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train | nan_acf | Calculate the autocorrelation function of the noise
where the noise is a 2d array that may contain nans
Parameters
----------
noise : 2d-array
Noise image.
Returns
-------
acf : 2d-array
The ACF. | AegeanTools/fitting.py | def nan_acf(noise):
"""
Calculate the autocorrelation function of the noise
where the noise is a 2d array that may contain nans
Parameters
----------
noise : 2d-array
Noise image.
Returns
-------
acf : 2d-array
The ACF.
"""
corr = np.zeros(noise.shape)
... | def nan_acf(noise):
"""
Calculate the autocorrelation function of the noise
where the noise is a 2d array that may contain nans
Parameters
----------
noise : 2d-array
Noise image.
Returns
-------
acf : 2d-array
The ACF.
"""
corr = np.zeros(noise.shape)
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train | make_ita | Create the matrix ita of the noise where the noise may be a masked array
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Parameters
----------
noise : 2d-array
The noise image
acf : 2d-array
The autocorrelation matrix. (None = calcula... | AegeanTools/fitting.py | def make_ita(noise, acf=None):
"""
Create the matrix ita of the noise where the noise may be a masked array
where ita(x,y) is the correlation between pixel pairs that have the same separation as x and y.
Parameters
----------
noise : 2d-array
The noise image
acf : 2d-array
... | def make_ita(noise, acf=None):
"""
Create the matrix ita of the noise where the noise may be a masked array
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Parameters
----------
noise : 2d-array
The noise image
acf : 2d-array
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train | RB_bias | Calculate the expected bias on each of the parameters in the model pars.
Only parameters that are allowed to vary will have a bias.
Calculation follows the description of Refrieger & Brown 1998 (cite).
Parameters
----------
data : 2d-array
data that was fit
pars : lmfit.Parameters
... | AegeanTools/fitting.py | def RB_bias(data, pars, ita=None, acf=None):
"""
Calculate the expected bias on each of the parameters in the model pars.
Only parameters that are allowed to vary will have a bias.
Calculation follows the description of Refrieger & Brown 1998 (cite).
Parameters
----------
data : 2d-array
... | def RB_bias(data, pars, ita=None, acf=None):
"""
Calculate the expected bias on each of the parameters in the model pars.
Only parameters that are allowed to vary will have a bias.
Calculation follows the description of Refrieger & Brown 1998 (cite).
Parameters
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data : 2d-array
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train | bias_correct | Calculate and apply a bias correction to the given fit parameters
Parameters
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params : lmfit.Parameters
The model parameters. These will be modified.
data : 2d-array
The data which was used in the fitting
acf : 2d-array
ACF of the data. Default = None.
Retu... | AegeanTools/fitting.py | def bias_correct(params, data, acf=None):
"""
Calculate and apply a bias correction to the given fit parameters
Parameters
----------
params : lmfit.Parameters
The model parameters. These will be modified.
data : 2d-array
The data which was used in the fitting
acf : 2d-ar... | def bias_correct(params, data, acf=None):
"""
Calculate and apply a bias correction to the given fit parameters
Parameters
----------
params : lmfit.Parameters
The model parameters. These will be modified.
data : 2d-array
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train | condon_errors | Calculate the parameter errors for a fitted source
using the description of Condon'97
All parameters are assigned errors, assuming that all params were fit.
If some params were held fixed then these errors are overestimated.
Parameters
----------
source : :class:`AegeanTools.models.SimpleSource... | AegeanTools/fitting.py | def condon_errors(source, theta_n, psf=None):
"""
Calculate the parameter errors for a fitted source
using the description of Condon'97
All parameters are assigned errors, assuming that all params were fit.
If some params were held fixed then these errors are overestimated.
Parameters
-----... | def condon_errors(source, theta_n, psf=None):
"""
Calculate the parameter errors for a fitted source
using the description of Condon'97
All parameters are assigned errors, assuming that all params were fit.
If some params were held fixed then these errors are overestimated.
Parameters
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train | errors | Convert pixel based errors into sky coord errors
Parameters
----------
source : :class:`AegeanTools.models.SimpleSource`
The source which was fit.
model : lmfit.Parameters
The model which was fit.
wcshelper : :class:`AegeanTools.wcs_helpers.WCSHelper`
WCS information.
... | AegeanTools/fitting.py | def errors(source, model, wcshelper):
"""
Convert pixel based errors into sky coord errors
Parameters
----------
source : :class:`AegeanTools.models.SimpleSource`
The source which was fit.
model : lmfit.Parameters
The model which was fit.
wcshelper : :class:`AegeanTools.wc... | def errors(source, model, wcshelper):
"""
Convert pixel based errors into sky coord errors
Parameters
----------
source : :class:`AegeanTools.models.SimpleSource`
The source which was fit.
model : lmfit.Parameters
The model which was fit.
wcshelper : :class:`AegeanTools.wc... | [
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train | new_errors | Convert pixel based errors into sky coord errors
Uses covariance matrix for ra/dec errors
and calculus approach to a/b/pa errors
Parameters
----------
source : :class:`AegeanTools.models.SimpleSource`
The source which was fit.
model : lmfit.Parameters
The model which was fit.
... | AegeanTools/fitting.py | def new_errors(source, model, wcshelper): # pragma: no cover
"""
Convert pixel based errors into sky coord errors
Uses covariance matrix for ra/dec errors
and calculus approach to a/b/pa errors
Parameters
----------
source : :class:`AegeanTools.models.SimpleSource`
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Convert pixel based errors into sky coord errors
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----------
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train | ntwodgaussian_lmfit | Convert an lmfit.Parameters object into a function which calculates the model.
Parameters
----------
params : lmfit.Parameters
Model parameters, can have multiple components.
Returns
-------
model : func
A function f(x,y) that will compute the model. | AegeanTools/fitting.py | def ntwodgaussian_lmfit(params):
"""
Convert an lmfit.Parameters object into a function which calculates the model.
Parameters
----------
params : lmfit.Parameters
Model parameters, can have multiple components.
Returns
-------
model : func
A function f(x,y) that will ... | def ntwodgaussian_lmfit(params):
"""
Convert an lmfit.Parameters object into a function which calculates the model.
Parameters
----------
params : lmfit.Parameters
Model parameters, can have multiple components.
Returns
-------
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train | do_lmfit | Fit the model to the data
data may contain 'flagged' or 'masked' data with the value of np.NaN
Parameters
----------
data : 2d-array
Image data
params : lmfit.Parameters
Initial model guess.
B : 2d-array
B matrix to be used in residual calculations.
