Downloading Public Datasets#

What you will learn in this tutorial:#

  • how to get an overview of the available public datasets

  • how to download and extract one of the available public datasets

  • how to customize the default directory structure

Preparations#

We import pymovements as the alias pm for convenience.

import pymovements as pm

pymovements provides a library of publicly available datasets.

You can browse through the available dataset definitions here: Dataset

To get the names of all currently available datasets, you can use the DatasetLibrary.names() method:

pm.DatasetLibrary.names()

['BSC',
 'BSCII',
 'ChineseReading',
 'CoLAGaze',
 'CodeComprehension',
 'CopCo',
 'DAEMONS',
 'DIDEC',
 'EMTeC',
 'ETDD70',
 'FakeNewsPerception',
 'GGTG',
 'Gaze4Hate',
 'GazeBase',
 'GazeBaseVR',
 'GazeGraph',
 'GazeOnFaces',
 'HBN',
 'IITB_HGC',
 'InteRead',
 'JuDo1000',
 'MECOL1W1',
 'MECOL1W2',
 'MECOL2W1',
 'MECOL2W2',
 'MouseCursor',
 'OneStop',
 'PoTeC',
 'PotsdamBingeRemotePVT',
 'PotsdamBingeWearablePVT',
 'Provo',
 'RaCCooNS',
 'SBSAT',
 'TECO',
 'ToyDataset',
 'ToyDatasetEyeLink',
 'UCL']

For this tutorial we will limit ourselves to the ToyDataset due to its minimal space requirements.

Other datasets can be downloaded by simply replacing ToyDataset with one of the other available datasets.

If you want to get more information about a specific dataset without downloading it yet, you can use the DatasetLibrary.get() method:

pm.DatasetLibrary.get('ToyDataset')
DatasetDefinition
  • acceleration_columns:
    None
  • column_map:
    None
  • custom_read_kwargs:
    None
  • distance_column:
    None
  • Experiment
    Experiment
    • EyeTracker
      EyeTracker
      • left:
        None
      • model:
        None
      • mount:
        None
      • right:
        None
      • sampling_rate:
        1000
      • vendor:
        None
      • version:
        None
    • sampling_rate:
      1000
    • Screen
      Screen
      • distance_cm:
        68
      • height_cm:
        30.2
      • height_px:
        1024
      • origin:
        'upper left'
      • width_cm:
        38
      • width_px:
        1280
      • x_max_dva:
        15.599386487782953
      • x_min_dva:
        -15.599386487782953
      • y_max_dva:
        12.508044410882546
      • y_min_dva:
        -12.508044410882546
  • extract:
    None
  • dict (1 items)
    • gaze:
      'trial_{text_id:d}_{page_id:d}.csv'
  • dict (1 items)
    • dict (2 items)
      • text_id:
        <class 'int'>
      • page_id:
        <class 'int'>
  • has_resources:
    True
  • long_name:
    'pymovements Toy Dataset'
  • mirrors:
    dict (0 items)
  • name:
    'ToyDataset'
  • pixel_columns:
    None
  • position_columns:
    None
  • list (1 items)
    • ResourceDefinition
      • content:
        'gaze'
      • filename:
        'pymovements-toy-dataset.zip'
      • filename_pattern:
        'trial_{text_id:d}_{page_id:d}.csv'
      • dict (2 items)
        • text_id:
          <class 'int'>
        • page_id:
          <class 'int'>
      • load_function:
        None
      • dict (4 items)
        • time_column:
          'timestamp'
        • time_unit:
          'ms'
        • (2 more)
      • md5:
        '256901852c1c07581d375eef705855d6'
      • mirrors:
        None
      • 'https://github.com/pymovements/pymovements-toy-dat...'
        'https://github.com/pymovements/pymovements-toy-dataset/archive/refs/heads/main.zip'
  • time_column:
    None
  • time_unit:
    None
  • trial_columns:
    None
  • velocity_columns:
    None

First, we initialize our public dataset by specifying its name and the root data directory.

