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'''
Code for package-level customization.
'''
from __future__ import absolute_import, division, print_function, unicode_literals
import numpy as np
class SpySettings:
'''Run-time settings for the `spectral` module.
After importing `spectral`, the settings object is referenced as
`spectral.settings`.
Noteworthy members:
`WX_GL_DEPTH_SIZE` (integer, default 24):
Sets the depth (in number of bits) for the OpenGL depth buffer.
If calls to `view_cube` or `view_nd` result in windows with blank
canvases, try reducing this value.
`envi_support_nonlowercase_params` (bool, default False)
By default, ENVI headers are read with parameter names converted
to lower case. If this attribute is set to True, parameters will
be read with original capitalization retained.
`show_progress` (bool, default True):
Indicates whether long-running algorithms should display progress
to sys.stdout. It can be useful to set this value to False when
SPy is embedded in another application (e.g., IPython Notebook).
`imshow_figure_size` (2-tuple of integers, default `None`):
Width and height (in inches) of windows opened with `imshow`. If
this value is `None`, matplotlib's default size is used.
`imshow_background_color` (3-tuple of integers, default (0,0,0)):
Default color to use for masked pixels in `imshow` displays.
`imshow_interpolation` (str, default `None`):
Pixel interpolation to be used in imshow windows. If this value
is `None`, matplotlib's default interpolation is used. Note that
zoom windows always use "nearest" interpolation.
`imshow_stretch`:
Default RGB linear color stretch to perform.
`imshow_stretch_all`:
If True, each color channel limits are determined independently.
`imshow_zoom_figure_width` (int, default `None`):
Width of zoom windows opened from an imshow window. Since zoom
windows are always square, this is also the window height. If this
value is `None`, matplotlib's default window size is used.
`imshow_zoom_pixel_width` (int, default 50):
Number of source image pixel rows and columns to display in a
zoom window.
`imshow_float_cmap` (str, default "gray"):
imshow color map to use with floating point arrays.
`imshow_class_alpha` (float, default 0.5):
alpha blending value to use for imshow class overlays
`imshow_enable_rectangle_selector` (bool, default True):
Whether to create the rectangle selection tool that enables
interactive image pixel class labeling. On some OS/backend
combinations, an exception may be raised when this object is
created so disabling it allows imshow windows to be created without
using the selector tool.
`imshow_disable_mpl_callbacks` (bool, default True):
If True, several matplotlib keypress event callbacks will be
disabled to prevent conflicts with callbacks from SPy. The
matplotlib callbacks can be set back to their defaults by
calling `matplotlib.rcdefaults()`.
'''
viewer = None
plotter = None
# If START_WX_APP is True and there is no current wx.App object when a
# GUI function is called, then an app object will be created.
START_WX_APP = True
# Parameter used by GLCanvas objects in view_cube and view_nd. If the
# canvas does not render, try reducing this value (e.g., 16).
WX_GL_DEPTH_SIZE = 24
envi_support_nonlowercase_params = False
# Should algorithms show completion progress of algorithms?
show_progress = True
# imshow settings
imshow_figure_size = None
imshow_background_color = (0, 0, 0)
imshow_interpolation = None
imshow_stretch = (0.0, 1.0)
imshow_stretch_all = True
imshow_zoom_figure_width = None
imshow_zoom_pixel_width = 50
imshow_float_cmap = 'gray'
imshow_class_alpha = 0.5
imshow_enable_rectangle_selector = True
imshow_disable_mpl_callbacks = True
# Default color table
spy_colors = np.array([[0, 0, 0],
[255, 0, 0],
[0, 255, 0],
[0, 0, 255],
[255, 255, 0],
[255, 0, 255],
[0, 255, 255],
[200, 100, 0],
[0, 200, 100],
[100, 0, 200],
[200, 0, 100],
[100, 200, 0],
[0, 100, 200],
[150, 75, 75],
[75, 150, 75],
[75, 75, 150],
[255, 100, 100],
[100, 255, 100],
[100, 100, 255],
[255, 150, 75],
[75, 255, 150],
[150, 75, 255],
[50, 50, 50],
[100, 100, 100],
[150, 150, 150],
[200, 200, 200],
[250, 250, 250],
[100, 0, 0],
[200, 0, 0],
[0, 100, 0],
[0, 200, 0],
[0, 0, 100],
[0, 0, 200],
[100, 100, 0],
[200, 200, 0],
[100, 0, 100],
[200, 0, 200],
[0, 100, 100],
[0, 200, 200]], np.int16)
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