Default = N... | AegeanTools/fitting.py | def do_lmfit(data, params, B=None, errs=None, dojac=True):
"""
Fit the model to the data
data may contain 'flagged' or 'masked' data with the value of np.NaN
Parameters
----------
data : 2d-array
Image data
params : lmfit.Parameters
Initial model guess.
B : 2d-array
... | def do_lmfit(data, params, B=None, errs=None, dojac=True):
"""
Fit the model to the data
data may contain 'flagged' or 'masked' data with the value of np.NaN
Parameters
----------
data : 2d-array
Image data
params : lmfit.Parameters
Initial model guess.
B : 2d-array
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train | covar_errors | Take a set of parameters that were fit with lmfit, and replace the errors
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Parameters
----------
params : lmfit.Parameters
Model
data : 2d-array
Image data
errs : 2d-array ?
Image noise.
B : 2d-array
... | AegeanTools/fitting.py | def covar_errors(params, data, errs, B, C=None):
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Take a set of parameters that were fit with lmfit, and replace the errors
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Parameters
----------
params : lmfit.Parameters
Model
data : 2d-array
Image data
... | def covar_errors(params, data, errs, B, C=None):
"""
Take a set of parameters that were fit with lmfit, and replace the errors
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Parameters
----------
params : lmfit.Parameters
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Image data
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train | barrier | act as a multiprocessing barrier | AegeanTools/BANE.py | def barrier(events, sid, kind='neighbour'):
"""
act as a multiprocessing barrier
"""
events[sid].set()
# only wait for the neighbours
if kind=='neighbour':
if sid > 0:
logging.debug("{0} is waiting for {1}".format(sid, sid - 1))
events[sid - 1].wait()
if s... | def barrier(events, sid, kind='neighbour'):
"""
act as a multiprocessing barrier
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events[sid].set()
# only wait for the neighbours
if kind=='neighbour':
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train | sigmaclip | Perform sigma clipping on an array, ignoring non finite values.
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Parameters
----------
arr : iterable
An iterable array of numeric types.
... | AegeanTools/BANE.py | def sigmaclip(arr, lo, hi, reps=3):
"""
Perform sigma clipping on an array, ignoring non finite values.
During each iteration return an array whose elements c obey:
mean -std*lo < c < mean + std*hi
where mean/std are the mean std of the input array.
Parameters
----------
arr : iterabl... | def sigmaclip(arr, lo, hi, reps=3):
"""
Perform sigma clipping on an array, ignoring non finite values.
During each iteration return an array whose elements c obey:
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----------
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train | _sf2 | A shallow wrapper for sigma_filter.
Parameters
----------
args : list
A list of arguments for sigma_filter
Returns
-------
None | AegeanTools/BANE.py | def _sf2(args):
"""
A shallow wrapper for sigma_filter.
Parameters
----------
args : list
A list of arguments for sigma_filter
Returns
-------
None
"""
# an easier to debug traceback when multiprocessing
# thanks to https://stackoverflow.com/a/16618842/1710603
t... | def _sf2(args):
"""
A shallow wrapper for sigma_filter.
Parameters
----------
args : list
A list of arguments for sigma_filter
Returns
-------
None
"""
# an easier to debug traceback when multiprocessing
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train | sigma_filter | Calculate the background and rms for a sub region of an image. The results are
written to shared memory - irms and ibkg.
Parameters
----------
filename : string
Fits file to open
region : list
Region within the fits file that is to be processed. (row_min, row_max).
step_size :... | AegeanTools/BANE.py | def sigma_filter(filename, region, step_size, box_size, shape, domask, sid):
"""
Calculate the background and rms for a sub region of an image. The results are
written to shared memory - irms and ibkg.
Parameters
----------
filename : string
Fits file to open
region : list
... | def sigma_filter(filename, region, step_size, box_size, shape, domask, sid):
"""
Calculate the background and rms for a sub region of an image. The results are
written to shared memory - irms and ibkg.
Parameters
----------
filename : string
Fits file to open
region : list
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train | filter_mc_sharemem | Calculate the background and noise images corresponding to the input file.
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filename : str
Filename to be filtered.
step_size : (int, int)
Step size for the filter.
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"""
Calculate the background and noise images corresponding to the input file.
The calculation is done via a box-car approach and uses multiple cores and shared memory.
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----------
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Calculate the background and noise images corresponding to the input file.
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train | filter_image | Create a background and noise image from an input image.
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----------
im_name : str or HDUList
Image to filter. Either a string filename or an astropy.io.fits.HDUList.
out_base : str
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"""
Create a background and noise image from an input image.
Resulting images are written to `outbase_bkg.fits` and `outbase_rms.fits`
Parameters
----------
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Create a background and noise image from an input image.
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data : numpy.ndarray
The data to be written.
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The header for the fits file.
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The file to write
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Combine data and a fits header to write a fits file.
Parameters
----------
data : numpy.ndarray
The data to be written.
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The header for the fits file.
file_name : string
The file to writ... | def write_fits(data, header, file_name):
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Combine data and a fits header to write a fits file.
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data : numpy.ndarray
The data to be written.
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The header for the fits file.
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train | dec2dec | Convert sexegessimal RA string into a float in degrees.
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dec : string
A string separated representing the Dec.
Expected format is `[+- ]hh:mm[:ss.s]`
Colons can be replaced with any whit space character.
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dec : float
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"""
Convert sexegessimal RA string into a float in degrees.
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----------
dec : string
A string separated representing the Dec.
Expected format is `[+- ]hh:mm[:ss.s]`
Colons can be replaced with any whit space character.
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Convert sexegessimal RA string into a float in degrees.
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dec : string
A string separated representing the Dec.
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train | dec2dms | Convert decimal degrees into a sexagessimal string in degrees.
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x : float
Angle in degrees
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dms : string
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Convert decimal degrees into a sexagessimal string in degrees.
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----------
x : float
Angle in degrees
Returns
-------
dms : string
String of format [+-]DD:MM:SS.SS
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Convert decimal degrees into a sexagessimal string in degrees.
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x : float
Angle in degrees
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dms : string
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train | dec2hms | Convert decimal degrees into a sexagessimal string in hours.
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x : float
Angle in degrees
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dms : string
String of format HH:MM:SS.SS
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Convert decimal degrees into a sexagessimal string in hours.
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x : float
Angle in degrees
Returns
-------
dms : string
String of format HH:MM:SS.SS
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Angle in degrees
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train | gcd | Calculate the great circle distance between to points using the haversine formula [1]_.
Parameters
----------
ra1, dec1, ra2, dec2 : float
The coordinates of the two points of interest.
Units are in degrees.
Returns
-------
dist : float
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Calculate the great circle distance between to points using the haversine formula [1]_.
