dacapo.experiments.datasplits.datasets.arrays.intensity_array
=============================================================

.. py:module:: dacapo.experiments.datasplits.datasets.arrays.intensity_array


Classes
-------

.. autoapisummary::

   dacapo.experiments.datasplits.datasets.arrays.intensity_array.IntensitiesArray


Module Contents
---------------

.. py:class:: IntensitiesArray(array_config)



   This is wrapper another array that will normalize intensities to
   the range (0, 1) and convert to float32. Use this if you have your
   intensities stored as uint8 or similar and want your model to
   have floats as input.

   .. attribute:: array_config

      The config object for the array

      :type: ArrayConfig

   .. attribute:: min

      The minimum intensity value in the array

      :type: float

   .. attribute:: max

      The maximum intensity value in the array

      :type: float

   .. method:: __getitem__

      Returns the intensities normalized to the range (0, 1)

   .. rubric:: Notes

   The array_config must be an ArrayConfig object.
   The min and max values are used to normalize the intensities.
   All intensities are converted to float32.


   .. py:attribute:: name


   .. py:property:: attrs
      Returns the attributes of the source array

      :returns: The attributes of the source array
      :rtype: dict

      :raises ValueError: If the attributes is not a dictionary

      .. rubric:: Examples

      >>> intensities_array.attrs
      {'resolution': (1.0, 1.0, 1.0), 'unit': 'micrometer'}

      .. rubric:: Notes

      The attributes are the same as the source array


   .. py:property:: axes
      Returns the axes of the source array

      :returns: The axes of the source array
      :rtype: str

      :raises ValueError: If the axes is not a string

      .. rubric:: Examples

      >>> intensities_array.axes
      'zyx'

      .. rubric:: Notes

      The axes are the same as the source array


   .. py:property:: dims
      :type: int

      Returns the dimensions of the source array

      :returns: The dimensions of the source array
      :rtype: int

      :raises ValueError: If the dimensions is not an integer

      .. rubric:: Examples

      >>> intensities_array.dims
      3

      .. rubric:: Notes

      The dimensions are the same as the source array


   .. py:property:: voxel_size
      :type: funlib.geometry.Coordinate

      Returns the voxel size of the source array

      :returns: The voxel size of the source array
      :rtype: Coordinate

      :raises ValueError: If the voxel size is not a Coordinate object

      .. rubric:: Examples

      >>> intensities_array.voxel_size
      Coordinate(x=1.0, y=1.0, z=1.0)

      .. rubric:: Notes

      The voxel size is the same as the source array


   .. py:property:: roi
      :type: funlib.geometry.Roi

      Returns the region of interest of the source array

      :returns: The region of interest of the source array
      :rtype: Roi

      :raises ValueError: If the region of interest is not a Roi object

      .. rubric:: Examples

      >>> intensities_array.roi
      Roi(offset=(0, 0, 0), shape=(10, 20, 30))

      .. rubric:: Notes

      The region of interest is the same as the source array


   .. py:property:: writable
      :type: bool

      Returns whether the array is writable

      :returns: Whether the array is writable
      :rtype: bool

      :raises ValueError: If the array is not writable

      .. rubric:: Examples

      >>> intensities_array.writable
      False

      .. rubric:: Notes

      The array is not writable because it is a virtual array created by modifying another array on demand.


   .. py:property:: dtype
      Returns the data type of the array

      :returns: The data type of the array
      :rtype: type

      :raises ValueError: If the data type is not a type

      .. rubric:: Examples

      >>> intensities_array.dtype
      numpy.float32

      .. rubric:: Notes

      The data type is always float32


   .. py:property:: num_channels
      :type: int

      Returns the number of channels in the source array

      :returns: The number of channels in the source array
      :rtype: int

      :raises ValueError: If the number of channels is not an integer

      .. rubric:: Examples

      >>> intensities_array.num_channels
      3

      .. rubric:: Notes

      The number of channels is the same as the source array


   .. py:property:: data
      Returns the data of the source array

      :returns: The data of the source array
      :rtype: np.ndarray

      :raises ValueError: If the data is not a numpy array

      .. rubric:: Examples

      >>> intensities_array.data
      array([[[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]], [[0.7, 0.8, 0.9], [1.0, 1.1, 1.2]]])

      .. rubric:: Notes

      The data is the same as the source array