Our dataset will then be placed in a directory with the name of the dataset:

dataset = pm.Dataset('ToyDataset', path='data/ToyDataset')

dataset.path

PosixPath('data/ToyDataset')

If you only want to specify a root directory which contains all your datasets, you can pass a DatasetPaths instance.

The directory of your dataset will have the same name as in the dataset definition.

dataset_paths = pm.DatasetPaths(root='data/')
dataset = pm.Dataset('ToyDataset', path=dataset_paths)

dataset.path

PosixPath('data/ToyDataset')

Can also specify an alternative dataset directory for your downloaded dataset.

dataset_paths_alt = pm.DatasetPaths(root='data/', dataset='my_dataset')
dataset_alt = pm.Dataset('ToyDataset', path=dataset_paths_alt)

dataset_alt.path

PosixPath('data/my_dataset')

Downloading#

The dataset will then be downloaded by calling:

dataset.download()

INFO:pymovements.dataset.dataset:
        You are downloading the pymovements Toy Dataset. Please be aware that pymovements does not
        host or distribute any dataset resources and only provides a convenient interface to
        download the public dataset resources that were published by their respective authors.

        Please cite the referenced publication if you intend to use the dataset in your research.
        

Using already downloaded and verified file: data/ToyDataset/downloads/pymovements-toy-dataset.zip
Extracting pymovements-toy-dataset.zip to data/ToyDataset/raw

Extracting archive:   0%|          | 0/23 [00:00<?, ?file/s]

Extracting archive: 100%|██████████| 23/23 [00:00<00:00, 349.78file/s]
Dataset
  • DatasetDefinition
    DatasetDefinition
    • acceleration_columns:
      None
    • column_map:
      None
    • custom_read_kwargs:
      None
    • distance_column:
      None
    • Experiment
      Experiment
      • EyeTracker
        EyeTracker
        • left:
          None
        • model:
          None
        • mount:
          None
        • right:
          None
        • sampling_rate:
          1000
        • vendor:
          None
        • version:
          None
      • sampling_rate:
        1000
      • Screen
        Screen
        • distance_cm:
          68
        • height_cm:
          30.2
        • height_px:
          1024
        • origin:
          'upper left'
        • width_cm:
          38
        • width_px:
          1280
        • x_max_dva:
          15.599386487782953
        • x_min_dva:
          -15.599386487782953
        • y_max_dva:
          12.508044410882546
        • y_min_dva:
          -12.508044410882546
    • extract:
      None
    • dict (1 items)
      • gaze:
        'trial_{text_id:d}_{page_id:d}.csv'
    • dict (1 items)
      • dict (2 items)
        • text_id:
          <class 'int'>
        • page_id:
          <class 'int'>
    • has_resources:
      True
    • long_name:
      'pymovements Toy Dataset'
    • mirrors:
      dict (0 items)
    • name:
      'ToyDataset'
    • pixel_columns:
      None
    • position_columns:
      None
    • list (1 items)
      • ResourceDefinition
        • content:
          'gaze'
        • filename:
          'pymovements-toy-dataset.zip'
        • filename_pattern:
          'trial_{text_id:d}_{page_id:d}.csv'
        • dict (2 items)
          • text_id:
            <class 'int'>
          • page_id:
            <class 'int'>
        • load_function:
          None
        • dict (4 items)
          • time_column:
            'timestamp'
          • time_unit:
            'ms'
          • (2 more)
        • md5:
          '256901852c1c07581d375eef705855d6'
        • mirrors:
          None
        • 'https://github.com/pymovements/pymovements-toy-dat...'
          'https://github.com/pymovements/pymovements-toy-dataset/archive/refs/heads/main.zip'
    • time_column:
      None
    • time_unit:
      None
    • trial_columns:
      None
    • velocity_columns:
      None
  • events:
    tuple (0 items)
  • DataFrame (0 columns, 0 rows)
    shape: (0, 0)
  • gaze:
    list (0 items)
  • path:
    PosixPath('data/ToyDataset')
  • DatasetPaths
    DatasetPaths
    • dataset:
      PosixPath('data/ToyDataset')
    • downloads:
      PosixPath('data/ToyDataset/downloads')
    • events:
      PosixPath('data/ToyDataset/events')
    • precomputed_events:
      PosixPath('data/ToyDataset/precomputed_events')
    • precomputed_reading_measures:
      PosixPath('data/ToyDataset/precomputed_reading_measures')
    • preprocessed:
      PosixPath('data/ToyDataset/preprocessed')
    • raw:
      PosixPath('data/ToyDataset/raw')
    • root:
      PosixPath('data')
    • stimuli:
      PosixPath('data/ToyDataset/stimuli')
  • precomputed_events:
    list (0 items)
  • precomputed_reading_measures:
    list (0 items)
  • stimuli:
    list (0 items)