Parameters
----------
ra1, dec1, ra2, dec2 : float
The coordinates of the two points of interest.
Units are in degrees.
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-------
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Calculate the great circle distance between to points using the haversine formula [1]_.
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ra1, dec1, ra2, dec2 : float
The coordinates of the two points of interest.
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train | bear | Calculate the bearing of point 2 from point 1 along a great circle.
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----------
ra1, dec1, ra2, dec2 : float
The sky coordinates (degrees) of the two points.
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-... | AegeanTools/angle_tools.py | def bear(ra1, dec1, ra2, dec2):
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Calculate the bearing of point 2 from point 1 along a great circle.
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train | translate | Translate a given point a distance r in the (initial) direction theta, along a great circle.
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ra, dec : float
The initial point of interest (degrees).
r, theta : float
The distance and initial direction to translate (degrees).
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ra, dec ... | AegeanTools/angle_tools.py | def translate(ra, dec, r, theta):
"""
Translate a given point a distance r in the (initial) direction theta, along a great circle.
Parameters
----------
ra, dec : float
The initial point of interest (degrees).
r, theta : float
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Translate a given point a distance r in the (initial) direction theta, along a great circle.
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The initial point of interest (degrees).
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train | dist_rhumb | Calculate the Rhumb line distance between two points [1]_.
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ra1, dec1, ra2, dec2 : float
The position of the two points (degrees).
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dist : float
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"""
Calculate the Rhumb line distance between two points [1]_.
A Rhumb line between two points is one which follows a constant bearing.
Parameters
----------
ra1, dec1, ra2, dec2 : float
The position of the two points (degrees).
Returns
---... | def dist_rhumb(ra1, dec1, ra2, dec2):
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Calculate the Rhumb line distance between two points [1]_.
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ra1, dec1, ra2, dec2 : float
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train | bear_rhumb | Calculate the bearing of point 2 from point 1 along a Rhumb line.
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ra1, dec1, ra2, dec2 : float
The sky coordinates (degrees) of the two points.
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Calculate the bearing of point 2 from point 1 along a Rhumb line.
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Calculate the bearing of point 2 from point 1 along a Rhumb line.
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train | translate_rhumb | Translate a given point a distance r in the (initial) direction theta, along a Rhumb line.
Parameters
----------
ra, dec : float
The initial point of interest (degrees).
r, theta : float
The distance and initial direction to translate (degrees).
Returns
-------
ra, dec : fl... | AegeanTools/angle_tools.py | def translate_rhumb(ra, dec, r, theta):
"""
Translate a given point a distance r in the (initial) direction theta, along a Rhumb line.
Parameters
----------
ra, dec : float
The initial point of interest (degrees).
r, theta : float
The distance and initial direction to translate ... | def translate_rhumb(ra, dec, r, theta):
"""
Translate a given point a distance r in the (initial) direction theta, along a Rhumb line.
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ra, dec : float
The initial point of interest (degrees).
r, theta : float
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train | galactic2fk5 | Convert galactic l/b to fk5 ra/dec
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l, b : float
Galactic coordinates in radians.
Returns
-------
ra, dec : float
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"""
Convert galactic l/b to fk5 ra/dec
Parameters
----------
l, b : float
Galactic coordinates in radians.
Returns
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ra, dec : float
FK5 ecliptic coordinates in radians.
"""
a = SkyCoord(l, b, unit=(u.radian, u.radian), frame='galac... | def galactic2fk5(l, b):
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Convert galactic l/b to fk5 ra/dec
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l, b : float
Galactic coordinates in radians.
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train | mask_plane | Mask a 2d image (data) such that pixels within 'region' are set to nan.
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data : 2d-array
Image array.
wcs : astropy.wcs.WCS
WCS for the image in question.
region : :class:`AegeanTools.regions.Region`
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Mask a 2d image (data) such that pixels within 'region' are set to nan.
Parameters
----------
data : 2d-array
Image array.
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WCS for the image in question.
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Mask a 2d image (data) such that pixels within 'region' are set to nan.
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----------
data : 2d-array
Image array.
wcs : astropy.wcs.WCS
WCS for the image in question.
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regionfile : str
A file which can be loaded as a :class:`AegeanTools.regions.Region`.
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Created a masked version of file, using a region.
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A file which can be loaded as a :class:`AegeanTools.regions.Region`.
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train | mask_table | Apply a given mask (region) to the table, removing all the rows with ra/dec inside the region
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region : :class:`AegeanTools.regions.Region`
Region to mask.
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Apply a given mask (region) to the table, removing all the rows with ra/dec inside the region
If negate=False then remove the rows with ra/dec outside the region.
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----------
region : :class:`AegeanTools.regio... | def mask_table(region, table, negate=False, racol='ra', deccol='dec'):
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Apply a given mask (region) to the table, removing all the rows with ra/dec inside the region
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train | mask_catalog | Apply a region file as a mask to a catalog, removing all the rows with ra/dec inside the region
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regionfile : str
A file which can be loaded as a :class:`AegeanTools.regions.Region`.
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Apply a region file as a mask to a catalog, removing all the rows with ra/dec inside the region
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----------
regionfile : str... | def mask_catalog(regionfile, infile, outfile, negate=False, racol='ra', deccol='dec'):
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Apply a region file as a mask to a catalog, removing all the rows with ra/dec inside the region
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----------
mimfile : str
Input file in MIMAS format.
regfile : str
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Convert a MIMAS region (.mim) file into a DS9 region (.reg) file.
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mimfile : str
Input file in MIMAS format.
regfile : str
Output file.
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mimfile : str
Input file in MIMAS format.
regfile : str
Output file.
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train | mim2fits | Convert a MIMAS region (.mim) file into a MOC region (.fits) file.
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mimfile : str
Input file in MIMAS format.
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Convert a MIMAS region (.mim) file into a MOC region (.fits) file.
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mimfile : str
Input file in MIMAS format.
fitsfile : str
Output file.
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region.write_fits(fitsfile, moctool=... | def mim2fits(mimfile, fitsfile):
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Input file in MIMAS format.
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Output file.
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train | box2poly | Convert a string that describes a box in ds9 format, into a polygon that is given by the corners of the box
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line : str
A string containing a DS9 region command for a box.
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-------
poly : [ra, dec, ...]
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----------
line : str
A string containing a DS9 region command for a box.
Returns
-------
poly : [ra, dec, ...]
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A string containing a DS9 region command for a box.
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A string containing a DS9 region command for a circle.
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line : str
A string containing a DS9 region command for a circle.
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circle : [ra, dec, radius]
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A string containing a DS9 region command for a circle.
