Saving and Loading Event Data#

What you will learn in this tutorial:#

how to save your event data
how to load your event data

Preparations#

We import pymovements as the alias pm for convenience.

[1]:

import pymovements as pm

/home/docs/checkouts/readthedocs.org/user_builds/pymovements/envs/v0.23.0/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
  from .autonotebook import tqdm as notebook_tqdm

Let’s start by downloading our ToyDataset and loading in its data:

[2]:

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

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

100%|██████████| 23/23 [00:00<00:00, 322.48it/s]
100%|██████████| 20/20 [00:00<00:00, 59.44it/s]

[2]:

Dataset

definition:
DatasetDefinition
DatasetDefinition
- acceleration_columns:
  None
  
  None
- column_map:
  dict (0 items)
- custom_read_kwargs:
  dict (1 items)
  - gaze:
    dict (4 items)
    
    columns:
    list (5 items)
    
    'timestamp'
    'x'
    (3 more)
    
    schema_overrides:
    dict (5 items)
    
    timestamp:
    Float64
    
    Float64
    
    x:
    Float64
    
    Float64
    
    (3 more)
    
    (2 more)
- distance_column:
  None
  
  None
- experiment:
  Experiment
  Experiment
  - eyetracker:
    EyeTracker
    
    EyeTracker
    
    left:
    None
    
    None
    
    model:
    None
    
    None
    
    mount:
    None
    
    None
    
    right:
    None
    
    None
    
    sampling_rate:
    1000
    
    1000
    
    vendor:
    None
    
    None
    
    version:
    None
    
    None
  - sampling_rate:
    1000
    
    1000
  - screen:
    Screen
    
    Screen
    
    distance_cm:
    68
    
    68
    
    height_cm:
    30.2
    
    30.2
    
    height_px:
    1024
    
    1024
    
    origin:
    'upper left'
    
    'upper left'
    
    width_cm:
    38
    
    38
    
    width_px:
    1280
    
    1280
    
    x_max_dva:
    15.599386487782953
    
    15.599386487782953
    
    x_min_dva:
    -15.599386487782953
    
    -15.599386487782953
    
    y_max_dva:
    12.508044410882546
    
    12.508044410882546
    
    y_min_dva:
    -12.508044410882546
    
    -12.508044410882546
- extract:
  None
  
  None
- filename_format:
  dict (1 items)
  - gaze:
    'trial_{text_id:d}_{page_id:d}.csv'
    
    'trial_{text_id:d}_{page_id:d}.csv'
- filename_format_schema_overrides:
  dict (1 items)
  - gaze:
    dict (2 items)
    
    text_id:
    <class 'int'>
    
    <class 'int'>
    
    page_id:
    <class 'int'>
    
    <class 'int'>
- has_resources:
  True
  
  True
- long_name:
  'pymovements Toy Dataset'
  
  'pymovements Toy Dataset'
- mirrors:
  dict (0 items)
- name:
  'ToyDataset'
  
  'ToyDataset'
- pixel_columns:
  list (2 items)
  - 'x'
  - 'y'
- position_columns:
  None
  
  None
- resources:
  list (1 items)
  - ResourceDefinition(content='gaze', filename='pymovements-toy-dataset.zip', url='http://github.com/aeye-lab/pymovements-toy-dataset/zipball/6cb5d663317bf418cec0c9abe1dde5085a8a8ebd/', md5='4da622457637a8181d86601fe17f3aa8', filename_pattern='trial_{text_id:d}_{page_id:d}.csv', filename_pattern_schema_overrides={'text_id': <class 'int'>, 'page_id': <class 'int'>})
- time_column:
  'timestamp'
  
  'timestamp'
- time_unit:
  'ms'
  
  'ms'
- trial_columns:
  None
  
  None
- velocity_columns:
  None
  
  None
events:
list (0 items)

fileinfo:

dict (1 items)

gaze:

DataFrame (3 columns, 20 rows)

shape: (20, 3)

text_id	page_id	filepath
i64	i64	str
0	1	"aeye-lab-pymovements-toy-datas…
0	2	"aeye-lab-pymovements-toy-datas…
0	3	"aeye-lab-pymovements-toy-datas…
0	4	"aeye-lab-pymovements-toy-datas…
0	5	"aeye-lab-pymovements-toy-datas…
…	…	…
3	1	"aeye-lab-pymovements-toy-datas…
3	2	"aeye-lab-pymovements-toy-datas…
3	3	"aeye-lab-pymovements-toy-datas…
3	4	"aeye-lab-pymovements-toy-datas…
3	5	"aeye-lab-pymovements-toy-datas…

gaze:

list (20 items)

Gaze

samples:

DataFrame (6 columns, 17223 rows)

shape: (17_223, 6)

time	stimuli_x	stimuli_y	text_id	page_id	pixel
i64	f64	f64	i64	i64	list[f64]
1988145	-1.0	-1.0	0	1	[206.8, 152.4]
1988146	-1.0	-1.0	0	1	[206.9, 152.1]
1988147	-1.0	-1.0	0	1	[207.0, 151.8]
1988148	-1.0	-1.0	0	1	[207.1, 151.7]
1988149	-1.0	-1.0	0	1	[207.0, 151.5]
…	…	…	…	…	…
2005363	-1.0	-1.0	0	1	[361.0, 415.4]
2005364	-1.0	-1.0	0	1	[358.0, 414.5]
2005365	-1.0	-1.0	0	1	[355.8, 413.8]
2005366	-1.0	-1.0	0	1	[353.1, 413.2]
2005367	-1.0	-1.0	0	1	[351.2, 412.9]

events:
Events
Events
- frame:
  DataFrame (6 columns, 0 rows)
  
  shape: (0, 6)
  text_id page_id name onset offset duration
  i64 i64 str i64 i64 i64
- trial_columns:
  list (2 items)
  - 'text_id'
  - 'page_id'
trial_columns:
list (2 items)
- 'text_id'
- 'page_id'
experiment:
Experiment
Experiment
- eyetracker:
  EyeTracker
  EyeTracker
  - left:
    None
    