As we see from the download message, the dataset resource has been downloaded to a downloads’ directory.

You can get the path to the downloads directory from the downloads attribute:

dataset.paths.downloads

PosixPath('data/ToyDataset/downloads')

You can also specify a custom directory name during initialization:

dataset_paths_3 = pm.DatasetPaths(root='data/', downloads='new_downloads')
dataset_3 = pm.Dataset('ToyDataset', path=dataset_paths_3)

dataset_3.paths.downloads

PosixPath('data/ToyDataset/new_downloads')

By default, all archives are recursively extracted to Dataset.paths.raw:

dataset.paths.raw

PosixPath('data/ToyDataset/raw')

If you want to remove the downloaded archives after extraction to save some space, you can set remove_finished to True:

dataset.extract(remove_finished=True)

Extracting pymovements-toy-dataset.zip to data/ToyDataset/raw

Extracting archive:   0%|          | 0/23 [00:00<?, ?file/s]

Extracting archive: 100%|██████████| 23/23 [00:00<00:00, 348.00file/s]
Dataset
  • DatasetDefinition
    DatasetDefinition
    • acceleration_columns:
      None
    • column_map:
      None
    • custom_read_kwargs:
      None
    • distance_column:
      None
    • Experiment
      Experiment
      • EyeTracker
        EyeTracker
        • left:
          None
        • model:
          None
        • mount:
          None
        • right:
          None
        • sampling_rate:
          1000
        • vendor:
          None
        • version:
          None
      • sampling_rate:
        1000
      • Screen
        Screen
        • distance_cm:
          68
        • height_cm:
          30.2
        • height_px:
          1024
        • origin:
          'upper left'
        • width_cm:
          38
        • width_px:
          1280
        • x_max_dva:
          15.599386487782953
        • x_min_dva:
          -15.599386487782953
        • y_max_dva:
          12.508044410882546
        • y_min_dva:
          -12.508044410882546
    • extract:
      None
    • dict (1 items)
      • gaze:
        'trial_{text_id:d}_{page_id:d}.csv'
    • dict (1 items)
      • dict (2 items)
        • text_id:
          <class 'int'>
        • page_id:
          <class 'int'>
    • has_resources:
      True
    • long_name:
      'pymovements Toy Dataset'
    • mirrors:
      dict (0 items)
    • name:
      'ToyDataset'
    • pixel_columns:
      None
    • position_columns:
      None
    • list (1 items)
      • ResourceDefinition
        • content:
          'gaze'
        • filename:
          'pymovements-toy-dataset.zip'
        • filename_pattern:
          'trial_{text_id:d}_{page_id:d}.csv'
        • dict (2 items)
          • text_id:
            <class 'int'>
          • page_id:
            <class 'int'>
        • load_function:
          None
        • dict (4 items)
          • time_column:
            'timestamp'
          • time_unit:
            'ms'
          • (2 more)
        • md5:
          '256901852c1c07581d375eef705855d6'
        • mirrors:
          None
        • 'https://github.com/pymovements/pymovements-toy-dat...'
          'https://github.com/pymovements/pymovements-toy-dataset/archive/refs/heads/main.zip'
    • time_column:
      None
    • time_unit:
      None
    • trial_columns:
      None
    • velocity_columns:
      None
  • events:
    tuple (0 items)
  • DataFrame (0 columns, 0 rows)
    shape: (0, 0)
  • gaze:
    list (0 items)
  • path:
    PosixPath('data/ToyDataset')
  • DatasetPaths
    DatasetPaths
    • dataset:
      PosixPath('data/ToyDataset')
    • downloads:
      PosixPath('data/ToyDataset/downloads')
    • events:
      PosixPath('data/ToyDataset/events')
    • precomputed_events:
      PosixPath('data/ToyDataset/precomputed_events')
    • precomputed_reading_measures:
      PosixPath('data/ToyDataset/precomputed_reading_measures')
    • preprocessed:
      PosixPath('data/ToyDataset/preprocessed')
    • raw:
      PosixPath('data/ToyDataset/raw')
    • root:
      PosixPath('data')
    • stimuli:
      PosixPath('data/ToyDataset/stimuli')
  • precomputed_events:
    list (0 items)
  • precomputed_reading_measures:
    list (0 items)
  • stimuli:
    list (0 items)