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A string containing a DS9 region command for a polygon.
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A string containing a DS9 region command for a polygon.
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A string containing a DS9 region command for a polygon.
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regfile : str
DS9 region (.reg) file.
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MIMAS region (.mim) file.
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Parse a DS9 region file and write a MIMAS region (.mim) file.
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regfile : str
DS9 region (.reg) file.
mimfile : str
MIMAS region (.mim) file.
maxdepth : str
Depth/resolution of the region file.
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Parse a DS9 region file and write a MIMAS region (.mim) file.
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DS9 region (.reg) file.
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MIMAS region (.mim) file.
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Depth/resolution of the region file.
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Return a region that is the combination of those specified in the container.
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train | intersect_regions | Construct a region which is the intersection of all regions described in the given
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flist : list
A list of region filenames.
Returns
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region : :class:`AegeanTools.regions.Region`
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"""
Construct a region which is the intersection of all regions described in the given
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Parameters
----------
flist : list
A list of region filenames.
Returns
-------
region : :class:`AegeanTools.regions.Region`
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"""
Construct a region which is the intersection of all regions described in the given
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Parameters
----------
flist : list
A list of region filenames.
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-------
region : :class:`AegeanTools.regions.Region`
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train | save_region | Save the given region to a file
Parameters
----------
region : :class:`AegeanTools.regions.Region`
A region.
filename : str
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"""
Save the given region to a file
Parameters
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region : :class:`AegeanTools.regions.Region`
A region.
filename : str
Output file name.
"""
region.save(filename)
logging.info("Wrote {0}".format(filename))
return | def save_region(region, filename):
"""
Save the given region to a file
Parameters
----------
region : :class:`AegeanTools.regions.Region`
A region.
filename : str
Output file name.
"""
region.save(filename)
logging.info("Wrote {0}".format(filename))
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train | save_as_image | Convert a MIMAS region (.mim) file into a image (eg .png)
Parameters
----------
region : :class:`AegeanTools.regions.Region`
Region of interest.
filename : str
Output filename. | AegeanTools/MIMAS.py | def save_as_image(region, filename):
"""
Convert a MIMAS region (.mim) file into a image (eg .png)
Parameters
----------
region : :class:`AegeanTools.regions.Region`
Region of interest.
filename : str
Output filename.
"""
import healpy as hp
pixels = list(region.get... | def save_as_image(region, filename):
"""
Convert a MIMAS region (.mim) file into a image (eg .png)
Parameters
----------
region : :class:`AegeanTools.regions.Region`
Region of interest.
filename : str
Output filename.
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train | get_pixinfo | Return some pixel information based on the given hdu header
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pixscale - the side lengths of a pixel (assuming they are square)
Parameters
----------
header : HDUHeader or dict
FITS header information
Returns
-------
pixarea : float
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"""
Return some pixel information based on the given hdu header
pixarea - the area of a single pixel in deg2
pixscale - the side lengths of a pixel (assuming they are square)
Parameters
----------
header : HDUHeader or dict
FITS header information
Retur... | def get_pixinfo(header):
"""
Return some pixel information based on the given hdu header
pixarea - the area of a single pixel in deg2
pixscale - the side lengths of a pixel (assuming they are square)
Parameters
----------
header : HDUHeader or dict
FITS header information
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train | get_beam | Create a :class:`AegeanTools.fits_image.Beam` object from a fits header.
BPA may be missing but will be assumed to be zero.
if BMAJ or BMIN are missing then return None instead of a beam object.
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header : HDUHeader
The fits header.
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beam : ... | AegeanTools/fits_image.py | def get_beam(header):
"""
Create a :class:`AegeanTools.fits_image.Beam` object from a fits header.
BPA may be missing but will be assumed to be zero.
if BMAJ or BMIN are missing then return None instead of a beam object.
Parameters
----------
header : HDUHeader
The fits header.
... | def get_beam(header):
"""
Create a :class:`AegeanTools.fits_image.Beam` object from a fits header.
BPA may be missing but will be assumed to be zero.
if BMAJ or BMIN are missing then return None instead of a beam object.
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header : HDUHeader
The fits header.
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train | fix_aips_header | Search through an image header. If the keywords BMAJ/BMIN/BPA are not set,
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Fix the header if possible, otherwise don't. Either way, don't complain.
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"""
Search through an image header. If the keywords BMAJ/BMIN/BPA are not set,
but there are AIPS history cards, then we can populate the BMAJ/BMIN/BPA.
Fix the header if possible, otherwise don't. Either way, don't complain.
Parameters
----------
header : HDUH... | def fix_aips_header(header):
"""
Search through an image header. If the keywords BMAJ/BMIN/BPA are not set,
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train | FitsImage.set_pixels | Set the image data.
Will not work if the new image has a different shape than the current image.
Parameters
----------
pixels : numpy.ndarray
New image data
Returns
-------
None | AegeanTools/fits_image.py | def set_pixels(self, pixels):
"""
Set the image data.
Will not work if the new image has a different shape than the current image.
Parameters
----------
pixels : numpy.ndarray
New image data
Returns
-------
None
"""
if... | def set_pixels(self, pixels):
"""
Set the image data.
Will not work if the new image has a different shape than the current image.
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----------
pixels : numpy.ndarray
New image data
Returns
-------
None
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train | FitsImage.get_background_rms | Calculate the rms of the image. The rms is calculated from the interqurtile range (IQR), to
reduce bias from source pixels.
Returns
-------
rms : float
The image rms.
Notes
-----
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"""
Calculate the rms of the image. The rms is calculated from the interqurtile range (IQR), to
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Returns
-------
rms : float
The image rms.
Notes
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Calculate the rms of the image. The rms is calculated from the interqurtile range (IQR), to
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-------
rms : float
The image rms.
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train | FitsImage.pix2sky | Get the sky coordinates for a given image pixel.
Parameters
----------
pixel : (float, float)
Image coordinates.
Returns
-------
ra,dec : float
Sky coordinates (degrees) | AegeanTools/fits_image.py | def pix2sky(self, pixel):
"""
Get the sky coordinates for a given image pixel.
Parameters
----------
pixel : (float, float)
Image coordinates.
Returns
-------
ra,dec : float
Sky coordinates (degrees)
"""
pixbox = ... | def pix2sky(self, pixel):
"""
Get the sky coordinates for a given image pixel.
Parameters
----------
pixel : (float, float)
Image coordinates.
Returns
-------
ra,dec : float
Sky coordinates (degrees)
"""
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train | FitsImage.sky2pix | Get the pixel coordinates for a given sky position (degrees).
Parameters
----------
skypos : (float,float)
ra,dec position in degrees.