    None
  - model:
    None
    
    None
  - mount:
    None
    
    None
  - right:
    None
    
    None
  - sampling_rate:
    1000
    
    1000
  - vendor:
    None
    
    None
  - version:
    None
    
    None
- sampling_rate:
  1000
  
  1000
- screen:
  Screen
  Screen
  - distance_cm:
    68
    
    68
  - height_cm:
    30.2
    
    30.2
  - height_px:
    1024
    
    1024
  - origin:
    'upper left'
    
    'upper left'
  - width_cm:
    38
    
    38
  - width_px:
    1280
    
    1280
  - x_max_dva:
    15.599386487782953
    
    15.599386487782953
  - x_min_dva:
    -15.599386487782953
    
    -15.599386487782953
  - y_max_dva:
    12.508044410882546
    
    12.508044410882546
  - y_min_dva:
    -12.508044410882546
    
    -12.508044410882546

Gaze

samples:

DataFrame (6 columns, 29799 rows)

shape: (29_799, 6)

time	stimuli_x	stimuli_y	text_id	page_id	pixel
i64	f64	f64	i64	i64	list[f64]
2008305	-1.0	-1.0	0	2	[141.4, 153.6]
2008306	-1.0	-1.0	0	2	[141.1, 153.2]
2008307	-1.0	-1.0	0	2	[140.7, 152.8]
2008308	-1.0	-1.0	0	2	[140.6, 152.7]
2008309	-1.0	-1.0	0	2	[140.5, 152.6]
…	…	…	…	…	…
2038099	-1.0	-1.0	0	2	[273.8, 773.8]
2038100	-1.0	-1.0	0	2	[273.8, 774.1]
2038101	-1.0	-1.0	0	2	[273.9, 774.5]
2038102	-1.0	-1.0	0	2	[274.0, 774.4]
2038103	-1.0	-1.0	0	2	[274.0, 773.9]

events:
Events
Events
- frame:
  DataFrame (6 columns, 0 rows)
  
  shape: (0, 6)
  text_id page_id name onset offset duration
  i64 i64 str i64 i64 i64
- trial_columns:
  list (2 items)
  - 'text_id'
  - 'page_id'
trial_columns:
list (2 items)
- 'text_id'
- 'page_id'
experiment:
Experiment
Experiment
- eyetracker:
  EyeTracker
  EyeTracker
  - left:
    None
    
    None
  - model:
    None
    
    None
  - mount:
    None
    
    None
  - right:
    None
    
    None
  - sampling_rate:
    1000
    
    1000
  - vendor:
    None
    
    None
  - version:
    None
    
    None
- sampling_rate:
  1000
  
  1000
- screen:
  Screen
  Screen
  - distance_cm:
    68
    
    68
  - height_cm:
    30.2
    
    30.2
  - height_px:
    1024
    
    1024
  - origin:
    'upper left'
    
    'upper left'
  - width_cm:
    38
    
    38
  - width_px:
    1280
    
    1280
  - x_max_dva:
    15.599386487782953
    
    15.599386487782953
  - x_min_dva:
    -15.599386487782953
    
    -15.599386487782953
  - y_max_dva:
    12.508044410882546
    
    12.508044410882546
  - y_min_dva:
    -12.508044410882546
    
    -12.508044410882546

(18 more)

path:
PosixPath('data/ToyDataset')

PosixPath('data/ToyDataset')
paths:
DatasetPaths
DatasetPaths
- dataset:
  PosixPath('data/ToyDataset')
  
  PosixPath('data/ToyDataset')
- downloads:
  PosixPath('data/ToyDataset/downloads')
  
  PosixPath('data/ToyDataset/downloads')
- events:
  PosixPath('data/ToyDataset/events')
  
  PosixPath('data/ToyDataset/events')
- precomputed_events:
  PosixPath('data/ToyDataset/precomputed_events')
  
  PosixPath('data/ToyDataset/precomputed_events')
- precomputed_reading_measures:
  PosixPath
  
  PosixPath('data/ToyDataset/precomputed_reading_measures')
- preprocessed:
  PosixPath('data/ToyDataset/preprocessed')
  
  PosixPath('data/ToyDataset/preprocessed')
- raw:
  PosixPath('data/ToyDataset/raw')
  
  PosixPath('data/ToyDataset/raw')
- root:
  PosixPath('data/ToyDataset')
  
  PosixPath('data/ToyDataset')
precomputed_events:
list (0 items)
precomputed_reading_measures:
list (0 items)

Now let’s do some preprocessing:

[3]:

dataset.pix2deg()
dataset.pos2vel()

dataset.gaze[0]

100%|██████████| 20/20 [00:00<00:00, 32.30it/s]
100%|██████████| 20/20 [00:00<00:00, 65.30it/s]

[3]:

Gaze

samples:

