IsisPool¶

class pysis.IsisPool(strict=False, *args, **kwargs)[source]¶

Multiprocessing pool for ISIS commands.

Example for running the following isis script in parallel for a list of images.

On the command line:

mdis2isis from=filename.IMG to=filename.cub
spiceinit from=filename.cub
mdiscal from=filename.cub to=filename.cal.cub

With pysis:

from pysis import IsisPool
from pysis.util import ImageName

def calibrate_mdis(images):
    images = [ImageName(filename) for filename in images]

    with IsisPool() as isis_pool:
        for filename in images:
            isis_pool.mdis2isis(from_=filename.IMG, to=filename.cub)

    with IsisPool() as isis_pool:
        for filename in images:
            isis_pool.spiceinit(from_=filename.cub)

    with IsisPool() as isis_pool:
        for filename in images:
            isis_pool.mdiscal(from_=filename.cub, to=filename.cal.cub)

Parameters:	strict – when in strict mode, the isis pool will initialize its attributes with commands from the isis environment. Otherwise attributes are dynamically added as use **kwargs – additional parameters used to initialize the multiprocessing pool

close_and_wait()[source]¶

Close the pool and wait for all commands to complete.

This will be automatically called if used as a context manager.

CubeFile¶

class pysis.CubeFile(stream_or_fname, filename=None)[source]¶

A Isis Cube file reader.

apply_numpy_specials(copy=True)[source]¶

Convert isis special pixel values to numpy special pixel values.

Isis	Numpy
Null	nan
Lrs	-inf
Lis	-inf
His	inf
Hrs	inf

Parameters:	copy – whether to apply the new special values to a copy of the pixel data and leave the orginial unaffected
Returns:	a numpy array with special values converted to numpy’s nan, inf and -inf

apply_scaling(copy=True)[source]¶

Scale pixel values to there true DN.

Parameters:	copy – whether to apply the scalling to a copy of the pixel data and leave the orginial unaffected
Returns:	a scalled version of the pixel data

bands¶

Number of image bands.

base¶

An additive factor by which to offset pixel DN.

data = None¶

A numpy array representing the image data.

dtype¶

Pixel data type.

filename = None¶

The filename if given, otherwise none.

get_image_array()[source]¶

Create an array for use in making an image.

Creates a linear stretch of the image and scales it to between 0 and 255. Null, Lis and Lrs pixels are set to 0. His and Hrs pixels are set to 255.

Usage:

from pysis import CubeFile
from PIL import Image

# Read in the image and create the image data
image = CubeFile.open('test.cub')
data = image.get_image_array()

# Save the first band to a new file
Image.fromarray(data[0]).save('test.png')

Returns:	A uint8 array of pixel values.

label = None¶

The parsed label header in dictionary form.

lines¶

Number of lines per band.

multiplier¶

A multiplicative factor by which to scale pixel DN.

classmethod open(filename)[source]¶

Read an Isis Cube file from disk.

Parameters:	filename – name of file to read as an isis file

samples¶

Number of samples per line.

shape¶

Tuple of images bands, lines and samples.

size¶

Total number of pixels.

specials_mask()[source]¶

Create a pixel map for special pixels.

Returns:	an array where the value is False if the pixel is special and True otherwise

start_byte¶

Index of the start of the image data (zero indexed).

tile_lines¶

Number of lines per tile.

tile_samples¶

Number of samples per tile.

Cube Label Parsing¶

Contributing¶

Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given.

You can contribute in many ways:

$ python -m unittest tests.test_bining

Credits¶

History¶