Package wfpc2tools :: Module wfpc2destreak

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Module wfpc2destreak

source code

Version: 2.2 (2010 March 12)

Classes

[hide private]

Wfpc2destreak
Calculate magnitude of and remove streaks from specified group of wfpc2 data.

Functions

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check_py_pars(input_file, group, bias_thresh, row_thresh, input_mask, niter)
When run under python, verify that each unspecified parameter should take the default value, and give the user the opportunity to change it.

source code

int, float, float, int

check_cl_pars(input_file, group, bias_thresh, row_thresh, input_mask, niter)
When run from linux command line, verify that each parameter is valid.

source code

cr_reject(SubArray, niter)
Identify and replace cosmic rays in the given subarray.

source code

Int32

check_neighbors(new_cr, residual, cutoff, sub_shape)
Check for cosmic rays in neighboring pixels.

source code

float

median(y, mask)
Return the median of the array y, ignoring masked elements.

source code

tuple of two floats

fitline(x, y, mask)
Fit a straight line to y vs x, where mask is 0.

source code

update_header(self, hdr, verbosity)
update header from input c0 file with specified header, and updated data

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write_mask(data, filename)
write specified mask

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write_to_file(data, filename, hdr, verbosity, im_mean, im_sigma)

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Variables

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NUM_SIG = 2.5

TOT_ITER = 4

ERROR_RETURN = 2

__package__ = 'wfpc2tools'

Imports: pyfits, N, boxcar, pytools, OptionParser, ndimage, fileutil, wfpc2util, opusutil, sys, string

Function Details

[hide private]

check_py_pars(input_file, group, bias_thresh, row_thresh, input_mask, niter)

source code

When run under python, verify that each unspecified parameter should take the default value, and
    give the user the opportunity to change it.

@param input_file: name of input file
@type input_file: string
@param group: number of group to process
@type group: int
@param bias_thresh: bias threshold (no correction will be performed if this is exceeded by im_mean)
@type bias_thresh: float
@param row_thresh: row threshold (no correction will be performed if this exceeds the calculated row correction)
@type row_thresh: float
@param input_mask: name of input mask
@type input_mask: string
@param niter: number of CR rejection iterations   
@type niter: int
@return: group, row_thresh,
@return: group, bias_thresh, row_thresh
@rtype:  int, float, float

check_cl_pars(input_file, group, bias_thresh, row_thresh, input_mask, niter)

source code

When run from linux command line, verify that each parameter is valid.

Parameters:

input_file (string) - name of input file
group (int) - number of group to process
bias_thresh (float) - bias threshold (no correction will be performed if this is exceeded by im_mean)
row_thresh (float) - row threshold (no correction will be performed if this exceeds the calculated row correction)
input_mask (string) - name of input mask file
niter (int) - number of CR rejection iterations

Returns: int, float, float, int

group, row_thresh, niter

cr_reject(SubArray, niter)

source code

Identify and replace cosmic rays in the given subarray.

Parameters:

SubArray (ndarray) - subarray of the data
niter (int) - the number of iterations used when rejecting cosmic rays

check_neighbors(new_cr, residual, cutoff, sub_shape)

source code

Check for cosmic rays in neighboring pixels.

Parameters:

new_cr (Int32) - 1-D array of ones or zeros (1 indicates a cosmic ray)
residual (Float64) - 1-D array of residuals, subarray - fit
cutoff (float) - criterion for flagging an outlier as a cosmic ray
sub_shape (tuple) - numbers of lines and columns in subarray

Returns: Int32

new_cr, possibly with additional cosmic rays flagged

median(y, mask)

source code

Return the median of the array y, ignoring masked elements.

Parameters:

y (Float64) - array of values
mask (Int32) - array of ones or zeros (0 indicates a good value)

Returns: float

median of y, ignoring masked elements

fitline(x, y, mask)

source code

Fit a straight line to y vs x, where mask is 0.

Parameters:

x (Float64) - array of independent-variable values
y (Float64) - array of dependent-variable values
mask (Int32) - array of ones or zeros (0 indicates a good value)

Returns: tuple of two floats

coefficients of fit, the slope and intercept

update_header(self, hdr, verbosity)

source code

update header from input c0 file with specified header, and updated data

Parameters:

hdr (Pyfits header object) - header
verbosity (string) - verbosity level (0 for quiet, 1 verbose, 2 very verbose)

write_mask(data, filename)

source code

write specified mask

Parameters:

data (array of floats) - mask array
filename - mask file name
verbosity (string) - verbosity level (0 for quiet, 1 verbose, 2 very verbose)

write_to_file(data, filename, hdr, verbosity, im_mean, im_sigma)

source code

Parameters:

data (array of floats) - array
filename - mask file name
hdr (Pyfits header object) - header
verbosity (string) - verbosity level (0 for quiet, 1 verbose, 2 very verbose)
im_mean (float) - clipped mean of image region
im_sigma (float) - clipped sigma of image region