DataFrame (8 columns, 17223 rows)

shape: (17_223, 8)

time	stimuli_x	stimuli_y	text_id	page_id	pixel	position	velocity
i64	f64	f64	i64	i64	list[f64]	list[f64]	list[f64]
1988145	-1.0	-1.0	0	1	[206.8, 152.4]	[-10.697598, -8.852399]	[null, null]
1988146	-1.0	-1.0	0	1	[206.9, 152.1]	[-10.695183, -8.859678]	[null, null]
1988147	-1.0	-1.0	0	1	[207.0, 151.8]	[-10.692768, -8.866956]	[1.610194, -5.256267]
1988148	-1.0	-1.0	0	1	[207.1, 151.7]	[-10.690352, -8.869381]	[0.402548, -4.447465]
1988149	-1.0	-1.0	0	1	[207.0, 151.5]	[-10.692768, -8.874233]	[0.402561, -3.234462]
…	…	…	…	…	…	…	…
2005363	-1.0	-1.0	0	1	[361.0, 415.4]	[-6.932438, -2.386672]	[-63.266374, -21.085616]
2005364	-1.0	-1.0	0	1	[358.0, 414.5]	[-7.006376, -2.408998]	[-63.249652, -19.431326]
2005365	-1.0	-1.0	0	1	[355.8, 413.8]	[-7.060582, -2.426362]	[-60.359624, -15.710061]
2005366	-1.0	-1.0	0	1	[353.1, 413.2]	[-7.12709, -2.441245]	[null, null]
2005367	-1.0	-1.0	0	1	[351.2, 412.9]	[-7.173881, -2.448686]	[null, null]

events:
Events
Events
- frame:
  DataFrame (6 columns, 0 rows)
  
  shape: (0, 6)
  text_id page_id name onset offset duration
  i64 i64 str i64 i64 i64
- trial_columns:
  list (2 items)
  - 'text_id'
  - 'page_id'
trial_columns:
list (2 items)
- 'text_id'
- 'page_id'
experiment:
Experiment
Experiment
- eyetracker:
  EyeTracker
  EyeTracker
  - left:
    None
    
    None
  - model:
    None
    
    None
  - mount:
    None
    
    None
  - right:
    None
    
    None
  - sampling_rate:
    1000
    
    1000
  - vendor:
    None
    
    None
  - version:
    None
    
    None
- sampling_rate:
  1000
  
  1000
- screen:
  Screen
  Screen
  - distance_cm:
    68
    
    68
  - height_cm:
    30.2
    
    30.2
  - height_px:
    1024
    
    1024
  - origin:
    'upper left'
    
    'upper left'
  - width_cm:
    38
    
    38
  - width_px:
    1280
    
    1280
  - x_max_dva:
    15.599386487782953
    
    15.599386487782953
  - x_min_dva:
    -15.599386487782953
    
    -15.599386487782953
  - y_max_dva:
    12.508044410882546
    
    12.508044410882546
  - y_min_dva:
    -12.508044410882546
    
    -12.508044410882546

Detect some events:

[4]:

dataset.detect_events('ivt')

dataset.events[0]

20it [00:00, 97.00it/s]

[4]:

Events

frame:

DataFrame (6 columns, 73 rows)

shape: (73, 6)

text_id	page_id	name	onset	offset	duration
i64	i64	str	i64	i64	i64
0	1	"fixation"	1988147	1988322	175
0	1	"fixation"	1988351	1988546	195
0	1	"fixation"	1988592	1988736	144
0	1	"fixation"	1988788	1989013	225
0	1	"fixation"	1989060	1989170	110
…	…	…	…	…	…
0	1	"fixation"	2004132	2004331	199
0	1	"fixation"	2004399	2004687	288
0	1	"fixation"	2004714	2004878	164
0	1	"fixation"	2004931	2005109	178
0	1	"fixation"	2005138	2005287	149

trial_columns:
list (2 items)
- 'text_id'
- 'page_id'

[5]:

dataset.detect_events('microsaccades')

dataset.events[0]

20it [00:00, 54.84it/s]

[5]:

Events

frame:

DataFrame (6 columns, 215 rows)

shape: (215, 6)

text_id	page_id	name	onset	offset	duration
i64	i64	str	i64	i64	i64
0	1	"fixation"	1988147	1988322	175
0	1	"fixation"	1988351	1988546	195
0	1	"fixation"	1988592	1988736	144
0	1	"fixation"	1988788	1989013	225
0	1	"fixation"	1989060	1989170	110
…	…	…	…	…	…
0	1	"saccade"	2005110	2005126	16
0	1	"saccade"	2005128	2005138	10
0	1	"saccade"	2005288	2005345	57
0	1	"saccade"	2005347	2005356	9
0	1	"saccade"	2005359	2005365	6

trial_columns:
list (2 items)
- 'text_id'
- 'page_id'

We now have event dataframes available with our detected event data.

Saving#

Saving your event data is as simple as:

[6]:

dataset.save_events()

100%|██████████| 20/20 [00:00<00:00, 2841.67it/s]

[6]:

Dataset

definition:
DatasetDefinition
DatasetDefinition
- acceleration_columns:
  None
  
  None
- column_map:
  dict (0 items)
- custom_read_kwargs:
  dict (1 items)
  - gaze:
    dict (4 items)
    
    columns:
    list (5 items)
    
    'timestamp'
    'x'
    (3 more)
    
    schema_overrides:
    dict (5 items)
    
    timestamp:
    Float64
    
    Float64
    
    x:
    Float64
    
    Float64
    
    (3 more)
    
    (2 more)
- distance_column:
  None
  
  None
- experiment:
  Experiment
  Experiment
  - eyetracker:
    EyeTracker
    
    EyeTracker
    
    left:
    None
    
    None
    
    model:
    None
    
    None
    
    mount:
    None
    
    None
    
    right:
    None
    
    None
    
    sampling_rate:
    1000
    
    1000
    
    vendor:
    None
    
    None
    
    version:
    None
    
    None
  - sampling_rate:
    1000
    
    1000
  - screen:
    Screen
    
    Screen
    
    distance_cm:
    68
    
    68
    
    height_cm:
    30.2
    
    30.2
    
    height_px:
    1024
    
    1024
    
    origin:
    'upper left'
    
    'upper left'
    
    width_cm:
    38
    
    38
    
    width_px:
    1280
    
    1280
    
    x_max_dva:
    15.599386487782953
    
    15.599386487782953
    
    x_min_dva:
    -15.599386487782953
    
    -15.599386487782953
    
    y_max_dva:
    12.508044410882546
    
    12.508044410882546
    
    y_min_dva:
    -12.508044410882546
    
    -12.508044410882546
- extract:
  None
  
  None
- filename_format:
  dict (1 items)
  - gaze:
    'trial_{text_id:d}_{page_id:d}.csv'
    