This is also available for the PublicDataset.download() method:

dataset.download(remove_finished=True)

INFO:pymovements.dataset.dataset:
        You are downloading the pymovements Toy Dataset. Please be aware that pymovements does not
        host or distribute any dataset resources and only provides a convenient interface to
        download the public dataset resources that were published by their respective authors.

        Please cite the referenced publication if you intend to use the dataset in your research.
        

Downloading https://github.com/pymovements/pymovements-toy-dataset/archive/refs/heads/main.zip to data/ToyDataset/downloads/pymovements-toy-dataset.zip

Checking integrity of pymovements-toy-dataset.zip
Extracting pymovements-toy-dataset.zip to data/ToyDataset/raw

Extracting archive:   0%|          | 0/23 [00:00<?, ?file/s]

Extracting archive: 100%|██████████| 23/23 [00:00<00:00, 347.38file/s]
Dataset
  • DatasetDefinition
    DatasetDefinition
    • acceleration_columns:
      None
    • column_map:
      None
    • custom_read_kwargs:
      None
    • distance_column:
      None
    • Experiment
      Experiment
      • EyeTracker
        EyeTracker
        • left:
          None
        • model:
          None
        • mount:
          None
        • right:
          None
        • sampling_rate:
          1000
        • vendor:
          None
        • version:
          None
      • sampling_rate:
        1000
      • Screen
        Screen
        • distance_cm:
          68
        • height_cm:
          30.2
        • height_px:
          1024
        • origin:
          'upper left'
        • width_cm:
          38
        • width_px:
          1280
        • x_max_dva:
          15.599386487782953
        • x_min_dva:
          -15.599386487782953
        • y_max_dva:
          12.508044410882546
        • y_min_dva:
          -12.508044410882546
    • extract:
      None
    • dict (1 items)
      • gaze:
        'trial_{text_id:d}_{page_id:d}.csv'
    • dict (1 items)
      • dict (2 items)
        • text_id:
          <class 'int'>
        • page_id:
          <class 'int'>
    • has_resources:
      True
    • long_name:
      'pymovements Toy Dataset'
    • mirrors:
      dict (0 items)
    • name:
      'ToyDataset'
    • pixel_columns:
      None
    • position_columns:
      None
    • list (1 items)
      • ResourceDefinition
        • content:
          'gaze'
        • filename:
          'pymovements-toy-dataset.zip'
        • filename_pattern:
          'trial_{text_id:d}_{page_id:d}.csv'
        • dict (2 items)
          • text_id:
            <class 'int'>
          • page_id:
            <class 'int'>
        • load_function:
          None
        • dict (4 items)
          • time_column:
            'timestamp'
          • time_unit:
            'ms'
          • (2 more)
        • md5:
          '256901852c1c07581d375eef705855d6'
        • mirrors:
          None
        • 'https://github.com/pymovements/pymovements-toy-dat...'
          'https://github.com/pymovements/pymovements-toy-dataset/archive/refs/heads/main.zip'
    • time_column:
      None
    • time_unit:
      None
    • trial_columns:
      None
    • velocity_columns:
      None
  • events:
    tuple (0 items)
  • DataFrame (0 columns, 0 rows)
    shape: (0, 0)
  • gaze:
    list (0 items)
  • path:
    PosixPath('data/ToyDataset')
  • DatasetPaths
    DatasetPaths
    • dataset:
      PosixPath('data/ToyDataset')
    • downloads:
      PosixPath('data/ToyDataset/downloads')
    • events:
      PosixPath('data/ToyDataset/events')
    • precomputed_events:
      PosixPath('data/ToyDataset/precomputed_events')
    • precomputed_reading_measures:
      PosixPath('data/ToyDataset/precomputed_reading_measures')
    • preprocessed:
      PosixPath('data/ToyDataset/preprocessed')
    • raw:
      PosixPath('data/ToyDataset/raw')
    • root:
      PosixPath('data')
    • stimuli:
      PosixPath('data/ToyDataset/stimuli')
  • precomputed_events:
    list (0 items)
  • precomputed_reading_measures:
    list (0 items)
  • stimuli:
    list (0 items)

Inspecting the dataset#

The Dataset class provides a method to scan the dataset files and create a fileinfo table. This is useful to get an overview of the dataset structure and for example, to check if all files have been downloaded correctly and how to specify a subset of files for further processing.

dataset.scan()
Dataset
  • DatasetDefinition
    DatasetDefinition
    • acceleration_columns:
      None
    • column_map:
      None
    • custom_read_kwargs:
      None
    • distance_column:
      None
    • Experiment
      Experiment
      • EyeTracker
        EyeTracker
        • left:
          None
        • model:
          None
        • mount:
          None
        • right:
          None
        • sampling_rate:
          1000
        • vendor:
          None
        • version:
          None
      • sampling_rate:
        1000
      • Screen
        Screen
        • distance_cm:
          68
        • height_cm:
          30.2
        • height_px:
          1024
        • origin:
          'upper left'
        • width_cm:
          38
        • width_px:
          1280
        • x_max_dva:
          15.599386487782953
        • x_min_dva:
          -15.599386487782953
        • y_max_dva:
          12.508044410882546
        • y_min_dva:
          -12.508044410882546
    • extract:
      None
    • dict (1 items)
      • gaze:
        'trial_{text_id:d}_{page_id:d}.csv'
    • dict (1 items)
      • dict (2 items)
        • text_id:
          <class 'int'>
        • page_id:
          <class 'int'>
    • has_resources:
      True
    • long_name:
      'pymovements Toy Dataset'
    • mirrors:
      dict (0 items)
    • name:
      'ToyDataset'
    • pixel_columns:
      None
    • position_columns:
      None
    • list (1 items)
      • ResourceDefinition
        • content:
          'gaze'
        • filename:
          'pymovements-toy-dataset.zip'
        • filename_pattern:
          'trial_{text_id:d}_{page_id:d}.csv'
        • dict (2 items)
          • text_id:
            <class 'int'>
          • page_id:
            <class 'int'>
        • load_function:
          None
        • dict (4 items)
          • time_column:
            'timestamp'
          • time_unit:
            'ms'
          • (2 more)
        • md5:
          '256901852c1c07581d375eef705855d6'
        • mirrors:
          None
        • 'https://github.com/pymovements/pymovements-toy-dat...'
          'https://github.com/pymovements/pymovements-toy-dataset/archive/refs/heads/main.zip'
    • time_column:
      None
    • time_unit:
      None
    • trial_columns:
      None
    • velocity_columns:
      None
  • events:
    tuple (0 items)
  • dict (1 items)
    • DataFrame (3 columns, 20 rows)
      shape: (20, 3)
      text_idpage_idfilepath
      i64i64str
      01"pymovements-toy-dataset-main/d…
      02"pymovements-toy-dataset-main/d…
      03"pymovements-toy-dataset-main/d…
      04"pymovements-toy-dataset-main/d…
      05"pymovements-toy-dataset-main/d…
      ………
      31"pymovements-toy-dataset-main/d…
      32"pymovements-toy-dataset-main/d…
      33"pymovements-toy-dataset-main/d…
      34"pymovements-toy-dataset-main/d…
      35"pymovements-toy-dataset-main/d…
  • gaze:
    list (0 items)
  • path:
    PosixPath('data/ToyDataset')
  • DatasetPaths
    DatasetPaths
    • dataset:
      PosixPath('data/ToyDataset')
    • downloads:
      PosixPath('data/ToyDataset/downloads')
    • events:
      PosixPath('data/ToyDataset/events')
    • precomputed_events:
      PosixPath('data/ToyDataset/precomputed_events')
    • precomputed_reading_measures:
      PosixPath('data/ToyDataset/precomputed_reading_measures')
    • preprocessed:
      PosixPath('data/ToyDataset/preprocessed')
    • raw:
      PosixPath('data/ToyDataset/raw')
    • root:
      PosixPath('data')
    • stimuli:
      PosixPath('data/ToyDataset/stimuli')
  • precomputed_events:
    list (0 items)
  • precomputed_reading_measures:
    list (0 items)
  • stimuli:
    list (0 items)