Returns
-------
x,y : float
Pixel coordinates. | AegeanTools/fits_image.py | def sky2pix(self, skypos):
"""
Get the pixel coordinates for a given sky position (degrees).
Parameters
----------
skypos : (float,float)
ra,dec position in degrees.
Returns
-------
x,y : float
Pixel coordinates.
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... | def sky2pix(self, skypos):
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Get the pixel coordinates for a given sky position (degrees).
Parameters
----------
skypos : (float,float)
ra,dec position in degrees.
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-------
x,y : float
Pixel coordinates.
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train | load_sources | Open a file, read contents, return a list of all the sources in that file.
@param filename:
@return: list of OutputSource objects | AegeanTools/AeRes.py | def load_sources(filename):
"""
Open a file, read contents, return a list of all the sources in that file.
@param filename:
@return: list of OutputSource objects
"""
catalog = catalogs.table_to_source_list(catalogs.load_table(filename))
logging.info("read {0} sources from {1}".format(len(cat... | def load_sources(filename):
"""
Open a file, read contents, return a list of all the sources in that file.
@param filename:
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"""
catalog = catalogs.table_to_source_list(catalogs.load_table(filename))
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train | search_beam | Will search the beam info from the HISTORY
:param hdulist:
:return: | scripts/fix_beam.py | def search_beam(hdulist):
"""
Will search the beam info from the HISTORY
:param hdulist:
:return:
"""
header = hdulist[0].header
history = header['HISTORY']
history_str = str(history)
#AIPS CLEAN BMAJ= 1.2500E-02 BMIN= 1.2500E-02 BPA= 0.00
if 'BMAJ' in history_str:
... | def search_beam(hdulist):
"""
Will search the beam info from the HISTORY
:param hdulist:
:return:
"""
header = hdulist[0].header
history = header['HISTORY']
history_str = str(history)
#AIPS CLEAN BMAJ= 1.2500E-02 BMIN= 1.2500E-02 BPA= 0.00
if 'BMAJ' in history_str:
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train | fix_shape | Ensure that a>=b for a given source object.
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Parameters
----------
source : object
any object with a/b/pa/err_a/err_b properties | AegeanTools/source_finder.py | def fix_shape(source):
"""
Ensure that a>=b for a given source object.
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err_a/err_b are also swapped as needed.
Parameters
----------
source : object
any object with a/b/pa/err_a/err_b properties
"""
if source.a < source.b:
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"""
Ensure that a>=b for a given source object.
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----------
source : object
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train | theta_limit | Angle theta is periodic with period pi.
Constrain theta such that -pi/2<theta<=pi/2.
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theta : float
Input angle.
Returns
-------
theta : float
Rotate angle. | AegeanTools/source_finder.py | def theta_limit(theta):
"""
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Parameters
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theta : float
Input angle.
Returns
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theta : float
Rotate angle.
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theta : float
Input angle.
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theta : float
Rotate angle.
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train | scope2lat | Convert a telescope name into a latitude
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telescope : str
Acronym (name) of telescope, eg MWA.
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lat : float
The latitude of the telescope.
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"""
Convert a telescope name into a latitude
returns None when the telescope is unknown.
Parameters
----------
telescope : str
Acronym (name) of telescope, eg MWA.
Returns
-------
lat : float
The latitude of the telescope.
Notes
--... | def scope2lat(telescope):
"""
Convert a telescope name into a latitude
returns None when the telescope is unknown.
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telescope : str
Acronym (name) of telescope, eg MWA.
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Return 1 if we are not able to make a queue via pprocess.
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cores : int
The number of cores that are requested.
Returns
-------
cores : int
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"""
Determine how many cores we are able to use.
Return 1 if we are not able to make a queue via pprocess.
Parameters
----------
cores : int
The number of cores that are requested.
Returns
-------
cores : int
The number of cores available.
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"""
Determine how many cores we are able to use.
Return 1 if we are not able to make a queue via pprocess.
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----------
cores : int
The number of cores that are requested.
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train | get_aux_files | Look for and return all the aux files that are associated witht this filename.
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rms (_rms.fits)
mask (.mim)
catalogue (_comp.fits)
psf map (_psf.fits)
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"""
Look for and return all the aux files that are associated witht this filename.
Will look for:
background (_bkg.fits)
rms (_rms.fits)
mask (.mim)
catalogue (_comp.fits)
psf map (_psf.fits)
will return filenames if they exist, or None ... | def get_aux_files(basename):
"""
Look for and return all the aux files that are associated witht this filename.
Will look for:
background (_bkg.fits)
rms (_rms.fits)
mask (.mim)
catalogue (_comp.fits)
psf map (_psf.fits)
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train | SourceFinder._gen_flood_wrap | Generator function.
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Needs to work for entire image, and also for components within an island.
Parameters
----------
data : 2d-array
Image array.
rmsimg : 2d-array
Noise image.
... | AegeanTools/source_finder.py | def _gen_flood_wrap(self, data, rmsimg, innerclip, outerclip=None, domask=False):
"""
Generator function.
Segment an image into islands and return one island at a time.
Needs to work for entire image, and also for components within an island.
Parameters
----------
... | def _gen_flood_wrap(self, data, rmsimg, innerclip, outerclip=None, domask=False):
"""
Generator function.
Segment an image into islands and return one island at a time.
Needs to work for entire image, and also for components within an island.
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train | SourceFinder.estimate_lmfit_parinfo | Estimates the number of sources in an island and returns initial parameters for the fit as well as
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Parameters
----------
data : 2d-array
(sub) image of flux values. Background should be subtracted.
rmsimg : 2d-array
Image of 1... | AegeanTools/source_finder.py | def estimate_lmfit_parinfo(self, data, rmsimg, curve, beam, innerclip, outerclip=None, offsets=(0, 0),
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"""
Estimates the number of sources in an island and returns initial parameters for the fit as well as
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Estimates the number of sources in an island and returns initial parameters for the fit as well as
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train | SourceFinder.result_to_components | Convert fitting results into a set of components
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result : lmfit.MinimizerResult
The fitting results.
model : lmfit.Parameters
The model that was fit.
island_data : :class:`AegeanTools.models.IslandFittingData`
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"""
Convert fitting results into a set of components
Parameters
----------
result : lmfit.MinimizerResult
The fitting results.
model : lmfit.Parameters
The model that was fit.
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Convert fitting results into a set of components
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----------
result : lmfit.MinimizerResult
The fitting results.
model : lmfit.Parameters
The model that was fit.