    'trial_{text_id:d}_{page_id:d}.csv'
- filename_format_schema_overrides:
  dict (1 items)
  - gaze:
    dict (2 items)
    
    text_id:
    <class 'int'>
    
    <class 'int'>
    
    page_id:
    <class 'int'>
    
    <class 'int'>
- has_resources:
  True
  
  True
- long_name:
  'pymovements Toy Dataset'
  
  'pymovements Toy Dataset'
- mirrors:
  dict (0 items)
- name:
  'ToyDataset'
  
  'ToyDataset'
- pixel_columns:
  list (2 items)
  - 'x'
  - 'y'
- position_columns:
  None
  
  None
- resources:
  list (1 items)
  - ResourceDefinition(content='gaze', filename='pymovements-toy-dataset.zip', url='http://github.com/aeye-lab/pymovements-toy-dataset/zipball/6cb5d663317bf418cec0c9abe1dde5085a8a8ebd/', md5='4da622457637a8181d86601fe17f3aa8', filename_pattern='trial_{text_id:d}_{page_id:d}.csv', filename_pattern_schema_overrides={'text_id': <class 'int'>, 'page_id': <class 'int'>})
- time_column:
  'timestamp'
  
  'timestamp'
- time_unit:
  'ms'
  
  'ms'
- trial_columns:
  None
  
  None
- velocity_columns:
  None
  
  None

events:

list (20 items)

Events

frame:

DataFrame (6 columns, 215 rows)

shape: (215, 6)

text_id	page_id	name	onset	offset	duration
i64	i64	str	i64	i64	i64
0	1	"fixation"	1988147	1988322	175
0	1	"fixation"	1988351	1988546	195
0	1	"fixation"	1988592	1988736	144
0	1	"fixation"	1988788	1989013	225
0	1	"fixation"	1989060	1989170	110
…	…	…	…	…	…
0	1	"saccade"	2005110	2005126	16
0	1	"saccade"	2005128	2005138	10
0	1	"saccade"	2005288	2005345	57
0	1	"saccade"	2005347	2005356	9
0	1	"saccade"	2005359	2005365	6

trial_columns:
list (2 items)
- 'text_id'
- 'page_id'

Events

frame:

DataFrame (6 columns, 352 rows)

shape: (352, 6)

text_id	page_id	name	onset	offset	duration
i64	i64	str	i64	i64	i64
0	2	"fixation"	2008307	2008474	167
0	2	"fixation"	2008498	2008603	105
0	2	"fixation"	2008628	2008806	178
0	2	"fixation"	2008862	2009051	189
0	2	"fixation"	2009064	2009201	137
…	…	…	…	…	…
0	2	"saccade"	2037638	2037654	16
0	2	"saccade"	2037656	2037666	10
0	2	"saccade"	2037812	2037830	18
0	2	"saccade"	2037832	2037839	7
0	2	"saccade"	2037845	2037851	6

trial_columns:
list (2 items)
- 'text_id'
- 'page_id'

(18 more)

fileinfo:

dict (1 items)

gaze:

DataFrame (3 columns, 20 rows)

shape: (20, 3)

text_id	page_id	filepath
i64	i64	str
0	1	"aeye-lab-pymovements-toy-datas…
0	2	"aeye-lab-pymovements-toy-datas…
0	3	"aeye-lab-pymovements-toy-datas…
0	4	"aeye-lab-pymovements-toy-datas…
0	5	"aeye-lab-pymovements-toy-datas…
…	…	…
3	1	"aeye-lab-pymovements-toy-datas…
3	2	"aeye-lab-pymovements-toy-datas…
3	3	"aeye-lab-pymovements-toy-datas…
3	4	"aeye-lab-pymovements-toy-datas…
3	5	"aeye-lab-pymovements-toy-datas…

gaze:

list (20 items)

Gaze

samples:

DataFrame (8 columns, 17223 rows)

shape: (17_223, 8)

time	stimuli_x	stimuli_y	text_id	page_id	pixel	position	velocity
i64	f64	f64	i64	i64	list[f64]	list[f64]	list[f64]
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1988148	-1.0	-1.0	0	1	[207.1, 151.7]	[-10.690352, -8.869381]	[0.402548, -4.447465]
1988149	-1.0	-1.0	0	1	[207.0, 151.5]	[-10.692768, -8.874233]	[0.402561, -3.234462]
…	…	…	…	…	…	…	…
2005363	-1.0	-1.0	0	1	[361.0, 415.4]	[-6.932438, -2.386672]	[-63.266374, -21.085616]
2005364	-1.0	-1.0	0	1	[358.0, 414.5]	[-7.006376, -2.408998]	[-63.249652, -19.431326]
2005365	-1.0	-1.0	0	1	[355.8, 413.8]	[-7.060582, -2.426362]	[-60.359624, -15.710061]
2005366	-1.0	-1.0	0	1	[353.1, 413.2]	[-7.12709, -2.441245]	[null, null]
2005367	-1.0	-1.0	0	1	[351.2, 412.9]	[-7.173881, -2.448686]	[null, null]

events:

Events

frame:

DataFrame (6 columns, 215 rows)

shape: (215, 6)

text_id	page_id	name	onset	offset	duration
i64	i64	str	i64	i64	i64
0	1	"fixation"	1988147	1988322	175
0	1	"fixation"	1988351	1988546	195
0	1	"fixation"	1988592	1988736	144
0	1	"fixation"	1988788	1989013	225
0	1	"fixation"	1989060	1989170	110
…	…	…	…	…	…
0	1	"saccade"	2005110	2005126	16
0	1	"saccade"	2005128	2005138	10
0	1	"saccade"	2005288	2005345	57
0	1	"saccade"	2005347	2005356	9
0	1	"saccade"	2005359	2005365	6

trial_columns:
list (2 items)
- 'text_id'
- 'page_id'

trial_columns:
list (2 items)
- 'text_id'
- 'page_id'
experiment:
Experiment
Experiment
- eyetracker:
  EyeTracker
  EyeTracker
  - left:
    None
    
