:mod:`neuron_morphology.transforms.affine_transform`
====================================================

.. py:module:: neuron_morphology.transforms.affine_transform


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

Classes
~~~~~~~

.. autoapisummary::

   neuron_morphology.transforms.affine_transform.AffineTransform



Functions
~~~~~~~~~

.. autoapisummary::

   neuron_morphology.transforms.affine_transform.affine_from_transform_translation
   neuron_morphology.transforms.affine_transform.rotation_from_angle
   neuron_morphology.transforms.affine_transform.affine_from_translation
   neuron_morphology.transforms.affine_transform.affine_from_transform


.. py:class:: AffineTransform(affine: Optional[Any] = None)

   Bases: :class:`neuron_morphology.transforms.transform_base.TransformBase`

   Handles transformations to a pia/wm aligned coordinate frame.
















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   .. classmethod:: from_dict(cls, affine_dict: Dict[str, float])

      Create an AffineTransform from a dict with keys and values.


      :Parameters:

          **affine_dict: keys and values corresponding to the following**
              [[tvr_00 tvr_01 tvr_02 tvr_09]
               [tvr_03 tvr_04 tvr_05 tvr_10]
               [tvr_06 tvr_07 tvr_08 tvr_11]
               [0      0      0      1]]

      :Returns:

          AffineTransform object
              ..













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   .. classmethod:: from_list(cls, affine_list: List[float])

      Create an Affine Transform from a list


      :Parameters:

          **affine_list: list of tvr values corresponding to:**
              [[tvr_00 tvr_01 tvr_02 tvr_09]
               [tvr_03 tvr_04 tvr_05 tvr_10]
               [tvr_06 tvr_07 tvr_08 tvr_11]
               [0      0      0      1]]

      :Returns:

          AffineTransform object
              ..













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   .. method:: to_dict(self)

      Create dictionary defining the transformation.



      :Returns:

          Dict with keys and values corresponding to the following:
              [[tvr_00 tvr_01 tvr_02 tvr_09]
               [tvr_03 tvr_04 tvr_05 tvr_10]
               [tvr_06 tvr_07 tvr_08 tvr_11]
               [0      0      0      1]]













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   .. method:: to_list(self)

      Create a list defining the transformation.



      :Returns:

          List with values corresponding to the following:
              [[tvr_00 tvr_01 tvr_02 tvr_09]
               [tvr_03 tvr_04 tvr_05 tvr_10]
               [tvr_06 tvr_07 tvr_08 tvr_11]
               [0      0      0      1]]













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   .. method:: transform(self, vector: Any)

      Apply this transform to (3,) point or (n,3) array-like of points.


      :Parameters:

          **vector: a (3,) array-like point or a (n,3) array-like array**
              of points to be transformed

      :Returns:

          numpy.ndarray with same shape as input
              ..













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   .. method:: _get_scaling_factor(self)

      Calculate the scaling factor from the affine matrix.



      :Returns:

          Scaling factor: 3rd root of the determinant.
              ..













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   .. method:: transform_morphology(self, morphology: Morphology, clone: bool = False, scale_radius: bool = True)

      Apply this transform to all nodes in a morphology.


      :Parameters:

          **morphology: a Morphology loaded from an swc file**
              ..

          **clone: make a new object if True**
              ..

          **scale_radius: apply radius scaling if True**
              ..

      :Returns:

          A Morphology
              ..













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.. function:: affine_from_transform_translation(transform: Optional[Any] = None, translation: Optional[Any] = None, translate_first: bool = False)

   Create affine from linear transformation and translation.

   Affine transformation of vector x -> Ax + b in 3D:
   [A,       b
    0, 0, 0, 1]
   A is a 3x3 linear tranformation
   b is a 3x1 translation

   :Parameters:

       **transform: linear transformation (3, 3) array-like**
           ..

       **translation: linear translation (3,) array-like**
           ..

       **translate_first: apply the translation before the transform**
           ..

   :Returns:

       (4, 4) numpy.ndarray affine matrix
           ..













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.. function:: rotation_from_angle(angle: float, axis: int = 2)

   Create an affine matrix from a rotation about a specific axis.


   :Parameters:

       **angle: rotation angle in radians**
           ..

       **axis: axis to rotate about, 0=x, 1=y, 2=z (default z axis)**
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   :Returns:

       (3, 3) numpy.ndarray rotation matrix
           ..













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.. function:: affine_from_translation(translation: Any)

   Create an affine translation.


   :Parameters:

       **translation: array-like vector of x, y, and z translations**
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   :Returns:

       (4, 4) numpy.ndarray affine matrix
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.. function:: affine_from_transform(transform: Any)

   Create affine transformation.


   :Parameters:

       **transformation: (3, 3) row major array-like transformation**
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   :Returns:

       (4, 4) numpy.ndarray affine matrix
           ..













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