Merge branch 'dev' into mask_conversion

docs/gallery/general/file.py

@@ -157,7 +157,6 @@
 # for the column and a description of what the column stores. You do not need to supply data
 # type, as this will inferred.
 # Once all columns have been added, trial data can be populated using :py:func:`~pynwb.file.NWBFile.add_trial`.
-# This method takes a dict with keys that correspond to column names.
 #
 # Lets add an additional column and some trial data.
 
@@ -177,22 +176,21 @@
 # and :py:func:`~pynwb.file.NWBFile.add_unit_column`. These methods work like the methods for adding
 # trials described :ref:`above <basic_trials>`
 #
-# By default, NWBFile only requires a unique identifier for each unit. Additional columns
-# can be added using :py:func:`~pynwb.file.NWBFile.add_unit_column`. Like
+# By default, NWBFile only requires a unique identifier for each unit. Optional values for each unit
+# are: `spike_times`, `electrodes`, `electrode_group`, `waveform_mean`, and `waveform_sd`.
+# Additional columns can be added using :py:func:`~pynwb.file.NWBFile.add_unit_column`. Like
 # :py:func:`~pynwb.file.NWBFile.add_trial_column`, this method also takes a name
 # for the column, a description of what the column stores and does not need a data type.
 # Once all columns have been added, unit data can be populated using :py:func:`~pynwb.file.NWBFile.add_unit`.
-# Again, like :py:func:`~pynwb.file.NWBFile.add_trial_column`, this method takes a dict with keys that correspond
-# to column names.
 #
 # Lets specify some unit metadata and then add some units
 
 nwbfile.add_unit_column('location', 'the anatomical location of this unit')
 nwbfile.add_unit_column('quality', 'the quality for the inference of this unit')
 
-nwbfile.add_unit(id=1, location='CA1', quality=0.95)
-nwbfile.add_unit(id=2, location='CA3', quality=0.85)
-nwbfile.add_unit(id=3, location='CA1', quality=0.90)
+nwbfile.add_unit(id=1, spike_times=[2.2, 3.0, 4.5], location='CA1', quality=0.95)
+nwbfile.add_unit(id=2, spike_times=[2.2, 3.0], location='CA3', quality=0.85)
+nwbfile.add_unit(id=3, spike_times=[1.2, 2.3, 3.3, 4.5], location='CA1', quality=0.90)
 
 ####################
 # .. _units_fields_ref:

requirements-dev.txt

@@ -16,5 +16,5 @@ six==1.11.0
 tox==3.0.0
 traceback2==1.4.0
 unittest2==1.1.0
-urllib3==1.22
+urllib3==1.23
 virtualenv==15.2.0

requirements.txt

@@ -7,5 +7,5 @@ python-dateutil==2.7.2
 requests==2.20.0
 ruamel.yaml==0.15.37
 six==1.11.0
-urllib3==1.22
+urllib3==1.23
 pandas==0.23.4

src/pynwb/data/nwb.ecephys.yaml

@@ -73,6 +73,25 @@ groups:
     - - null
       - null
       - null
+  - name: timestamps
+    dtype: float64
+    doc: 'Timestamps for samples stored in data.COMMENT: Timestamps here have all
+      been corrected to the common experiment master-clock. Time is stored as seconds
+      and all timestamps are relative to experiment start time. This is added here so
+      that the timestamps is required for SpikeEventTimes.'
+    attributes:
+    - name: interval
+      dtype: int32
+      doc: Value is '1'
+      value: 1
+    - name: unit
+      dtype: text
+      doc: Value is 'Seconds'
+      value: Seconds
+    dims:
+    - num_times
+    shape:
+    - null
 - neurodata_type_def: ClusterWaveforms
   neurodata_type_inc: NWBDataInterface
   doc: 'The mean waveform shape, including standard deviation, of the different clusters.

src/pynwb/data/nwb.file.yaml

@@ -277,6 +277,10 @@ groups:
         dtype: text
         doc: Age of subject
         quantity: '?'
+      - name: date_of_birth
+        dtype: isodatetime
+        doc: can be supplied instead of age
+        quantity: '?'
       - name: description
         dtype: text
         doc: Description of subject and where subject came from (e.g., breeder, if

