Skip to content

Commit

Permalink
update docstring of judo1000 dataset definition (#830)
Browse files Browse the repository at this point in the history
  • Loading branch information
SiQube committed Sep 27, 2024
1 parent bd31736 commit f14bfbc
Showing 1 changed file with 32 additions and 2 deletions.
34 changes: 32 additions & 2 deletions src/pymovements/datasets/judo1000.py
Original file line number Diff line number Diff line change
Expand Up @@ -49,15 +49,23 @@ class JuDo1000(DatasetDefinition):
name: str
The name of the dataset.
has_files: dict[str, bool]
Indicate whether the dataset contains 'gaze', 'precomputed_events', and
'precomputed_reading_measures'.
mirrors: dict[str, tuple[str, ...]]
A tuple of mirrors of the dataset. Each entry must be of type `str` and end with a '/'.
resources: dict[str, tuple[dict[str, str], ...]]
A tuple of dataset resources. Each list entry must be a dictionary with the following keys:
A tuple of dataset gaze_resources. Each list entry must be a dictionary with the following
keys:
- `resource`: The url suffix of the resource. This will be concatenated with the mirror.
- `filename`: The filename under which the file is saved as.
- `md5`: The MD5 checksum of the respective file.
extract: dict[str, bool]
Decide whether to extract the data.
experiment: Experiment
The experiment definition.
Expand All @@ -69,12 +77,34 @@ class JuDo1000(DatasetDefinition):
If named groups are present in the `filename_format`, this makes it possible to cast
specific named groups to a particular datatype.
trial_columns: list[str]
The name of the trial columns in the input data frame. If the list is empty or None,
the input data frame is assumed to contain only one trial. If the list is not empty,
the input data frame is assumed to contain multiple trials and the transformation
methods will be applied to each trial separately.
time_column: str
The name of the timestamp column in the input data frame. This column will be renamed to
``time``.
time_unit: str
The unit of the timestamps in the timestamp column in the input data frame. Supported
units are 's' for seconds, 'ms' for milliseconds and 'step' for steps. If the unit is
'step' the experiment definition must be specified. All timestamps will be converted to
milliseconds.
pixel_columns: list[str]
The name of the pixel position columns in the input data frame. These columns will be
nested into the column ``pixel``. If the list is empty or None, the nested ``pixel``
column will not be created.
column_map: dict[str, str]
The keys are the columns to read, the values are the names to which they should be renamed.
custom_read_kwargs: dict[str, dict[str, Any]]
If specified, these keyword arguments will be passed to the file reading function.
Examples
--------
Initialize your :py:class:`~pymovements.PublicDataset` object with the
Expand Down Expand Up @@ -172,7 +202,7 @@ class JuDo1000(DatasetDefinition):
},
)

custom_read_kwargs: dict[str, Any] = field(
custom_read_kwargs: dict[str, dict[str, Any]] = field(
default_factory=lambda: {
'gaze': {
'dtypes': {
Expand Down

0 comments on commit f14bfbc

Please sign in to comment.