# Path: retina/input/image2d.py
# def image2Dfactory(input_type):
#     # I think this implementation will find only the classes defined in this
#     # file
#     all_image2d_cls = Image2D.__subclasses__()
#     all_image2d_names = [cls.__name__ for cls in all_image2d_cls]
#     try:
#         image2d_cls = all_image2d_cls[all_image2d_names.index(input_type)]
#     except ValueError:
#         print('Invalid Image2D subclass name: {}'.format(input_type))
#         print('Valid names: {}'.format(all_image2d_names))
#         return None
# 
#     return image2d_cls
# 
# Path: retina/screen/map/mapimpl.py
# def pointmapfactory(map_type):
#     # I think this implementation will find only the classes defined in this
#     # file
#     all_pointmap_cls = PointMap.__subclasses__()
#     all_pointmap_names = [cls.__name__ for cls in all_pointmap_cls]
#     try:
#         pointmap_cls = all_pointmap_cls[all_pointmap_names.index(map_type)]
#     except ValueError:
#         print('Invalid PointMap subclass name:{}'.format(map_type))
#         return None
#     return pointmap_cls
# 
# Path: retina/screen/transform/imagetransform.py
# class ImageTransform(SignalTransform):
#     def __init__(self, original_grid, new_grid):
#         """
#         :param original_grid: list of 2 1D arrays of original coordinates
#                               in strictly ascending order
#         :param new_grid: list of 2 arrays of new coordinates
#         """
#         self.ogrid = original_grid
#         self.ngrid = new_grid
# 
#     def interpolate(self, images):
#         new_images = np.empty(
#             (images.shape[0],)+ self.ngrid[0].shape, images.dtype)
#         for i, image in enumerate(images):
#             new_images[i] = self.interpolate_individual(image)
#         return new_images
# 
#     def interpolate_individual(self, image):
#         # unpacking
#         ogridx, ogridy = self.ogrid
#         ngridx, ngridy = self.ngrid
# 
#         f = RectBivariateSpline(ogridy, ogridx, image, kx=1, ky=1)
#         return f.ev(ngridy.flatten(), ngridx.flatten()).reshape(ngridx.shape)


import os
import contextlib
import numpy as np
        import matplotlib
        import matplotlib.pyplot as plt
        import matplotlib
        import matplotlib.pyplot as plt
from abc import ABCMeta, abstractmethod, abstractproperty
from neurokernel.LPU.utils.simpleio import *
from retina.input.image2d import image2Dfactory
from .map.mapimpl import pointmapfactory
from .transform.imagetransform import ImageTransform
        from scipy.interpolate import griddata
        from mpl_toolkits.mplot3d import Axes3D
        from matplotlib import cm
        from matplotlib.animation import FFMpegFileWriter, AVConvFileWriter
        from matplotlib.colors import Normalize
        from scipy.interpolate import griddata
        from mpl_toolkits.mplot3d import Axes3D
        from matplotlib import cm
        from matplotlib.animation import FFMpegFileWriter, AVConvFileWriter
        from matplotlib.colors import Normalize
            colors = np.tile(np.reshape(colors, [X.shape[0], X.shape[1], 1]),
                             [1, 1, 4])
            colors[:, :, 3] = 1.0

            ax.clear()
            ax.xaxis.set_ticks([])
            ax.yaxis.set_ticks([])
            ax.zaxis.set_ticks([])
            ax.plot_surface(X, Y, Z, rstride=1, cstride=1,
                            facecolors=colors, antialiased=False,
                            shade=False)
            fig.canvas.draw()
            writer.grab_frame()
        writer.finish()


class CylinderScreen(Screen):
    def __init__(self, config):
        config_screen = config['Screen']['CylinderScreen']

        self._radius = config_screen['radius']
        # cylinder length
        # (height is more appropriate name but is used elsewhere)
        self._length = config_screen['height']

        self._height = config_screen['columns']
        self._width = config_screen['parallels']

