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+# ndx-acquisition-module
+
+[](https://gitlab.com/fleischmann-lab/ndx/ndx-acquisition-module/-/commits/main)
+[](LICENSE.txt)
+
+
+
+[](https://gitlab.com/fleischmann-lab/ndx/ndx-acquisition-module/-/releases)
+[](https://pypi.org/pypi/ndx-acquisition-module)
+[](https://anaconda.org/FleischmannLab/ndx-acquisition-module)
+
+This extension is used to allow adding modules in `nwbfile.acquisition`, similarly to how `nwbfile.processing` allows adding modules.
+
+More specifically, this allows creating a module that has `TimeSeries` and `DynamicTable` objects, then users can add this module.
+
+This is in alpha development stages. Please use with discretion.
+
+## Installation
+
+You can install via `pip`:
+
+```bash
+pip install ndx-acquisition-module
+```
+
+Or `conda`:
+
+```bash
+conda install -c fleischmannlab ndx-acquisition-module
+```
+
+Or directly from the `git` repository:
+
+```bash
+pip install git+https://gitlab.com/fleischmann-lab/ndx/ndx-acquisition-module
+```
+
+## Usage
+
+### Main usage
+
+Here's a short example to create the module, add objects into it then add to acquisition
+
+```python
+from ndx_acquisition_module import AcquisitionModule
+
+mod = AcquisitionModule(name="raw_mod", description="raw acq module")
+
+# Add data objects to created AcquisitionModule
+mod.add(time_series) # add time series
+mod.add(dynamic_table) # add dynamic table
+
+# Add AcquisitionModule to nwbfile.acquisition
+nwbfile.add_acquisition(mod)
+```
+
+### Full example
+
+Here's a full example that you can copy and paste in a script/notebook and run. A `test.nwb` file would be created.
+
+Expand to see full example script
+
+```python
+from datetime import datetime
+
+import numpy as np
+from dateutil import tz
+from hdmf.common import DynamicTable, VectorData
+from ndx_acquisition_module import AcquisitionModule
+
+from pynwb import NWBHDF5IO, NWBFile, TimeSeries
+
+# Create an example NWBFile
+nwbfile = NWBFile(
+ session_description="test session description",
+ identifier="unique_identifier",
+ session_start_time=datetime(2012, 2, 21, tzinfo=tz.gettz("US/Pacific")),
+)
+
+# Create time series
+ts = TimeSeries(
+ name="choice_series",
+ description="raw choice series",
+ data=np.random.randint(4, size=100),
+ timestamps=(np.arange(100).astype("float") + 2) / 30,
+ unit="-",
+)
+
+# Create dynamic table
+tbl = DynamicTable(
+ name="lookup_table",
+ description="lookup table for `choice_series`",
+ columns=[
+ VectorData(
+ name="lookup_id", description="ID to look up", data=[0, 1, 2, 3]
+ ),
+ VectorData(
+ name="lookup_name",
+ description="name of ID",
+ data=["water", "earth", "fire", "air"],
+ ),
+ ],
+)
+
+# Create AcquisitionModule to store these objects
+mod = AcquisitionModule(name="raw_mod", description="raw acq module")
+
+# Add data objects to created AcquisitionModule
+mod.add(ts) # add time series
+mod.add(tbl) # add dynamic table
+
+# Add AcquisitionModule to nwbfile.acquisition
+nwbfile.add_acquisition(mod)
+
+# Write the file to disk
+filename = "test.nwb"
+with NWBHDF5IO(path=filename, mode="w") as io:
+ io.write(nwbfile)
+
+```
+
+