    None
  - model:
    None
    
    None
  - mount:
    None
    
    None
  - right:
    None
    
    None
  - sampling_rate:
    1000
    
    1000
  - vendor:
    None
    
    None
  - version:
    None
    
    None
- sampling_rate:
  1000
  
  1000
- screen:
  Screen
  Screen
  - distance_cm:
    68
    
    68
  - height_cm:
    30.2
    
    30.2
  - height_px:
    1024
    
    1024
  - origin:
    'upper left'
    
    'upper left'
  - width_cm:
    38
    
    38
  - width_px:
    1280
    
    1280
  - x_max_dva:
    15.599386487782953
    
    15.599386487782953
  - x_min_dva:
    -15.599386487782953
    
    -15.599386487782953
  - y_max_dva:
    12.508044410882546
    
    12.508044410882546
  - y_min_dva:
    -12.508044410882546
    
    -12.508044410882546

Gaze

samples:

DataFrame (8 columns, 29799 rows)

shape: (29_799, 8)

time	stimuli_x	stimuli_y	text_id	page_id	pixel	position	velocity
i64	f64	f64	i64	i64	list[f64]	list[f64]	list[f64]
2008305	-1.0	-1.0	0	2	[141.4, 153.6]	[-12.268583, -8.823284]	[null, null]
2008306	-1.0	-1.0	0	2	[141.1, 153.2]	[-12.275749, -8.832989]	[null, null]
2008307	-1.0	-1.0	0	2	[140.7, 152.8]	[-12.285302, -8.842695]	[-5.572617, -6.065816]
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…	…	…	…	…	…	…	…
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2038103	-1.0	-1.0	0	2	[274.0, 773.9]	[-9.066271, 6.492621]	[null, null]

events:

Events

frame:

DataFrame (6 columns, 352 rows)

shape: (352, 6)

text_id	page_id	name	onset	offset	duration
i64	i64	str	i64	i64	i64
0	2	"fixation"	2008307	2008474	167
0	2	"fixation"	2008498	2008603	105
0	2	"fixation"	2008628	2008806	178
0	2	"fixation"	2008862	2009051	189
0	2	"fixation"	2009064	2009201	137
…	…	…	…	…	…
0	2	"saccade"	2037638	2037654	16
0	2	"saccade"	2037656	2037666	10
0	2	"saccade"	2037812	2037830	18
0	2	"saccade"	2037832	2037839	7
0	2	"saccade"	2037845	2037851	6

trial_columns:
list (2 items)
- 'text_id'
- 'page_id'

trial_columns:
list (2 items)
- 'text_id'
- 'page_id'
experiment:
Experiment
Experiment
- eyetracker:
  EyeTracker
  EyeTracker
  - left:
    None
    
    None
  - model:
    None
    
    None
  - mount:
    None
    
    None
  - right:
    None
    
    None
  - sampling_rate:
    1000
    
    1000
  - vendor:
    None
    
    None
  - version:
    None
    
    None
- sampling_rate:
  1000
  
  1000
- screen:
  Screen
  Screen
  - distance_cm:
    68
    
    68
  - height_cm:
    30.2
    
    30.2
  - height_px:
    1024
    
    1024
  - origin:
    'upper left'
    
    'upper left'
  - width_cm:
    38
    
    38
  - width_px:
    1280
    
    1280
  - x_max_dva:
    15.599386487782953
    
    15.599386487782953
  - x_min_dva:
    -15.599386487782953
    
    -15.599386487782953
  - y_max_dva:
    12.508044410882546
    
    12.508044410882546
  - y_min_dva:
    -12.508044410882546
    
    -12.508044410882546

(18 more)

path:
PosixPath('data/ToyDataset')

PosixPath('data/ToyDataset')
paths:
DatasetPaths
DatasetPaths
- dataset:
  PosixPath('data/ToyDataset')
  
  PosixPath('data/ToyDataset')
- downloads:
  PosixPath('data/ToyDataset/downloads')
  
  PosixPath('data/ToyDataset/downloads')
- events:
  PosixPath('data/ToyDataset/events')
  
  PosixPath('data/ToyDataset/events')
- precomputed_events:
  PosixPath('data/ToyDataset/precomputed_events')
  
  PosixPath('data/ToyDataset/precomputed_events')
- precomputed_reading_measures:
  PosixPath
  
  PosixPath('data/ToyDataset/precomputed_reading_measures')
- preprocessed:
  PosixPath('data/ToyDataset/preprocessed')
  
  PosixPath('data/ToyDataset/preprocessed')
- raw:
  PosixPath('data/ToyDataset/raw')
  
  PosixPath('data/ToyDataset/raw')
- root:
  PosixPath('data/ToyDataset')
  
  PosixPath('data/ToyDataset')
precomputed_events:
list (0 items)
precomputed_reading_measures:
list (0 items)

All of the event data is saved into this directory:

[7]:

dataset.paths.events

[7]:

PosixPath('data/ToyDataset/events')

Let’s confirm it by printing all the new files in this directory:

[8]:

print(list(dataset.paths.events.glob('*/*/*')))

[PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_0_1.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_1_2.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_0_2.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_3_5.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_1_4.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_0_4.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_3_4.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_2_3.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_2_2.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_3_1.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_1_5.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_3_3.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_2_4.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_3_2.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_2_5.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_1_3.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_0_3.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_1_1.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_0_5.feather'), PosixPath('data/ToyDataset/events/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_2_1.feather')]

All of the files have been saved into the Dataset.paths.events as feather files.

