goatpy.pseudo_image
===================

.. py:module:: goatpy.pseudo_image


Functions
---------

.. autoapisummary::

   goatpy.pseudo_image.Add_Pseudo_Image
   goatpy.pseudo_image.add_uns
   goatpy.pseudo_image.generate_random_colors
   goatpy.pseudo_image.map_categories_to_colors
   goatpy.pseudo_image.generate_continuous_bins
   goatpy.pseudo_image.create_image_from_data


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

.. py:function:: Add_Pseudo_Image(sdata, image_ident, tables='maldi_adata', library_id='Spatial', convert_to_int=True, cmap=None, is_continous=False, img_upscaling=1)

.. py:function:: add_uns(adata, ident, library_id, cmap=None, data_type='categorical', img_upscaling=1)

.. py:function:: generate_random_colors(categories)

   Generate a random color for each category.

   Parameters:
   - categories: List or array of unique category values.

   Returns:
   - A dictionary mapping categories to colors.


.. py:function:: map_categories_to_colors(categories, color_map)

   Map category values to colors using the color map.

   Parameters:
   - categories: Array of category values.
   - color_map: Dictionary mapping continents to colors.

   Returns:
   - An array of RGB colors.


.. py:function:: generate_continuous_bins(values)

   Generate bins for continuous values.

   Parameters:
   - values: Array of continuous values.

   Returns:
   - Binned values as integers.


.. py:function:: create_image_from_data(coords_array, category_values, color_map)

   Create an image from x, y coordinates and associated categorical values.

   Parameters:
   - coords_array: 2D NumPy array with shape (n, 2) where each row is [x, y].
   - category_values: Array of categorical values corresponding to each coordinate.
   - color_map: Dictionary mapping categories to RGB colors.

   Returns:
   - PIL.Image object.