src/pynwb/data/nwb.misc.yaml

@@ -111,6 +111,86 @@ groups:
     - num_times
     shape:
     - null
+- neurodata_type_def: DecompositionSeries
+  neurodata_type_inc: TimeSeries
+  doc: Holds spectral analysis of a timeseries. For instance of LFP or a speech signal
+  datasets:
+  - name: data
+    dtype: float
+    doc: The data goes here
+    shape:
+    - null
+    - null
+    - null
+    dims:
+    - num_times
+    - num_channels
+    - num_bands
+  - name: metric
+    dtype: text
+    doc: 'recommended: phase, amplitude, power'
+  links:
+  - name: source_timeseries
+    doc: HDF5 link to TimesSeries that this data was calculated from. Metadata
+      about electrodes and their position can be read from that ElectricalSeries so
+      it's not necessary to store that information here
+    target_type: TimeSeries
+  groups:
+  - neurodata_type_inc: DynamicTable
+    name: bands
+    doc: A table for describing the bands that this series was generated from. There
+         should be one row in this table for each band
+    datasets:
+    - neurodata_type_inc: VectorData
+      name: band_name
+      dtype: text
+      doc: the name of the band e.g. theta
+      attributes:
+      - name: description
+        dtype: text
+        doc: value is 'the name of the band e.g. theta'
+        value: the name of the band e.g. theta
+    - neurodata_type_inc: VectorData
+      name: band_limits
+      dtype: float
+      shape:
+      - null
+      - 2
+      dims:
+      - num_bands
+      - low, high
+      doc: Low and high limit of each band in Hz. If it is a Gaussian filter, use 2 SD on either side of the center
+      attributes:
+      - name: description
+        dtype: text
+        doc: value is 'Low and high limit of each band in Hz. If it is a Gaussian filter, use 2 SD on either side of the center'
+        value: Low and high limit of each band in Hz. If it is a Gaussian filter, use 2 SD on either side of the center
+    - neurodata_type_inc: VectorData
+      name: band_mean
+      dtype: float
+      shape:
+      - null
+      dims:
+      - num_bands
+      doc: The mean Gaussian filters in Hz
+      attributes:
+      - name: description
+        dtype: text
+        doc: The mean Gaussian filters in Hz
+        value: The mean Gaussian filters in Hz
+    - neurodata_type_inc: VectorData
+      name: band_stdev
+      dtype: float
+      shape:
+      - null
+      dims:
+      - num_bands
+      doc: The standard devaition of Gaussian filters in Hz
+      attributes:
+      - name: description
+        dtype: text
+        doc: The standard devaition of Gaussian filters in Hz
+        value: The standard devaition of Gaussian filters in Hz
 - neurodata_type_def: Units
   neurodata_type_inc: DynamicTable
   doc: Data about spiking units. Event times of observed units (e.g. cell, synapse, etc.)
@@ -127,9 +207,25 @@ groups:
     quantity: '?'
   - neurodata_type_inc: VectorData
     name: spike_times
+    dtype: double
     doc: the spike times for each unit
     quantity: '?'
-  - neurodata_type_inc: DynamicTableRegion
+  - neurodata_type_inc: VectorIndex
+    name: obs_intervals_index
+    doc: the index into the obs_intervals dataset
+    quantity: '?'
+  - neurodata_type_inc: VectorData
+    name: obs_intervals
+    doc: the observation intervals for each unit
+    quantity: '?'
+    dtype: double
+    dims:
+    - num_intervals
+    - start|end
+    shape:
+    - null
+    - 2
+  - neurodata_type_inc: VectorIndex
     name: electrodes_index
     doc: the index into electrodes
     quantity: '?'

src/pynwb/data/nwb.namespace.yaml

@@ -24,4 +24,4 @@ namespaces:
   - source: nwb.ogen.yaml
   - source: nwb.ophys.yaml
   - source: nwb.retinotopy.yaml
-  version: 1.2.0
+  version: 2.0.0b

src/pynwb/ecephys.py

@@ -8,6 +8,7 @@
 from .base import TimeSeries, _default_resolution, _default_conversion
 from .core import NWBContainer, NWBDataInterface, MultiContainerInterface, DynamicTableRegion
 from .device import Device
+from .misc import DecompositionSeries
 
 
 @register_class('ElectrodeGroup', CORE_NAMESPACE)
@@ -281,13 +282,18 @@ class LFP(MultiContainerInterface):
     ElectricalSeries description or comments field.
     """
 
-    __clsconf__ = {
-        'attr': 'electrical_series',
-        'type': ElectricalSeries,
-        'add': 'add_electrical_series',
-        'get': 'get_electrical_series',
-        'create': 'create_electrical_series',
-    }
+    __clsconf__ = [
+        {'attr': 'electrical_series',
+         'type': ElectricalSeries,
+         'add': 'add_electrical_series',
+         'get': 'get_electrical_series',
+         'create': 'create_electrical_series'},
+
+        {'attr': 'decomposition_series',
+         'type': DecompositionSeries,
+         'add': 'add_decomposition_series',
+         'get': 'get_decomposition_series',
+         'create': 'create_decomposition_series'}]
 
     __help = ("LFP data from one or more channels. Filter properties "
               "should be noted in the ElectricalSeries")

src/pynwb/file.py

@@ -45,6 +45,7 @@ class Subject(NWBContainer):
         'species',
         'subject_id',
         'weight',
+        'date_of_birth'
     )
 
     @docval({'name': 'age', 'type': str, 'doc': 'the age of the subject', 'default': None},
@@ -53,7 +54,9 @@ class Subject(NWBContainer):
             {'name': 'sex', 'type': str, 'doc': 'the sex of the subject', 'default': None},
             {'name': 'species', 'type': str, 'doc': 'the species of the subject', 'default': None},
             {'name': 'subject_id', 'type': str, 'doc': 'a unique identifier for the subject', 'default': None},
-            {'name': 'weight', 'type': str, 'doc': 'the weight of the subject', 'default': None})
+            {'name': 'weight', 'type': str, 'doc': 'the weight of the subject', 'default': None},
+            {'name': 'date_of_birth', 'type': datetime, 'default': None,
+             'doc': 'datetime of date of birth. May be supplied instead of age.'})
     def __init__(self, **kwargs):
         kwargs['name'] = 'subject'
         pargs, pkwargs = fmt_docval_args(super(Subject, self).__init__, kwargs)
@@ -65,6 +68,11 @@ def __init__(self, **kwargs):
         self.species = getargs('species', kwargs)
         self.subject_id = getargs('subject_id', kwargs)
         self.weight = getargs('weight', kwargs)
+        date_of_birth = getargs('date_of_birth', kwargs)
+        if date_of_birth and date_of_birth.tzinfo is None:
+            self.date_of_birth = _add_missing_timezone(date_of_birth)
+        else:
+            self.date_of_birth = date_of_birth
 
 
 @register_class('NWBFile', CORE_NAMESPACE)