Loading into memory#

Based on the fileinfo table, we can define a subset of the dataset that we want to load into our working memory. We can do this by specifying a dictionary of the format dict[str, float | int | str | list[float | int | str]] where the keys are the column names of the fileinfo table and the values are the specifications of the files to load:

dataset.load(subset={'text_id': [1, 2], 'page_id': 1})

However, in this case we will load the entire dataset, so we do not need to specify a subset. We simply load the data into our working memory by using the Dataset.load() method without any additional arguments:

dataset.load()
Dataset
  • DatasetDefinition
    DatasetDefinition
    • acceleration_columns:
      None
    • column_map:
      None
    • custom_read_kwargs:
      None
    • distance_column:
      None
    • Experiment
      Experiment
      • EyeTracker
        EyeTracker
        • left:
          None
        • model:
          None
        • mount:
          None
        • right:
          None
        • sampling_rate:
          1000
        • vendor:
          None
        • version:
          None
      • sampling_rate:
        1000
      • Screen
        Screen
        • distance_cm:
          68
        • height_cm:
          30.2
        • height_px:
          1024
        • origin:
          'upper left'
        • width_cm:
          38
        • width_px:
          1280
        • x_max_dva:
          15.599386487782953
        • x_min_dva:
          -15.599386487782953
        • y_max_dva:
          12.508044410882546
        • y_min_dva:
          -12.508044410882546
    • extract:
      None
    • dict (1 items)
      • gaze:
        'trial_{text_id:d}_{page_id:d}.csv'
    • dict (1 items)
      • dict (2 items)
        • text_id:
          <class 'int'>
        • page_id:
          <class 'int'>
    • has_resources:
      True
    • long_name:
      'pymovements Toy Dataset'
    • mirrors:
      dict (0 items)
    • name:
      'ToyDataset'
    • pixel_columns:
      None
    • position_columns:
      None
    • list (1 items)
      • ResourceDefinition
        • content:
          'gaze'
        • filename:
          'pymovements-toy-dataset.zip'
        • filename_pattern:
          'trial_{text_id:d}_{page_id:d}.csv'
        • dict (2 items)
          • text_id:
            <class 'int'>
          • page_id:
            <class 'int'>
        • load_function:
          None
        • dict (4 items)
          • time_column:
            'timestamp'
          • time_unit:
            'ms'
          • (2 more)
        • md5:
          '256901852c1c07581d375eef705855d6'
        • mirrors:
          None
        • 'https://github.com/pymovements/pymovements-toy-dat...'
          'https://github.com/pymovements/pymovements-toy-dataset/archive/refs/heads/main.zip'
    • time_column:
      None
    • time_unit:
      None
    • trial_columns:
      None
    • velocity_columns:
      None
  • tuple (20 items)
    • Events
      • DataFrame (4 columns, 0 rows)
        shape: (0, 4)
        nameonsetoffsetduration
        stri64i64i64
      • trial_columns:
        None
    • Events
      • DataFrame (4 columns, 0 rows)
        shape: (0, 4)
        nameonsetoffsetduration
        stri64i64i64
      • trial_columns:
        None
    • (18 more)
  • dict (1 items)
    • DataFrame (3 columns, 20 rows)
      shape: (20, 3)
      text_idpage_idfilepath
      i64i64str
      01"pymovements-toy-dataset-main/d…
      02"pymovements-toy-dataset-main/d…
      03"pymovements-toy-dataset-main/d…
      04"pymovements-toy-dataset-main/d…
      05"pymovements-toy-dataset-main/d…
      ………
      31"pymovements-toy-dataset-main/d…
      32"pymovements-toy-dataset-main/d…
      33"pymovements-toy-dataset-main/d…
      34"pymovements-toy-dataset-main/d…
      35"pymovements-toy-dataset-main/d…
  • list (20 items)
    • Gaze
      • DataFrame (4 columns, 17223 rows)
        shape: (17_223, 4)
