SimpleNorm

class astropy.visualization.SimpleNorm(stretch='linear', percent=None, *, min_percent=None, max_percent=None, vmin=None, vmax=None, power=1.0, log_a=1000, asinh_a=0.1, sinh_a=0.3, clip=False, invalid=-1.0)

Bases: object

Class to create a normalization object that can be used for displaying images with Matplotlib.

This convenience class provides the most common image stretching functions. Additional stretch functions are available in ImageNormalize.

Parameters:

stretch{‘linear’, ‘sqrt’, :ref: ‘power’, log’, ‘asinh’, ‘sinh’}, optional

The stretch function to apply to the image. The default is ‘linear’.

percentpython:float, optional

The percentage of the image values used to determine the pixel values of the minimum and maximum cut levels. The lower cut level will set at the (100 - percent) / 2 percentile, while the upper cut level will be set at the (100 + percent) / 2 percentile. The default is 100.0. percent is ignored if either min_percent or max_percent is input.

min_percentpython:float, optional

The percentile value used to determine the pixel value of minimum cut level. The default is 0.0. min_percent overrides percent.

max_percentpython:float, optional

The percentile value used to determine the pixel value of maximum cut level. The default is 100.0. max_percent overrides percent.

vminpython:float, optional

The pixel value of the minimum cut level. Data values less than vmin will set to vmin before stretching the image. The default is the image minimum. vmin overrides min_percent.

vmaxpython:float, optional

The pixel value of the maximum cut level. Data values greater than vmax will set to vmax before stretching the image. The default is the image maximum. vmax overrides max_percent.

powerpython:float, optional

The power index for stretch='power'. The default is 1.0.

log_apython:float, optional

The log index for stretch='log'. The default is 1000.

asinh_apython:float, optional

For stretch='asinh', the value where the asinh curve transitions from linear to logarithmic behavior, expressed as a fraction of the normalized image. Must be in the range between 0 and 1. The default is 0.1.

sinh_apython:float, optional

The scaling parameter for stretch='sinh'. The default is 0.3.

clipbool, optional

If True, data values outside the [0:1] range are clipped to the [0:1] range.

invalidpython:None or python:float, optional

Value to assign NaN values generated by the normalization. NaNs in the input data array are not changed. For matplotlib normalization, the invalid value should map to the matplotlib colormap “under” value (i.e., any finite value < 0). If None, then NaN values are not replaced. This keyword has no effect if clip=True.

See also

simple_norm

Examples

import numpy as np
import matplotlib.pyplot as plt
from astropy.visualization import SimpleNorm

image = np.arange(65536).reshape((256, 256))
snorm = SimpleNorm('sqrt', percent=98)
norm = snorm(image)
fig, ax = plt.subplots()
axim = ax.imshow(image, norm=norm, origin='lower')
fig.colorbar(axim)

(png, svg, pdf)

Methods Summary

__call__(data)	Return an ImageNormalize instance that can be used for displaying images with Matplotlib.
imshow(data[, ax])	A convenience function to display an image using matplotlib's matplotlib.pyplot.imshow function with the normalization defined by this class.

Methods Documentation

__call__(data)

Return an ImageNormalize instance that can be used for displaying images with Matplotlib.

Parameters:

datandarray

The image array.

Returns:

resultImageNormalize instance

An ImageNormalize instance that can be used for displaying images with Matplotlib.

imshow(data, ax=None, **kwargs)

A convenience function to display an image using matplotlib’s matplotlib.pyplot.imshow function with the normalization defined by this class.

Parameters:

data2D or 3D numpy:array_like

The data to display. Can be whatever imshow and ImageNormalize both accept.

axpython:None or Axes, optional

The matplotlib axes on which to plot. If None, then the current Axes instance is used.

**kwargspython:dict, optional

Keywords arguments passed to imshow. Cannot include the norm or X keyword.

Returns:

resultAxesImage

The AxesImage generated by imshow.

Examples

import numpy as np
import matplotlib.pyplot as plt
from astropy.visualization import SimpleNorm

image = np.arange(65536).reshape((256, 256))
snorm = SimpleNorm('sqrt', percent=98)
fig, ax = plt.subplots()
axim = snorm.imshow(image, ax=ax, origin='lower')
fig.colorbar(axim)

(png, svg, pdf)