If we want to save the data into an alternative directory and also use a different file format like csv we can use the following:

[9]:

dataset.save_events(events_dirname='events_csv', extension='csv')

100%|██████████| 20/20 [00:00<00:00, 2171.75it/s]

[9]:

Dataset

definition:
DatasetDefinition
DatasetDefinition
- acceleration_columns:
  None
  
  None
- column_map:
  dict (0 items)
- custom_read_kwargs:
  dict (1 items)
  - gaze:
    dict (4 items)
    
    columns:
    list (5 items)
    
    'timestamp'
    'x'
    (3 more)
    
    schema_overrides:
    dict (5 items)
    
    timestamp:
    Float64
    
    Float64
    
    x:
    Float64
    
    Float64
    
    (3 more)
    
    (2 more)
- distance_column:
  None
  
  None
- experiment:
  Experiment
  Experiment
  - eyetracker:
    EyeTracker
    
    EyeTracker
    
    left:
    None
    
    None
    
    model:
    None
    
    None
    
    mount:
    None
    
    None
    
    right:
    None
    
    None
    
    sampling_rate:
    1000
    
    1000
    
    vendor:
    None
    
    None
    
    version:
    None
    
    None
  - sampling_rate:
    1000
    
    1000
  - screen:
    Screen
    
    Screen
    
    distance_cm:
    68
    
    68
    
    height_cm:
    30.2
    
    30.2
    
    height_px:
    1024
    
    1024
    
    origin:
    'upper left'
    
    'upper left'
    
    width_cm:
    38
    
    38
    
    width_px:
    1280
    
    1280
    
    x_max_dva:
    15.599386487782953
    
    15.599386487782953
    
    x_min_dva:
    -15.599386487782953
    
    -15.599386487782953
    
    y_max_dva:
    12.508044410882546
    
    12.508044410882546
    
    y_min_dva:
    -12.508044410882546
    
    -12.508044410882546
- extract:
  None
  
  None
- filename_format:
  dict (1 items)
  - gaze:
    'trial_{text_id:d}_{page_id:d}.csv'
    
    'trial_{text_id:d}_{page_id:d}.csv'
- filename_format_schema_overrides:
  dict (1 items)
  - gaze:
    dict (2 items)
    
    text_id:
    <class 'int'>
    
    <class 'int'>
    
    page_id:
    <class 'int'>
    
    <class 'int'>
- has_resources:
  True
  
  True
- long_name:
  'pymovements Toy Dataset'
  
  'pymovements Toy Dataset'
- mirrors:
  dict (0 items)
- name:
  'ToyDataset'
  
  'ToyDataset'
- pixel_columns:
  list (2 items)
  - 'x'
  - 'y'
- position_columns:
  None
  
  None
- resources:
  list (1 items)
  - ResourceDefinition(content='gaze', filename='pymovements-toy-dataset.zip', url='http://github.com/aeye-lab/pymovements-toy-dataset/zipball/6cb5d663317bf418cec0c9abe1dde5085a8a8ebd/', md5='4da622457637a8181d86601fe17f3aa8', filename_pattern='trial_{text_id:d}_{page_id:d}.csv', filename_pattern_schema_overrides={'text_id': <class 'int'>, 'page_id': <class 'int'>})
- time_column:
  'timestamp'
  
  'timestamp'
- time_unit:
  'ms'
  
  'ms'
- trial_columns:
  None
  
  None
- velocity_columns:
  None
  
  None

events:

list (20 items)

Events

frame:

DataFrame (6 columns, 215 rows)

shape: (215, 6)

text_id	page_id	name	onset	offset	duration
i64	i64	str	i64	i64	i64
0	1	"fixation"	1988147	1988322	175
0	1	"fixation"	1988351	1988546	195
0	1	"fixation"	1988592	1988736	144
0	1	"fixation"	1988788	1989013	225
0	1	"fixation"	1989060	1989170	110
…	…	…	…	…	…
0	1	"saccade"	2005110	2005126	16
0	1	"saccade"	2005128	2005138	10
0	1	"saccade"	2005288	2005345	57
0	1	"saccade"	2005347	2005356	9
0	1	"saccade"	2005359	2005365	6

trial_columns:
list (2 items)
- 'text_id'
- 'page_id'

Events

frame:

DataFrame (6 columns, 352 rows)

shape: (352, 6)

text_id	page_id	name	onset	offset	duration
i64	i64	str	i64	i64	i64
0	2	"fixation"	2008307	2008474	167
0	2	"fixation"	2008498	2008603	105
0	2	"fixation"	2008628	2008806	178
0	2	"fixation"	2008862	2009051	189
0	2	"fixation"	2009064	2009201	137
…	…	…	…	…	…
0	2	"saccade"	2037638	2037654	16
0	2	"saccade"	2037656	2037666	10
0	2	"saccade"	2037812	2037830	18
0	2	"saccade"	2037832	2037839	7
0	2	"saccade"	2037845	2037851	6

trial_columns:
list (2 items)
- 'text_id'
- 'page_id'

(18 more)

fileinfo:

dict (1 items)

gaze:

DataFrame (3 columns, 20 rows)

shape: (20, 3)

text_id	page_id	filepath
i64	i64	str
0	1	"aeye-lab-pymovements-toy-datas…
0	2	"aeye-lab-pymovements-toy-datas…
0	3	"aeye-lab-pymovements-toy-datas…
0	4	"aeye-lab-pymovements-toy-datas…
0	5	"aeye-lab-pymovements-toy-datas…
…	…	…
3	1	"aeye-lab-pymovements-toy-datas…
3	2	"aeye-lab-pymovements-toy-datas…
3	3	"aeye-lab-pymovements-toy-datas…
3	4	"aeye-lab-pymovements-toy-datas…
3	5	"aeye-lab-pymovements-toy-datas…

gaze:

list (20 items)

Gaze

samples:

DataFrame (8 columns, 17223 rows)

shape: (17_223, 8)

time	stimuli_x	stimuli_y	text_id	page_id	pixel	position	velocity
i64	f64	f64	i64	i64	list[f64]	list[f64]	list[f64]
1988145	-1.0	-1.0	0	1	[206.8, 152.4]	[-10.697598, -8.852399]	[null, null]
1988146	-1.0	-1.0	0	1	[206.9, 152.1]	[-10.695183, -8.859678]	[null, null]
1988147	-1.0	-1.0	0	1	[207.0, 151.8]	[-10.692768, -8.866956]	[1.610194, -5.256267]
1988148	-1.0	-1.0	0	1	[207.1, 151.7]	[-10.690352, -8.869381]	[0.402548, -4.447465]
1988149	-1.0	-1.0	0	1	[207.0, 151.5]	[-10.692768, -8.874233]	[0.402561, -3.234462]
…	…	…	…	…	…	…	…
2005363	-1.0	-1.0	0	1	[361.0, 415.4]	[-6.932438, -2.386672]	[-63.266374, -21.085616]
2005364	-1.0	-1.0	0	1	[358.0, 414.5]	[-7.006376, -2.408998]	[-63.249652, -19.431326]
2005365	-1.0	-1.0	0	1	[355.8, 413.8]	[-7.060582, -2.426362]	[-60.359624, -15.710061]
2005366	-1.0	-1.0	0	1	[353.1, 413.2]	[-7.12709, -2.441245]	[null, null]
2005367	-1.0	-1.0	0	1	[351.2, 412.9]	[-7.173881, -2.448686]	[null, null]

events:

Events

frame:

DataFrame (6 columns, 215 rows)

shape: (215, 6)

text_id	page_id	name	onset	offset	duration
i64	i64	str	i64	i64	i64
0	1	"fixation"	1988147	1988322	175
0	1	"fixation"	1988351	1988546	195
0	1	"fixation"	1988592	1988736	144
0	1	"fixation"	1988788	1989013	225
0	1	"fixation"	1989060	1989170	110
…	…	…	…	…	…
0	1	"saccade"	2005110	2005126	16
0	1	"saccade"	2005128	2005138	10
0	1	"saccade"	2005288	2005345	57
0	1	"saccade"	2005347	2005356	9
0	1	"saccade"	2005359	2005365	6

trial_columns:
list (2 items)
- 'text_id'
- 'page_id'

trial_columns:
list (2 items)
- 'text_id'
- 'page_id'
experiment:
Experiment
Experiment
- eyetracker:
  EyeTracker
  EyeTracker
  - left:
    None
    
    None
  - model:
    None
    
    None
  - mount:
    None
    
    None
  - right:
    None
    
    None
  - sampling_rate:
    1000
    
    1000
  - vendor:
    None
    
    None
  - version:
    None
    
    None
- sampling_rate:
  1000
  
  1000
- screen:
  Screen
  Screen
  - distance_cm:
    68
    
    68
  - height_cm:
    30.2
    
    30.2
  - height_px:
    1024
    
    1024
  - origin:
    'upper left'
    
    'upper left'
  - width_cm:
    38
    
    38
  - width_px:
    1280
    
    1280
  - x_max_dva:
    15.599386487782953
    
    15.599386487782953
  - x_min_dva:
    -15.599386487782953
    
    -15.599386487782953
  - y_max_dva:
    12.508044410882546
    
    12.508044410882546
  - y_min_dva:
    -12.508044410882546
    
    -12.508044410882546

Gaze

samples:

DataFrame (8 columns, 29799 rows)

shape: (29_799, 8)

time	stimuli_x	stimuli_y	text_id	page_id	pixel	position	velocity
i64	f64	f64	i64	i64	list[f64]	list[f64]	list[f64]
2008305	-1.0	-1.0	0	2	[141.4, 153.6]	[-12.268583, -8.823284]	[null, null]
2008306	-1.0	-1.0	0	2	[141.1, 153.2]	[-12.275749, -8.832989]	[null, null]
2008307	-1.0	-1.0	0	2	[140.7, 152.8]	[-12.285302, -8.842695]	[-5.572617, -6.065816]
2008308	-1.0	-1.0	0	2	[140.6, 152.7]	[-12.28769, -8.845121]	[-3.582268, -4.043733]
2008309	-1.0	-1.0	0	2	[140.5, 152.6]	[-12.290078, -8.847547]	[-2.388085, -2.021821]
…	…	…	…	…	…	…	…
2038099	-1.0	-1.0	0	2	[273.8, 773.8]	[-9.071149, 6.490168]	[1.21962, 1.635403]
2038100	-1.0	-1.0	0	2	[273.8, 774.1]	[-9.071149, 6.497527]	[1.626175, 4.497406]
2038101	-1.0	-1.0	0	2	[273.9, 774.5]	[-9.06871, 6.50734]	[1.626186, 1.635423]
2038102	-1.0	-1.0	0	2	[274.0, 774.4]	[-9.066271, 6.504886]	[null, null]
2038103	-1.0	-1.0	0	2	[274.0, 773.9]	[-9.066271, 6.492621]	[null, null]

events:

Events

frame:

DataFrame (6 columns, 352 rows)

shape: (352, 6)

text_id	page_id	name	onset	offset	duration
i64	i64	str	i64	i64	i64
0	2	"fixation"	2008307	2008474	167
0	2	"fixation"	2008498	2008603	105
0	2	"fixation"	2008628	2008806	178
0	2	"fixation"	2008862	2009051	189
0	2	"fixation"	2009064	2009201	137
…	…	…	…	…	…
0	2	"saccade"	2037638	2037654	16
0	2	"saccade"	2037656	2037666	10
0	2	"saccade"	2037812	2037830	18
0	2	"saccade"	2037832	2037839	7
0	2	"saccade"	2037845	2037851	6

trial_columns:
list (2 items)
- 'text_id'
- 'page_id'

trial_columns:
list (2 items)
- 'text_id'
- 'page_id'
experiment:
Experiment
Experiment
- eyetracker:
  EyeTracker
  EyeTracker
  - left:
    None
    