        timestimuli_xstimuli_ypixel
        i64f64f64list[f64]
        1988145-1.0-1.0[206.8, 152.4]
        1988146-1.0-1.0[206.9, 152.1]
        1988147-1.0-1.0[207.0, 151.8]
        1988148-1.0-1.0[207.1, 151.7]
        1988149-1.0-1.0[207.0, 151.5]
        …………
        2005363-1.0-1.0[361.0, 415.4]
        2005364-1.0-1.0[358.0, 414.5]
        2005365-1.0-1.0[355.8, 413.8]
        2005366-1.0-1.0[353.1, 413.2]
        2005367-1.0-1.0[351.2, 412.9]
      • Events
        Events
        • DataFrame (4 columns, 0 rows)
          shape: (0, 4)
          nameonsetoffsetduration
          stri64i64i64
        • trial_columns:
          None
      • trial_columns:
        None
      • Experiment
        Experiment
        • EyeTracker
          EyeTracker
          • left:
            None
          • model:
            None
          • mount:
            None
          • right:
            None
          • sampling_rate:
            1000
          • vendor:
            None
          • version:
            None
        • sampling_rate:
          1000
        • Screen
          Screen
          • distance_cm:
            68
          • height_cm:
            30.2
          • height_px:
            1024
          • origin:
            'upper left'
          • width_cm:
            38
          • width_px:
            1280
          • x_max_dva:
            15.599386487782953
          • x_min_dva:
            -15.599386487782953
          • y_max_dva:
            12.508044410882546
          • y_min_dva:
            -12.508044410882546
    • Gaze
      • DataFrame (4 columns, 29799 rows)
        shape: (29_799, 4)
        timestimuli_xstimuli_ypixel
        i64f64f64list[f64]
        2008305-1.0-1.0[141.4, 153.6]
        2008306-1.0-1.0[141.1, 153.2]
        2008307-1.0-1.0[140.7, 152.8]
        2008308-1.0-1.0[140.6, 152.7]
        2008309-1.0-1.0[140.5, 152.6]
        …………
        2038099-1.0-1.0[273.8, 773.8]
        2038100-1.0-1.0[273.8, 774.1]
        2038101-1.0-1.0[273.9, 774.5]
        2038102-1.0-1.0[274.0, 774.4]
        2038103-1.0-1.0[274.0, 773.9]
      • Events
        Events
        • DataFrame (4 columns, 0 rows)
          shape: (0, 4)
          nameonsetoffsetduration
          stri64i64i64
        • trial_columns:
          None
      • trial_columns:
        None
      • Experiment
        Experiment
        • EyeTracker
          EyeTracker
          • left:
            None
          • model:
            None
          • mount:
            None
          • right:
            None
          • sampling_rate:
            1000
          • vendor:
            None
          • version:
            None
        • sampling_rate:
          1000
        • Screen
          Screen
          • distance_cm:
            68
          • height_cm:
            30.2
          • height_px:
            1024
          • origin:
            'upper left'
          • width_cm:
            38
          • width_px:
            1280
          • x_max_dva:
            15.599386487782953
          • x_min_dva:
            -15.599386487782953
          • y_max_dva:
            12.508044410882546
          • y_min_dva:
            -12.508044410882546
    • (18 more)
  • path:
    PosixPath('data/ToyDataset')
  • DatasetPaths
    DatasetPaths
    • dataset:
      PosixPath('data/ToyDataset')
    • downloads:
      PosixPath('data/ToyDataset/downloads')
    • events:
      PosixPath('data/ToyDataset/events')
    • precomputed_events:
      PosixPath('data/ToyDataset/precomputed_events')
    • precomputed_reading_measures:
      PosixPath('data/ToyDataset/precomputed_reading_measures')
    • preprocessed:
      PosixPath('data/ToyDataset/preprocessed')
    • raw:
      PosixPath('data/ToyDataset/raw')
    • root:
      PosixPath('data')
    • stimuli:
      PosixPath('data/ToyDataset/stimuli')
  • precomputed_events:
    list (0 items)
  • precomputed_reading_measures:
    list (0 items)
  • stimuli:
    list (0 items)

