timestamp'][1:len(df)]).astype(float) + timestampstart
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df = df.drop([0])
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df = df.drop([0])
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@ -126,7 +129,19 @@ def patch_ibi_with_bvp(ibi_data, bvp_data):
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ibi_data_file = BytesIO(ibi_data).getvalue().decode('utf-8')
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ibi_data_file = BytesIO(ibi_data).getvalue().decode('utf-8')
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ibi_data_file = StringIO(ibi_data_file)
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ibi_data_file = StringIO(ibi_data_file)
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ibi_data, ibi_start_timestamp = empatica2d_to_array(ibi_data_file)
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# Begin with the cr-features part
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try:
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ibi_data, ibi_start_timestamp = empatica2d_to_array(ibi_data_file)
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except IndexError:
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# Checks whether IBI.csv is empty
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df_test = pd.read_csv(ibi_data_file, names=['timings', 'inter_beat_interval'], header=None)
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print(df_test)
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if df_test.empty:
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df_test['timestamp'] = df_test['timings']
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df_test = df_test.set_index('timestamp')
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return df_test
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bvp_data_file = BytesIO(bvp_data).getvalue().decode('utf-8')
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bvp_data_file = BytesIO(bvp_data).getvalue().decode('utf-8')
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bvp_data_file = StringIO(bvp_data_file)
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bvp_data_file = StringIO(bvp_data_file)
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@ -139,7 +154,7 @@ def patch_ibi_with_bvp(ibi_data, bvp_data):
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winsorize_value=25, hampel_fiter=False, median_filter=False,
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winsorize_value=25, hampel_fiter=False, median_filter=False,
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mod_z_score_filter=True, sampling=64, feature_names=['meanHr'])
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mod_z_score_filter=True, sampling=64, feature_names=['meanHr'])
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ibi_timings, ibi_rr = get_patched_ibi_with_bvp(ibi_data[0], ibi_data[1], bvp_timings, bvp_rr, min_length=10)
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ibi_timings, ibi_rr = get_patched_ibi_with_bvp(ibi_data[0], ibi_data[1], bvp_timings, bvp_rr, min_length=None)
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df = \
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df = \
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pd.DataFrame(np.array([ibi_timings, ibi_rr]).transpose(), columns=['timestamp', 'inter_beat_interval'])
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pd.DataFrame(np.array([ibi_timings, ibi_rr]).transpose(), columns=['timestamp', 'inter_beat_interval'])
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