Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

[MAINT] lint and clean up #79

Merged
merged 1 commit into from
Jun 26, 2024
Merged

[MAINT] lint and clean up #79

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
64 changes: 42 additions & 22 deletions eye2bids/edf2bids.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -6,11 +6,11 @@
import json
import subprocess
from pathlib import Path
from typing import Any

import numpy as np
import pandas as pd
import yaml
from rich import print
from rich.prompt import Prompt
from yaml.loader import SafeLoader

Expand Down Expand Up @@ -135,29 +135,30 @@ def _extract_CalibrationType(df: pd.DataFrame) -> list[int]:


def _extract_CalibrationCount(df: pd.DataFrame) -> int:
if _2eyesmode(df) == True:
if _2eyesmode(df):
return len(_calibrations(df)) // 2
return len(_calibrations(df))


def _extract_CalibrationPosition(df: pd.DataFrame) -> list[list[int] | list[list[int]]]:
def _extract_CalibrationPosition(
df: pd.DataFrame,
) -> list[Any] | list[list[int] | list[list[int]]]:

if _has_validation(df) == False:
CalibrationPosition = []
return CalibrationPosition
if not _has_validation(df):
return []

calibration_df = df[df[2] == "VALIDATE"]
calibration_df[5] = pd.to_numeric(calibration_df[5], errors="coerce")

if _2eyesmode(df) == True:
if _2eyesmode(df):
# drop duplicated calibration position
# because they will be the same for both eyes
calibration_df = calibration_df[calibration_df[6] == "LEFT"]

nb_calibration_postions = calibration_df[5].max() + 1

# initiliaze
CalibrationPosition = [[[]] * nb_calibration_postions]
# initialize
CalibrationPosition: Any = [[[]] * nb_calibration_postions]

for i_pos in range(nb_calibration_postions):

Expand All @@ -167,7 +168,7 @@ def _extract_CalibrationPosition(df: pd.DataFrame) -> list[list[int] | list[list
values = calibration[1][8].split(",")

if len(CalibrationPosition) < i + 1:
CalibrationPosition.append([()] * nb_calibration_postions)
CalibrationPosition.append([[]] * nb_calibration_postions)

CalibrationPosition[i][i_pos] = [int(x) for x in values]

Expand Down Expand Up @@ -248,7 +249,7 @@ def _extract_SamplingFrequency(df: pd.DataFrame) -> int:
return int(df[df[2] == "RECCFG"].iloc[0:1, 2:3].to_string(header=False, index=False))


def _extract_RecordedEye(df: pd.DataFrame) -> str:
def _extract_RecordedEye(df: pd.DataFrame) -> str | list[str]:
eye = df[df[2] == "RECCFG"].iloc[0:1, 5:6].to_string(header=False, index=False)
if eye == "L":
return "Left"
Expand Down Expand Up @@ -368,18 +369,34 @@ def edf2bids(
base_json = {
"Columns": ["x_coordinate", "y_coordinate", "pupil_size", "timestamp"],
"timestamp": {
"Description": "Timestamp issued by the eye-tracker indexing the continuous recordings corresponding to the sampled eye."
"Description": (
"Timestamp issued by the eye-tracker "
"indexing the continuous recordings "
"corresponding to the sampled eye."
)
},
"x_coordinate": {
"Description": "Gaze position x-coordinate of the recorded eye, in the coordinate units specified in the corresponding metadata sidecar.",
"Description": (
"Gaze position x-coordinate of the recorded eye, "
"in the coordinate units specified "
"in the corresponding metadata sidecar."
),
"Units": "a.u.",
},
"y_coordinate": {
"Description": "Gaze position y-coordinate of the recorded eye, in the coordinate units specified in the corresponding metadata sidecar.",
"Description": (
"Gaze position y-coordinate of the recorded eye, "
"in the coordinate units specified "
"in the corresponding metadata sidecar."
),
"Units": "a.u.",
},
"pupil_size": {
"Description": "Pupil area of the recorded eye as calculated by the eye-tracker in arbitrary units (see EyeLink's documentation for conversion).",
"Description": (
"Pupil area of the recorded eye as calculated "
"by the eye-tracker in arbitrary units "
"(see EyeLink's documentation for conversion)."
),
"Units": "a.u.",
},
"Manufacturer": "SR-Research",
Expand All @@ -406,7 +423,7 @@ def edf2bids(
"CalibrationPosition": _extract_CalibrationPosition(df_ms_reduced),
}

if _2eyesmode(df_ms_reduced) == True:
if _2eyesmode(df_ms_reduced):
metadata_eye1 = {
"AverageCalibrationError": (_extract_AverageCalibrationError(df_ms)[0::2]),
"MaximalCalibrationError": (_extract_MaximalCalibrationError(df_ms)[0::2]),
Expand All @@ -426,7 +443,7 @@ def edf2bids(
}

json_eye1 = dict(base_json, **metadata_eye1)
if _2eyesmode(df_ms_reduced) == True:
if _2eyesmode(df_ms_reduced):
json_eye2 = dict(base_json, **metadata_eye2)

# to json
Expand All @@ -442,7 +459,7 @@ def edf2bids(

e2b_log.info(f"file generated: {output_filename_eye1}")

if _2eyesmode(df_ms_reduced) == True:
if _2eyesmode(df_ms_reduced):
output_filename_eye2 = generate_output_filename(
output_dir=output_dir,
input_file=input_file,
Expand All @@ -463,7 +480,10 @@ def edf2bids(
"blink": {"Description": "One indicates if the eye was closed, zero if open."},
"message": {"Description": "String messages logged by the eye-tracker."},
"trial_type": {
"Description": "Event type as identified by the eye-tracker's model (either 'n/a' if not applicabble, 'fixation', or 'saccade')."
"Description": (
"Event type as identified by the eye-tracker's model "
"((either 'n/a' if not applicabble, 'fixation', or 'saccade')."
)
},
"TaskName": _extract_TaskName(events),
"InstitutionAddress": metadata.get("InstitutionAddress"),
Expand All @@ -487,7 +507,7 @@ def edf2bids(

e2b_log.info(f"file generated: {output_filename_eye1}")

if _2eyesmode(df_ms_reduced) == True:
if _2eyesmode(df_ms_reduced):

output_filename_eye2 = generate_output_filename(
output_dir=output_dir,
Expand Down Expand Up @@ -516,7 +536,7 @@ def edf2bids(
.replace(".", np.nan, regex=False)
)

if _2eyesmode(df_ms_reduced) == True:
if _2eyesmode(df_ms_reduced):
samples_eye2 = pd.DataFrame(samples.iloc[:, [0, 4, 5, 6]])

# Samples to eye_physio.tsv.gz
Expand All @@ -533,7 +553,7 @@ def edf2bids(

e2b_log.info(f"file generated: {output_filename_eye1}")

if _2eyesmode(df_ms_reduced) == True:
if _2eyesmode(df_ms_reduced):

output_filename_eye2 = generate_output_filename(
output_dir=output_dir,
Expand Down
3 changes: 2 additions & 1 deletion tests/test_edf2bids.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -147,7 +147,8 @@ def test_2files_eye2(eyelink_test_data_dir):

@pytest.mark.skipif(not _check_edf2asc_present(), reason="edf2asc missing")
def test_number_columns_2eyes_tsv(eyelink_test_data_dir):
"""Check that values for only one eye were extracted in eye1-physio.tsv.gz by number of columns.
"""Check that values for only one eye were extracted \
in eye1-physio.tsv.gz by number of columns.

function _samples_to_data_frame
"""
Expand Down