Let’s verify that we have correctly scanned the dataset files:

dataset.fileinfo

{'gaze': shape: (20, 3)
 ┌─────────┬─────────┬─────────────────────────────────┐
 │ text_id ┆ page_id ┆ filepath                        │
 │ ---     ┆ ---     ┆ ---                             │
 │ i64     ┆ i64     ┆ str                             │
 ╞═════════╪═════════╪═════════════════════════════════╡
 │ 0       ┆ 1       ┆ pymovements-toy-dataset-main/d… │
 │ 0       ┆ 2       ┆ pymovements-toy-dataset-main/d… │
 │ 0       ┆ 3       ┆ pymovements-toy-dataset-main/d… │
 │ 0       ┆ 4       ┆ pymovements-toy-dataset-main/d… │
 │ 0       ┆ 5       ┆ pymovements-toy-dataset-main/d… │
 │ …       ┆ …       ┆ …                               │
 │ 3       ┆ 1       ┆ pymovements-toy-dataset-main/d… │
 │ 3       ┆ 2       ┆ pymovements-toy-dataset-main/d… │
 │ 3       ┆ 3       ┆ pymovements-toy-dataset-main/d… │
 │ 3       ┆ 4       ┆ pymovements-toy-dataset-main/d… │
 │ 3       ┆ 5       ┆ pymovements-toy-dataset-main/d… │
 └─────────┴─────────┴─────────────────────────────────┘}

Wonderful, all of our data has been downloaded and loaded in successfully!

What you have learned in this tutorial:#

  • how to initialize a public dataset

  • how to download and extract dataset resources

  • how to customize the default directory structure

  • how to load the dataset into your working memory