skneuromsi.core.dresult.result module
Utilities to represents a multisensory integration result as a multidimensional array.
- skneuromsi.core.ndresult.result.modes_to_data_array(modes_dict, dtype)[source]
Convert a dictionary of modes to an xarray.DataArray.
- Parameters:
modes_dict (dict) – A dictionary of modes and their corresponding coordinates.
dtype (numpy.dtype, optional) – The data type of the resulting xarray.DataArray.
- Returns:
The modes as an xarray.DataArray.
- Return type:
xarray.DataArray
- class skneuromsi.core.ndresult.result.NDResult(*, mname, mtype, output_mode, nmap, nddata, time_range, position_range, time_res, position_res, causes, run_parameters, extra, ensure_dtype=None)[source]
Bases:
objectRepresents a multisensory integration result.
- Parameters:
mname (str) – The name of the model.
mtype (str) – The type of the model.
output_mode (str) – The output mode of the model.
nmap (dict) – A dictionary mapping modes to their corresponding values.
nddata (xarray.DataArray or dict) – The multidimensional data as an xarray.DataArray.
time_range (tuple) – The range of time values.
position_range (tuple) – The range of position values.
time_res (float) – The resolution of time values.
position_res (float) – The resolution of position values.
causes (int, float or None) – The number of causes in the result.
run_parameters (dict) – The parameters used for running the model.
extra (dict) – Extra information associated with the result.
ensure_dtypes (numpy.dtype, optional (default=infer)) – Force all data types to be assigned to this type. This only applies to parameters that accept the dtype message If None, the data types are inferred.
- classmethod from_modes_dict(*, modes_dict, ensure_dtype=None, **kwargs)[source]
Create an NDResult object from a dictionary of modes.
- Parameters:
modes_dict (dict) – A dictionary mapping modes to their corresponding values.
ensure_dtype (numpy.dtype, optional) – Force all data types to be assigned to this type. This only applies to parameters that accept the dtype message If None, the data types are inferred.
**kwargs – Additional keyword arguments to pass to the NDResult constructor.
- Returns:
The NDResult object.
- Return type:
- property mname
The name of the model.
- Type:
str
- property mtype
The type of the model.
- Type:
str
- property output_mode
The output mode of the model.
- Type:
str
- property dims
The dimensions of the result data.
- Type:
list
- property nmap_
A copy of the nmap dictionary.
- Type:
dict
- property time_range
The range of time values.
- Type:
tuple
- property position_range
The range of position values.
- Type:
tuple
- property time_res
The resolution of time values.
- Type:
float
- property position_res
The resolution of position values.
- Type:
float
- property causes_
The number of causes in the result.
- Type:
int
- property modes_
The modes of the result data.
- Type:
numpy.ndarray
- property times_
The time values of the result data.
- Type:
numpy.ndarray
- property positions_
The position values of the result data.
- Type:
numpy.ndarray
- property positions_coordinates_
The position coordinates of the result data.
- Type:
numpy.ndarray
- property pcoords_
The position coordinates of the result data.
- Type:
numpy.ndarray
- property plot
Plot accessor for the NDResult object.
- Type:
- property stats
Stats accessor for the NDResult object.
- Type:
- get_modes(*, include=None)[source]
Get the modes of the result data as a DataFrame.
- Parameters:
include (str, int, float, numpy.number, Iterable, or None, optional) – The modes to include in the DataFrame. If None, all modes are included.
- Returns:
The modes as a DataFrame.
- Return type:
pandas.DataFrame
- get_times(*, include=None)[source]
Get the time values of the result data as a DataFrame.
- Parameters:
include (str, int, float, numpy.number, Iterable, or None, optional) – The time values to include in the DataFrame. If None, all time values are included.
- Returns:
The time values as a DataFrame.
- Return type:
pandas.DataFrame
- get_positions(*, include=None)[source]
Get the position values of the result data as a DataFrame.
- Parameters:
include (str, int, float, numpy.number, Iterable, or None, optional) – The position values to include in the DataFrame. If None, all position values are included.
- Returns:
The position values as a DataFrame.
- Return type:
pandas.DataFrame
- get_positions_coordinates(*, include=None)[source]
Get the position coordinates of the result data as a DataFrame.
- Parameters:
include (str, int, float, numpy.number, Iterable, or None, optional) – The position coordinates to include in the DataFrame. If None, all position coordinates are included.
- Returns:
The position coordinates as a DataFrame.
- Return type:
pandas.DataFrame
- get_pcoords(*, include=None)
Get the position coordinates of the result data as a DataFrame.
- Parameters:
include (str, int, float, numpy.number, Iterable, or None, optional) – The position coordinates to include in the DataFrame. If None, all position coordinates are included.
- Returns:
The position coordinates as a DataFrame.
- Return type:
pandas.DataFrame
- to_dict()[source]
Convert the NDResult object to a dictionary.
- Returns:
The NDResult object as a dictionary.
- Return type:
dict
- to_ndr(path_or_stream, metadata=None, **kwargs)[source]
Store the NDResult object in NMSI Result (NDR) format.
- Parameters:
path_or_stream (str or file-like object) – The path or file-like object to store the NDR data.
metadata (dict, optional) – Additional metadata to include in the NDR data.
**kwargs – Additional keyword arguments to pass to the NDR storage function.
- astype(dtype, *, attributes=None)[source]
Return a copy of the NDResult object with the specified data type.
- Parameters:
dtype (data type) – The data type to convert the NDResult object to.
attributes (list of str, optional) – The names of the attributes to convert. If None, all attributes
- Returns:
The NDResult object with the specified data type.
- Return type:
- deep_dtypes(*, max_deep=2, memory_usage=False)[source]
Returns the deep data types of the object.
- Parameters:
max_deep (int, optional) – The maximum depth to traverse the object. Defaults to 2.
memory_usage (bool, optional) – If True, return the memory usage of the object. Defaults to False.
- Returns:
The deep data types of the object.
- Return type:
dict