[](http://badge.fury.io/py/element-event)
# DataJoint Element - Experimental trials
+ `element-event` features a DataJoint pipeline design for event, trial, and block management.
+ `element-event` is not a complete workflow by itself, but rather a modular design of tables and dependencies.
+ `element-event` can be flexibly attached to any DataJoint workflow.
+ See the [Element Event documentation](https://elements.datajoint.org/description/event/) for the background information and development timeline.
+ For more information on the DataJoint Elements project, please visit https://elements.datajoint.org. This work is supported by the National Institutes of Health.
## Element architecture
In diagram below, ***BehaviorRecording*** table starts immediately downstream from
***Session***. Recordings can be segmented into both trials, which are assumed to have
duration, and events, which may be instantaneous. Researchers may find one or both appropriate for their particular paradigm. A set of trials can be further organized into
blocks, representing a larger span of time. We provide an
[example workflow](https://github.com/datajoint/workflow-trial/) with a
[pipeline script](https://github.com/datajoint/workflow-trial/blob/main/workflow_trial/pipeline.py)
that models combining this Element with the corresponding
[Element-Session](https://github.com/datajoint/element-session).
### Trial & Event Schemas
## Installation
+ Install `element-event`
```
pip install element-event
```
+ Upgrade `element-event` previously installed with `pip`
```
pip install --upgrade element-event
```
<!---
+ Install `element-interface`
+ `element-interface` is a dependency of `element-event`, however it is not
contained within `requirements.txt`.
```
pip install "element-interface @ git+https://github.com/datajoint/element-interface"
```
-->
## Usage
### Element activation
To activate the `element-event`, one need to provide:
1. Schema names for the event or trial module
2. Upstream Session table: A set of keys identifying a recording session (see [
Element-Session](https://github.com/datajoint/element-session)).
3. Utility functions. See
[example definitions here](https://github.com/datajoint/workflow-trial/blob/main/workflow_trial/paths.py)
For more detail, check the docstring of the `element-event`:
```python
from element_event import event, trial
help(event.activate)
help(trial.activate)
```
### Element usage
+ See the
[workflow-calcium-imaging](https://github.com/datajoint/workflow-calcium-imaging),
[workflow-array-ephys](https://github.com/datajoint/workflow-array-ephys), and
[workflow-miniscope](https://github.com/datajoint/workflow-miniscope)
repositories for example usages of `element-event`.
## Citation
+ If your work uses DataJoint and DataJoint Elements, please cite the respective Research Resource Identifiers (RRIDs) and manuscripts.
+ DataJoint for Python or MATLAB
+ Yatsenko D, Reimer J, Ecker AS, Walker EY, Sinz F, Berens P, Hoenselaar A, Cotton RJ, Siapas AS, Tolias AS. DataJoint: managing big scientific data using MATLAB or Python. bioRxiv. 2015 Jan 1:031658. doi: https://doi.org/10.1101/031658
+ DataJoint ([RRID:SCR_014543](https://scicrunch.org/resolver/SCR_014543)) - DataJoint for `<Select Python or MATLAB>` (version `<Enter version number>`)
+ DataJoint Elements
+ Yatsenko D, Nguyen T, Shen S, Gunalan K, Turner CA, Guzman R, Sasaki M, Sitonic D, Reimer J, Walker EY, Tolias AS. DataJoint Elements: Data Workflows for Neurophysiology. bioRxiv. 2021 Jan 1. doi: https://doi.org/10.1101/2021.03.30.437358
+ DataJoint Elements ([RRID:SCR_021894](https://scicrunch.org/resolver/SCR_021894)) - Element Event (version `<Enter version number>`)
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"description": "[](http://badge.fury.io/py/element-event)\n\n# DataJoint Element - Experimental trials\n\n+ `element-event` features a DataJoint pipeline design for event, trial, and block management. \n\n+ `element-event` is not a complete workflow by itself, but rather a modular design of tables and dependencies. \n\n+ `element-event` can be flexibly attached to any DataJoint workflow.\n\n+ See the [Element Event documentation](https://elements.datajoint.org/description/event/) for the background information and development timeline.\n\n+ For more information on the DataJoint Elements project, please visit https://elements.datajoint.org. This work is supported by the National Institutes of Health.\n\n## Element architecture\n\nIn diagram below, ***BehaviorRecording*** table starts immediately downstream from\n***Session***. Recordings can be segmented into both trials, which are assumed to have \nduration, and events, which may be instantaneous. Researchers may find one or both appropriate for their particular paradigm. A set of trials can be further organized into\nblocks, representing a larger span of time. We provide an\n[example workflow](https://github.com/datajoint/workflow-trial/) with a\n[pipeline script](https://github.com/datajoint/workflow-trial/blob/main/workflow_trial/pipeline.py)\nthat models combining this Element with the corresponding \n[Element-Session](https://github.com/datajoint/element-session).\n\n### Trial & Event Schemas\n\n\n\n## Installation\n\n+ Install `element-event`\n ```\n pip install element-event\n ```\n\n+ Upgrade `element-event` previously installed with `pip`\n ```\n pip install --upgrade element-event\n ```\n\n<!---\n+ Install `element-interface`\n\n + `element-interface` is a dependency of `element-event`, however it is not \n contained within `requirements.txt`.\n\n ```\n pip install \"element-interface @ git+https://github.com/datajoint/element-interface\"\n ```\n-->\n\n## Usage\n\n### Element activation\n\nTo activate the `element-event`, one need to provide:\n\n1. Schema names for the event or trial module\n2. Upstream Session table: A set of keys identifying a recording session (see [\nElement-Session](https://github.com/datajoint/element-session)).\n3. Utility functions. See \n[example definitions here](https://github.com/datajoint/workflow-trial/blob/main/workflow_trial/paths.py)\n\nFor more detail, check the docstring of the `element-event`:\n\n```python\nfrom element_event import event, trial\n\nhelp(event.activate)\nhelp(trial.activate)\n```\n\n### Element usage\n\n+ See the \n[workflow-calcium-imaging](https://github.com/datajoint/workflow-calcium-imaging), \n[workflow-array-ephys](https://github.com/datajoint/workflow-array-ephys), and \n[workflow-miniscope](https://github.com/datajoint/workflow-miniscope) \nrepositories for example usages of `element-event`.\n\n## Citation\n\n+ If your work uses DataJoint and DataJoint Elements, please cite the respective Research Resource Identifiers (RRIDs) and manuscripts.\n\n+ DataJoint for Python or MATLAB\n + Yatsenko D, Reimer J, Ecker AS, Walker EY, Sinz F, Berens P, Hoenselaar A, Cotton RJ, Siapas AS, Tolias AS. DataJoint: managing big scientific data using MATLAB or Python. bioRxiv. 2015 Jan 1:031658. doi: https://doi.org/10.1101/031658\n\n + DataJoint ([RRID:SCR_014543](https://scicrunch.org/resolver/SCR_014543)) - DataJoint for `<Select Python or MATLAB>` (version `<Enter version number>`)\n\n+ DataJoint Elements\n + Yatsenko D, Nguyen T, Shen S, Gunalan K, Turner CA, Guzman R, Sasaki M, Sitonic D, Reimer J, Walker EY, Tolias AS. DataJoint Elements: Data Workflows for Neurophysiology. bioRxiv. 2021 Jan 1. doi: https://doi.org/10.1101/2021.03.30.437358\n\n + DataJoint Elements ([RRID:SCR_021894](https://scicrunch.org/resolver/SCR_021894)) - Element Event (version `<Enter version number>`)\n\n",
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