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train | SourceFinder.load_globals | Populate the global_data object by loading or calculating the various components
Parameters
----------
filename : str or HDUList
Main image which source finding is run on
hdu_index : int
HDU index of the image within the fits file, default is 0 (first)
... | AegeanTools/source_finder.py | def load_globals(self, filename, hdu_index=0, bkgin=None, rmsin=None, beam=None, verb=False, rms=None, bkg=None, cores=1,
do_curve=True, mask=None, lat=None, psf=None, blank=False, docov=True, cube_index=None):
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Populate the global_data object by loading or calculating the variou... | def load_globals(self, filename, hdu_index=0, bkgin=None, rmsin=None, beam=None, verb=False, rms=None, bkg=None, cores=1,
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train | SourceFinder.save_background_files | Generate and save the background and RMS maps as FITS files.
They are saved in the current directly as aegean-background.fits and aegean-rms.fits.
Parameters
----------
image_filename : str or HDUList
Input image.
hdu_index : int
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outbase=None):
"""
Generate and save the background and RMS maps as FITS files.
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Generate and save the background and RMS maps as FITS files.
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train | SourceFinder.save_image | Save the image data.
This is probably only useful if the image data has been blanked.
Parameters
----------
outname : str
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"""
Save the image data.
This is probably only useful if the image data has been blanked.
Parameters
----------
outname : str
Name for the output file.
"""
hdu = self.global_data.img.hdu
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Save the image data.
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outname : str
Name for the output file.
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train | SourceFinder._make_bkg_rms | Calculate an rms image and a bkg image.
Parameters
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mesh_size : int
Number of beams per box default = 20
forced_rms : float
The rms of the image.
If None: calculate the rms level (default).
Otherwise assume a constant rms.
... | AegeanTools/source_finder.py | def _make_bkg_rms(self, mesh_size=20, forced_rms=None, forced_bkg=None, cores=None):
"""
Calculate an rms image and a bkg image.
Parameters
----------
mesh_size : int
Number of beams per box default = 20
forced_rms : float
The rms of the image.
... | def _make_bkg_rms(self, mesh_size=20, forced_rms=None, forced_bkg=None, cores=None):
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Calculate an rms image and a bkg image.
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----------
mesh_size : int
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train | SourceFinder._estimate_bkg_rms | Estimate the background noise mean and RMS.
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The RMS is estimated as the IQR of data / 1.34896.
Parameters
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xmin, xmax, ymin, ymax : int
The bounding region over which the bkg/rms will be calculated.
Retu... | AegeanTools/source_finder.py | def _estimate_bkg_rms(self, xmin, xmax, ymin, ymax):
"""
Estimate the background noise mean and RMS.
The mean is estimated as the median of data.
The RMS is estimated as the IQR of data / 1.34896.
Parameters
----------
xmin, xmax, ymin, ymax : int
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Estimate the background noise mean and RMS.
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xmin, xmax, ymin, ymax : int
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train | SourceFinder._load_aux_image | Load a fits file (bkg/rms/curve) and make sure that
it is the same shape as the main image.
Parameters
----------
image : :class:`AegeanTools.fits_image.FitsImage`
The main image that has already been loaded.
auxfile : str or HDUList
The auxiliary file t... | AegeanTools/source_finder.py | def _load_aux_image(self, image, auxfile):
"""
Load a fits file (bkg/rms/curve) and make sure that
it is the same shape as the main image.
Parameters
----------
image : :class:`AegeanTools.fits_image.FitsImage`
The main image that has already been loaded.
... | def _load_aux_image(self, image, auxfile):
"""
Load a fits file (bkg/rms/curve) and make sure that
it is the same shape as the main image.
Parameters
----------
image : :class:`AegeanTools.fits_image.FitsImage`
The main image that has already been loaded.
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train | SourceFinder._refit_islands | Do island refitting (priorized fitting) on a group of islands.
Parameters
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group : list
A list of components grouped by island.
stage : int
Refitting stage.
outerclip : float
Ignored, placed holder for future development.
... | AegeanTools/source_finder.py | def _refit_islands(self, group, stage, outerclip=None, istart=0):
"""
Do island refitting (priorized fitting) on a group of islands.
Parameters
----------
group : list
A list of components grouped by island.
stage : int
Refitting stage.
... | def _refit_islands(self, group, stage, outerclip=None, istart=0):
"""
Do island refitting (priorized fitting) on a group of islands.
Parameters
----------
group : list
A list of components grouped by island.
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Refitting stage.
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train | SourceFinder._fit_island | Take an Island, do all the parameter estimation and fitting.
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island_data : :class:`AegeanTools.models.IslandFittingData`
The island to be fit.
Returns
-------
sources : list
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"""
Take an Island, do all the parameter estimation and fitting.
Parameters
----------
island_data : :class:`AegeanTools.models.IslandFittingData`
The island to be fit.
Returns
-------
sources : list
... | def _fit_island(self, island_data):
"""
Take an Island, do all the parameter estimation and fitting.
Parameters
----------
island_data : :class:`AegeanTools.models.IslandFittingData`
The island to be fit.
Returns
-------
sources : list
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train | SourceFinder._fit_islands | Execute fitting on a list of islands
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Parameters
----------
islands : list of :class:`AegeanTools.models.IslandFittingData`
... | AegeanTools/source_finder.py | def _fit_islands(self, islands):
"""
Execute fitting on a list of islands
This function just wraps around fit_island, so that when we do multiprocesing
a single process will fit multiple islands before returning results.
Parameters
----------
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Execute fitting on a list of islands
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train | SourceFinder.find_sources_in_image | Run the Aegean source finder.
Parameters
----------
filename : str or HDUList
Image filename or HDUList.
hdu_index : int
The index of the FITS HDU (extension).
outfile : str
file for printing catalog (NOT a table, just a text file of my own... | AegeanTools/source_finder.py | def find_sources_in_image(self, filename, hdu_index=0, outfile=None, rms=None, bkg=None, max_summits=None, innerclip=5,
outerclip=4, cores=None, rmsin=None, bkgin=None, beam=None, doislandflux=False,
nopositive=False, nonegative=False, mask=None, lat=None, img... | def find_sources_in_image(self, filename, hdu_index=0, outfile=None, rms=None, bkg=None, max_summits=None, innerclip=5,
outerclip=4, cores=None, rmsin=None, bkgin=None, beam=None, doislandflux=False,
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train | SourceFinder.priorized_fit_islands | Take an input catalog, and image, and optional background/noise images
fit the flux and ra/dec for each of the given sources, keeping the morphology fixed
if doregroup is true the groups will be recreated based on a matching radius/probability.
if doregroup is false then the islands of the inpu... | AegeanTools/source_finder.py | def priorized_fit_islands(self, filename, catalogue, hdu_index=0, outfile=None, bkgin=None, rmsin=None, cores=1,
rms=None, bkg=None, beam=None, lat=None, imgpsf=None, catpsf=None, stage=3, ratio=None, outerclip=3,
doregroup=True, docov=True, cube_index=None):
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rms=None, bkg=None, beam=None, lat=None, imgpsf=None, catpsf=None, stage=3, ratio=None, outerclip=3,
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train | check_table_formats | Determine whether a list of files are of a recognizable output type.