        # parameter corresponds to the length of the image
        # TODO allow to be specified

# Path: retina/input/image2d.py
# def image2Dfactory(input_type):
#     # I think this implementation will find only the classes defined in this
#     # file
#     all_image2d_cls = Image2D.__subclasses__()
#     all_image2d_names = [cls.__name__ for cls in all_image2d_cls]
#     try:
#         image2d_cls = all_image2d_cls[all_image2d_names.index(input_type)]
#     except ValueError:
#         print('Invalid Image2D subclass name: {}'.format(input_type))
#         print('Valid names: {}'.format(all_image2d_names))
#         return None
# 
#     return image2d_cls
# 
# Path: retina/screen/map/mapimpl.py
# def pointmapfactory(map_type):
#     # I think this implementation will find only the classes defined in this
#     # file
#     all_pointmap_cls = PointMap.__subclasses__()
#     all_pointmap_names = [cls.__name__ for cls in all_pointmap_cls]
#     try:
#         pointmap_cls = all_pointmap_cls[all_pointmap_names.index(map_type)]
#     except ValueError:
#         print('Invalid PointMap subclass name:{}'.format(map_type))
#         return None
#     return pointmap_cls
# 
# Path: retina/screen/transform/imagetransform.py
# class ImageTransform(SignalTransform):
#     def __init__(self, original_grid, new_grid):
#         """
#         :param original_grid: list of 2 1D arrays of original coordinates
#                               in strictly ascending order
#         :param new_grid: list of 2 arrays of new coordinates
#         """
#         self.ogrid = original_grid
#         self.ngrid = new_grid
# 
#     def interpolate(self, images):
#         new_images = np.empty(
#             (images.shape[0],)+ self.ngrid[0].shape, images.dtype)
#         for i, image in enumerate(images):
#             new_images[i] = self.interpolate_individual(image)
#         return new_images
# 
#     def interpolate_individual(self, image):
#         # unpacking
#         ogridx, ogridy = self.ogrid
#         ngridx, ngridy = self.ngrid
# 
#         f = RectBivariateSpline(ogridy, ogridx, image, kx=1, ky=1)
#         return f.ev(ngridy.flatten(), ngridx.flatten()).reshape(ngridx.shape)


# Path: retina/screen/screen.py
import os
import contextlib
import numpy as np
        import matplotlib
        import matplotlib.pyplot as plt
        import matplotlib
        import matplotlib.pyplot as plt
from abc import ABCMeta, abstractmethod, abstractproperty
from neurokernel.LPU.utils.simpleio import *
from retina.input.image2d import image2Dfactory
from .map.mapimpl import pointmapfactory
from .transform.imagetransform import ImageTransform
        from scipy.interpolate import griddata
        from mpl_toolkits.mplot3d import Axes3D
        from matplotlib import cm
        from matplotlib.animation import FFMpegFileWriter, AVConvFileWriter
        from matplotlib.colors import Normalize
        from scipy.interpolate import griddata
        from mpl_toolkits.mplot3d import Axes3D
        from matplotlib import cm
        from matplotlib.animation import FFMpegFileWriter, AVConvFileWriter
        from matplotlib.colors import Normalize

            colors = np.tile(np.reshape(colors, [X.shape[0], X.shape[1], 1]),
                             [1, 1, 4])
            colors[:, :, 3] = 1.0

            ax.clear()
            ax.xaxis.set_ticks([])
            ax.yaxis.set_ticks([])
            ax.zaxis.set_ticks([])
            ax.plot_surface(X, Y, Z, rstride=1, cstride=1,
                            facecolors=colors, antialiased=False,
                            shade=False)
            fig.canvas.draw()
            writer.grab_frame()
        writer.finish()


class CylinderScreen(Screen):
    def __init__(self, config):
        config_screen = config['Screen']['CylinderScreen']

        self._radius = config_screen['radius']
        # cylinder length
        # (height is more appropriate name but is used elsewhere)
        self._length = config_screen['height']

        self._height = config_screen['columns']
        self._width = config_screen['parallels']

        # parameter corresponds to the length of the image
        # TODO allow to be specified

        self._screen_to_image_map = pointmapfactory(