def add_scratch(self, **kwargs):
'''Add data to the scratch space'''
data, name, notes = getargs('data', 'name', 'notes', kwargs)
if isinstance(data, (np.ndarray, pd.DataFrame, list, tuple)):
if name is None:
raise ValueError('please provide a name for scratch data')
if isinstance(data, pd.DataFrame):
table_description = getargs('table_description', kwargs)
data = DynamicTable.from_dataframe(
df=data, name=name, table_description=table_description)
if notes is not None:
warn(
'Notes argument is ignored when adding a pandas DataFrame to scratch'
)
else:
data = ScratchData(name=name, data=data, notes=notes)
else:
if notes is not None:
warn(
'Notes argument is ignored when adding an NWBContainer to scratch'
)
if name is not None:
warn(
'Name argument is ignored when adding an NWBContainer to scratch'
)
self._add_scratch(data)
def add_scratch(self, **kwargs):
'''Add data to the scratch space.'''
data, name, description = getargs('data', 'name', 'description',
kwargs)
if isinstance(
data,
(str, int, float, bytes, np.ndarray, list, tuple, pd.DataFrame)):
if name is None:
msg = (
'A name is required for NWBFile.add_scratch when adding a scalar, numpy.ndarray, '
'list, tuple, or pandas.DataFrame as scratch data.')
raise ValueError(msg)
if description is None:
msg = (
'A description is required for NWBFile.add_scratch when adding a scalar, numpy.ndarray, '
'list, tuple, or pandas.DataFrame as scratch data.')
raise ValueError(msg)
if isinstance(data, pd.DataFrame):
data = DynamicTable.from_dataframe(
df=data, name=name, table_description=description)
else:
data = ScratchData(name=name,
data=data,
description=description)
else:
if name is not None:
warn(
'The name argument is ignored when adding an NWBContainer, ScratchData, or '
'DynamicTable to scratch.')
if description is not None:
warn(
'The description argument is ignored when adding an NWBContainer, ScratchData, or '
'DynamicTable to scratch.')
return self._add_scratch(data)
def add_scratch(self, **kwargs):
'''Add data to the scratch space'''
data, name, notes, table_description, description = getargs('data', 'name', 'notes', 'table_description',
'description', kwargs)
if notes is not None or table_description != '':
warn('Use of the `notes` or `table_description` argument will be removed in a future version of PyNWB. '
'Use the `description` argument instead.', PendingDeprecationWarning)
if description is not None:
raise ValueError('Cannot call add_scratch with (notes or table_description) and description')
if isinstance(data, (str, int, float, bytes, np.ndarray, list, tuple, pd.DataFrame)):
if name is None:
msg = ('A name is required for NWBFile.add_scratch when adding a scalar, numpy.ndarray, '
'list, tuple, or pandas.DataFrame as scratch data.')
raise ValueError(msg)
if isinstance(data, pd.DataFrame):
if table_description != '':
description = table_description # remove after deprecation
if description is None:
msg = ('A description is required for NWBFile.add_scratch when adding a scalar, numpy.ndarray, '
'list, tuple, or pandas.DataFrame as scratch data.')
raise ValueError(msg)
data = DynamicTable.from_dataframe(df=data, name=name, table_description=description)
else:
if notes is not None:
description = notes # remove after deprecation
if description is None:
msg = ('A description is required for NWBFile.add_scratch when adding a scalar, numpy.ndarray, '
'list, tuple, or pandas.DataFrame as scratch data.')
raise ValueError(msg)
data = ScratchData(name=name, data=data, description=description)
else:
if name is not None:
warn('The name argument is ignored when adding an NWBContainer, ScratchData, or '
'DynamicTable to scratch.')
if description is not None:
warn('The description argument is ignored when adding an NWBContainer, ScratchData, or '
'DynamicTable to scratch.')
return self._add_scratch(data)
def setUpContainer(self):
return DynamicTable.from_dataframe(
pd.DataFrame({
'a': [[1, 2, 3], [1, 2, 3], [1, 2, 3]],
'b': ['4', '5', '6']
}), 'test_table')
df = table.to_dataframe()
###############################################################################
# .. note::
#
# Changes to the ``DataFrame`` will not be saved in the ``DynamicTable``.
###############################################################################
# Converting the table from a pandas ``DataFrame``
# ------------------------------------------------
# If your data is already in a :py:class:`~pandas.DataFrame`, you can convert the
# ``DataFrame`` to a :py:class:`~hdmf.common.table.DynamicTable` using the class method
# :py:meth:`DynamicTable.from_dataframe <hdmf.common.table.DynamicTable.from_dataframe>`.
table_from_df = DynamicTable.from_dataframe(
name='my_table',
df=df,
)
###############################################################################
# Accessing elements
# ------------------
# To access an element in the i-th row in the column with name "col_name" in a
# :py:class:`~hdmf.common.table.DynamicTable`, use square brackets notation:
# ``table[i, col_name]``. You can also use a tuple of row index and column
# name within the square brackets.
table[0, 'col1'] # returns 1
table[(0, 'col1')] # returns 1
###############################################################################
# If the column is a ragged array, instead of a single value being returned,
def create_module(self):
waveform_module = ProcessingModule(name=self.name, description=self.description)
waveform_module.add_container(
DynamicTable.from_dataframe(self.waveform_analysis.transpose(), name=self.name))
return waveform_module