Parameters
----------
files : str
A list of file names
Returns
-------
result : bool
True if *all* the file names are supported | AegeanTools/catalogs.py | def check_table_formats(files):
"""
Determine whether a list of files are of a recognizable output type.
Parameters
----------
files : str
A list of file names
Returns
-------
result : bool
True if *all* the file names are supported
"""
cont = True
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Determine whether a list of files are of a recognizable output type.
Parameters
----------
files : str
A list of file names
Returns
-------
result : bool
True if *all* the file names are supported
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train | show_formats | Print a list of all the file formats that are supported for writing.
The file formats are determined by their extensions.
Returns
-------
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"""
Print a list of all the file formats that are supported for writing.
The file formats are determined by their extensions.
Returns
-------
None
"""
fmts = {
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"fits": "FITS Binary Table",
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"""
Print a list of all the file formats that are supported for writing.
The file formats are determined by their extensions.
Returns
-------
None
"""
fmts = {
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train | update_meta_data | Modify the metadata dictionary.
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----------
meta : dict
The dictionary to be modified, default = None (empty)
Returns
-------
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"""
Modify the metadata dictionary.
DATE, PROGRAM, and PROGVER are added/modified.
Parameters
----------
meta : dict
The dictionary to be modified, default = None (empty)
Returns
-------
An updated dictionary.
"""
if meta is None... | def update_meta_data(meta=None):
"""
Modify the metadata dictionary.
DATE, PROGRAM, and PROGVER are added/modified.
Parameters
----------
meta : dict
The dictionary to be modified, default = None (empty)
Returns
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An updated dictionary.
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train | save_catalog | Save a catalogue of sources using filename as a model. Meta data can be written to some file types
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Save a catalogue of sources using filename as a model. Meta data can be written to some file types
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Each type of source will be in a separate file:
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Save a catalogue of sources using filename as a model. Meta data can be written to some file types
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train | load_catalog | Load a catalogue and extract the source positions (only)
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filename : str
Filename to read. Supported types are csv, tab, tex, vo, vot, and xml.
Returns
-------
catalogue : list
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"""
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Parameters
----------
filename : str
Filename to read. Supported types are csv, tab, tex, vo, vot, and xml.
Returns
-------
catalogue : list
A list of [ (ra, dec), ...]
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Filename to read. Supported types are csv, tab, tex, vo, vot, and xml.
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train | load_table | Load a table from a given file.
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filename : str
File to read
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filename : str
File to read
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-------
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filename : str
File to read
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train | write_table | Write a table to a file.
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table : Table
Table to be written
filename : str
Destination for saving table.
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Write a table to a file.
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table : Table
Table to be written
filename : str
Destination for saving table.
Returns
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None
"""
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Write a table to a file.
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table : Table
Table to be written
filename : str
Destination for saving table.
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None
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train | table_to_source_list | Convert a table of data into a list of sources.
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:class:`AegeanTools.models.OutputSource`, :class:`AegeanTools.models.SimpleSource`,
or :class:`AegeanTools.models.IslandSource`.
Parameters
----------
... | AegeanTools/catalogs.py | def table_to_source_list(table, src_type=OutputSource):
"""
Convert a table of data into a list of sources.
A single table must have consistent source types given by src_type. src_type should be one of
:class:`AegeanTools.models.OutputSource`, :class:`AegeanTools.models.SimpleSource`,
or :class:`Ae... | def table_to_source_list(table, src_type=OutputSource):
"""
Convert a table of data into a list of sources.
A single table must have consistent source types given by src_type. src_type should be one of
:class:`AegeanTools.models.OutputSource`, :class:`AegeanTools.models.SimpleSource`,
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train | write_catalog | Write a catalog (list of sources) to a file with format determined by extension.
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Write a catalog (list of sources) to a file with format determined by extension.
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train | writeFITSTable | Convert a table into a FITSTable and then write to disk.
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Filename to write.
table : Table
Table to write.
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Due to a bug in numpy, `int32` and `float32` are converted to `int64` and `float64` ... | AegeanTools/catalogs.py | def writeFITSTable(filename, table):
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Convert a table into a FITSTable and then write to disk.
Parameters
----------
filename : str
Filename to write.
table : Table
Table to write.
Returns
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None
Notes
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filename : str
Filename to write.
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Write an output file in ds9 .reg format that outlines the boundaries of each island.
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Filename to write.
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Filename to write.
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train | writeDB | Output an sqlite3 database containing one table for each source type
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Output filename
catalog : list
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Output an sqlite3 database containing one table for each source type
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filename : str
Output filename
catalog : list
List of sources of type :class:`AegeanTools.models.OutputSource`,
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Output an sqlite3 database containing one table for each source type
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Output filename
catalog : list
List of sources of type :class:`AegeanTools.models.OutputSource`,
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train | norm_dist | Calculate the normalised distance between two sources.
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Calculate the normalised distance between two sources.
Sources are elliptical Gaussians.
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Calculate the normalised distance between two sources.
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Great circle distance between two sources.
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Parameters
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src1, src2 : object
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Great circle distance between two sources.
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train | pairwise_ellpitical_binary | Do a pairwise comparison of all sources and determine if they have a normalized distance within
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Form this into a matrix of shape NxN.
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sources : list
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Do a pairwise comparison of all sources and determine if they have a normalized distance within
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Form this into a matrix of shape NxN.
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train | regroup_vectorized | Regroup the islands of a catalog according to their normalised distance.
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Return a list of island groups.
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srccat : np.rec.arry or pd.DataFrame
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ra[deg],dec[deg], a[arcsec],b... | AegeanTools/cluster.py | def regroup_vectorized(srccat, eps, far=None, dist=norm_dist):
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Regroup the islands of a catalog according to their normalised distance.
Assumes srccat is recarray-like for efficiency.
Return a list of island groups.
Parameters
----------
srccat : np.rec.arry or pd.DataFrame
Sho... | def regroup_vectorized(srccat, eps, far=None, dist=norm_dist):
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Regroup the islands of a catalog according to their normalised distance.
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srccat : np.rec.arry or pd.DataFrame
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train | regroup | Regroup the islands of a catalog according to their normalised distance.
Return a list of island groups. Sources have their (island,source) parameters relabeled.
