62 lines
1.9 KiB
ReStructuredText
62 lines
1.9 KiB
ReStructuredText
.. _minimal-working-example:
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Minimal Working Example
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=======================
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The following is a quick guide for creating and running a simple pipeline to extract Call metrics for daily and night epochs of one participant monitored on the US East coast.
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#. Make sure your database connection credentials in ``.env`` are correct. See step 1 of :ref:`Usage Section <db-configuration>`.
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#. Create at least one participant file ``p01`` under ``data/external/``. See step 2 of :ref:`Usage Section <db-configuration>`.
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#. Make sure your Conda (python) environment is active. See step 6 of :ref:`install-page`.
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#. Replace the contents of the ``Snakefile`` with the following snippet
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::
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configfile: "config.yaml"
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include: "rules/renv.snakefile"
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include: "rules/preprocessing.snakefile"
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include: "rules/features.snakefile"
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include: "rules/reports.snakefile"
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rule all:
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input:
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expand("data/processed/{pid}/call_{call_type}_{day_segment}.csv",
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pid=config["PIDS"],
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call_type=config["CALLS"]["TYPES"],
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day_segment = config["CALLS"]["DAY_SEGMENTS"]),
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#. Modify the following settings in the ``config.yaml`` file with the values shown below (leave all other settings as they are)
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::
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SENSORS: [calls]
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FITBIT_TABLE: []
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FITBIT_SENSORS: []
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PIDS: [p01]
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DAY_SEGMENTS: &day_segments
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[daily, night]
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TIMEZONE: &timezone
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America/New_York
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DATABASE_GROUP: &database_group
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MY_GROUP
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For more information on the ``calls`` sensor see :ref:`call-sensor-doc`
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#. Run the following command to execute RAPIDS
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::
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snakemake -j1
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#. Daily and night call metrics will be found in files under the ``data/processed/p01/`` directory.
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