    None
  - model:
    None
    
    None
  - mount:
    None
    
    None
  - right:
    None
    
    None
  - sampling_rate:
    1000
    
    1000
  - vendor:
    None
    
    None
  - version:
    None
    
    None
- sampling_rate:
  1000
  
  1000
- screen:
  Screen
  Screen
  - distance_cm:
    68
    
    68
  - height_cm:
    30.2
    
    30.2
  - height_px:
    1024
    
    1024
  - origin:
    'upper left'
    
    'upper left'
  - width_cm:
    38
    
    38
  - width_px:
    1280
    
    1280
  - x_max_dva:
    15.599386487782953
    
    15.599386487782953
  - x_min_dva:
    -15.599386487782953
    
    -15.599386487782953
  - y_max_dva:
    12.508044410882546
    
    12.508044410882546
  - y_min_dva:
    -12.508044410882546
    
    -12.508044410882546

(18 more)

path:
PosixPath('data/ToyDataset')

PosixPath('data/ToyDataset')
paths:
DatasetPaths
DatasetPaths
- dataset:
  PosixPath('data/ToyDataset')
  
  PosixPath('data/ToyDataset')
- downloads:
  PosixPath('data/ToyDataset/downloads')
  
  PosixPath('data/ToyDataset/downloads')
- events:
  PosixPath('data/ToyDataset/events')
  
  PosixPath('data/ToyDataset/events')
- precomputed_events:
  PosixPath('data/ToyDataset/precomputed_events')
  
  PosixPath('data/ToyDataset/precomputed_events')
- precomputed_reading_measures:
  PosixPath
  
  PosixPath('data/ToyDataset/precomputed_reading_measures')
- preprocessed:
  PosixPath('data/ToyDataset/preprocessed')
  
  PosixPath('data/ToyDataset/preprocessed')
- raw:
  PosixPath('data/ToyDataset/raw')
  
  PosixPath('data/ToyDataset/raw')
- root:
  PosixPath('data/ToyDataset')
  
  PosixPath('data/ToyDataset')
precomputed_events:
list (0 items)
precomputed_reading_measures:
list (0 items)

Let’s confirm again by printing all the new files in this alternative directory:

[10]:

alternative_dirpath = dataset.path / 'events_csv'
print(list(alternative_dirpath.glob('*/*/*')))

[PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_2_2.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_2_5.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_3_1.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_2_1.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_1_1.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_3_3.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_3_2.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_3_4.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_1_3.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_2_3.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_0_5.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_0_2.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_1_4.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_2_4.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_0_3.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_1_5.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_1_2.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_0_4.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_0_1.csv'), PosixPath('data/ToyDataset/events_csv/aeye-lab-pymovements-toy-dataset-6cb5d66/data/trial_3_5.csv')]

Loading#

Now let’s imagine that this preprocessing and saving was done in another file and we only want to load the preprocessed data.

We simulate this by initializing a new dataset object. We don’t need to download any additional data.

[11]:

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

The preprocessed data can now simply be loaded by setting preprocessed to True:

[12]:

preprocessed_dataset.load(events=True)

dataset.events[0]

100%|██████████| 20/20 [00:00<00:00, 64.03it/s]
100%|██████████| 20/20 [00:00<00:00, 1042.48it/s]

[12]:

Events

frame:

DataFrame (6 columns, 215 rows)

shape: (215, 6)

text_id	page_id	name	onset	offset	duration
i64	i64	str	i64	i64	i64
0	1	"fixation"	1988147	1988322	175
0	1	"fixation"	1988351	1988546	195
0	1	"fixation"	1988592	1988736	144
0	1	"fixation"	1988788	1989013	225
0	1	"fixation"	1989060	1989170	110
…	…	…	…	…	…
0	1	"saccade"	2005110	2005126	16
0	1	"saccade"	2005128	2005138	10
0	1	"saccade"	2005288	2005345	57
0	1	"saccade"	2005347	2005356	9
0	1	"saccade"	2005359	2005365	6

trial_columns:
list (2 items)
- 'text_id'
- 'page_id'

By default, the events directory and the feather extension will be chosen.

In case of alternative directory names or other file formats you can use the following:

[13]:

preprocessed_dataset.load(
    events=True,
    events_dirname='events_csv',
    extension='csv',
)
dataset.events[0]

100%|██████████| 20/20 [00:00<00:00, 60.96it/s]
100%|██████████| 20/20 [00:00<00:00, 913.61it/s]

[13]:

Events

frame:

DataFrame (6 columns, 215 rows)

shape: (215, 6)

text_id	page_id	name	onset	offset	duration
i64	i64	str	i64	i64	i64
0	1	"fixation"	1988147	1988322	175
0	1	"fixation"	1988351	1988546	195
0	1	"fixation"	1988592	1988736	144
0	1	"fixation"	1988788	1989013	225
0	1	"fixation"	1989060	1989170	110
…	…	…	…	…	…
0	1	"saccade"	2005110	2005126	16
0	1	"saccade"	2005128	2005138	10
0	1	"saccade"	2005288	2005345	57
0	1	"saccade"	2005347	2005356	9
0	1	"saccade"	2005359	2005365	6

trial_columns:
list (2 items)
- 'text_id'
- 'page_id'

What you have learned in this tutorial:#

saving your preprocesed data using Dataset.save_preprocessed()
load your preprocesed data using Dataset.load(preprocessed=True)
using custom directory names by specifying preprocessed_dirname
using other file formats than the default feather format by specifying extension

Saving and Loading Event Data#

What you will learn in this tutorial:#

Preparations#

Saving#

Loading#

What you have learned in this tutorial:#

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