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catalog : str or object
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Regroup the islands of a catalog according to their normalised distance.
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If filename is already an HDUList return that instead
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filename : str or HDUList
File or HDU to be loaded
Returns
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hdulist : HDUList | AegeanTools/fits_interp.py | def load_file_or_hdu(filename):
"""
Load a file from disk and return an HDUList
If filename is already an HDUList return that instead
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----------
filename : str or HDUList
File or HDU to be loaded
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-------
hdulist : HDUList
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Load a file from disk and return an HDUList
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filename : str or HDUList
File or HDU to be loaded
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hdulist : HDUList
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train | compress | Compress a file using decimation.
Parameters
----------
datafile : str or HDUList
Input data to be loaded. (HDUList will be modified if passed).
factor : int
Decimation factor.
outfile : str
File to be written. Default = None, which means don't write a file.
Returns
... | AegeanTools/fits_interp.py | def compress(datafile, factor, outfile=None):
"""
Compress a file using decimation.
Parameters
----------
datafile : str or HDUList
Input data to be loaded. (HDUList will be modified if passed).
factor : int
Decimation factor.
outfile : str
File to be written. Defa... | def compress(datafile, factor, outfile=None):
"""
Compress a file using decimation.
Parameters
----------
datafile : str or HDUList
Input data to be loaded. (HDUList will be modified if passed).
factor : int
Decimation factor.
outfile : str
File to be written. Defa... | [
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train | expand | Expand and interpolate the given data file using the given method.
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Parameters
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Expand and interpolate the given data file using the given method.
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Expand and interpolate the given data file using the given method.
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train | PostgresKernel.change_autocommit_mode | Strip and make a string case insensitive and ensure it is either 'true' or 'false'.
If neither, prompt user for either value.
When 'true', return True, and when 'false' return False. | postgres_kernel/kernel.py | def change_autocommit_mode(self, switch):
"""
Strip and make a string case insensitive and ensure it is either 'true' or 'false'.
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When 'true', return True, and when 'false' return False.
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parsed_switch = switch.strip().lower()... | def change_autocommit_mode(self, switch):
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Strip and make a string case insensitive and ensure it is either 'true' or 'false'.
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When 'true', return True, and when 'false' return False.
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train | armor | Returns a string in ASCII Armor format, for the given binary data. The
output of this is compatiple with pgcrypto's armor/dearmor functions. | pgcrypto/base.py | def armor(data, versioned=True):
"""
Returns a string in ASCII Armor format, for the given binary data. The
output of this is compatiple with pgcrypto's armor/dearmor functions.
"""
template = '-----BEGIN PGP MESSAGE-----\n%(headers)s%(body)s\n=%(crc)s\n-----END PGP MESSAGE-----'
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"""
Returns a string in ASCII Armor format, for the given binary data. The
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template = '-----BEGIN PGP MESSAGE-----\n%(headers)s%(body)s\n=%(crc)s\n-----END PGP MESSAGE-----'
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train | dearmor | Given a string in ASCII Armor format, returns the decoded binary data.
If verify=True (the default), the CRC is decoded and checked against that
of the decoded data, otherwise it is ignored. If the checksum does not
match, a BadChecksumError exception is raised. | pgcrypto/base.py | def dearmor(text, verify=True):
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Given a string in ASCII Armor format, returns the decoded binary data.
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... | def dearmor(text, verify=True):
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Given a string in ASCII Armor format, returns the decoded binary data.
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train | unpad | Takes the last character of the text, and if it is less than the block_size,
assumes the text is padded, and removes any trailing zeros or bytes with the
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Takes the last character of the text, and if it is less than the block_size,
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Takes the last character of the text, and if it is less than the block_size,
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train | pad | Given a text string and a block size, pads the text with bytes of the same value
as the number of padding bytes. This is the recommended method, and the one used
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"""
Given a text string and a block size, pads the text with bytes of the same value
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"""
num = bl... | def pad(text, block_size, zero=False):
"""
Given a text string and a block size, pads the text with bytes of the same value
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num = bl... | [
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train | aes_pad_key | AES keys must be either 16, 24, or 32 bytes long. If a key is provided that is not
one of these lengths, pad it with zeroes (this is what pgcrypto does). | pgcrypto/base.py | def aes_pad_key(key):
"""
AES keys must be either 16, 24, or 32 bytes long. If a key is provided that is not
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"""
if len(key) in (16, 24, 32):
return key
if len(key) < 16:
return pad(key, 16, zero=True)
eli... | def aes_pad_key(key):
"""
AES keys must be either 16, 24, or 32 bytes long. If a key is provided that is not
one of these lengths, pad it with zeroes (this is what pgcrypto does).
"""
if len(key) in (16, 24, 32):
return key
if len(key) < 16:
return pad(key, 16, zero=True)
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train | BaseEncryptedField.deconstruct | Deconstruct the field for Django 1.7+ migrations. | pgcrypto/fields.py | def deconstruct(self):
"""
Deconstruct the field for Django 1.7+ migrations.
"""
name, path, args, kwargs = super(BaseEncryptedField, self).deconstruct()
kwargs.update({
#'key': self.cipher_key,
'cipher': self.cipher_name,
'charset': self.chars... | def deconstruct(self):
"""
Deconstruct the field for Django 1.7+ migrations.
"""
name, path, args, kwargs = super(BaseEncryptedField, self).deconstruct()
kwargs.update({
#'key': self.cipher_key,
'cipher': self.cipher_name,
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train | BaseEncryptedField.get_cipher | Return a new Cipher object for each time we want to encrypt/decrypt. This is because
pgcrypto expects a zeroed block for IV (initial value), but the IV on the cipher
object is cumulatively updated each time encrypt/decrypt is called. | pgcrypto/fields.py | def get_cipher(self):
"""
Return a new Cipher object for each time we want to encrypt/decrypt. This is because
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object is cumulatively updated each time encrypt/decrypt is called.
"""
return s... | def get_cipher(self):
"""
Return a new Cipher object for each time we want to encrypt/decrypt. This is because
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object is cumulatively updated each time encrypt/decrypt is called.
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train | find_packages_by_root_package | Better than excluding everything that is not needed,
collect only what is needed. | setup.py | def find_packages_by_root_package(where):
"""Better than excluding everything that is not needed,
collect only what is needed.
"""
root_package = os.path.basename(where)
packages = [ "%s.%s" % (root_package, sub_package)
for sub_package in find_packages(where)]
packages.insert(0... | def find_packages_by_root_package(where):
"""Better than excluding everything that is not needed,
collect only what is needed.
"""
root_package = os.path.basename(where)
packages = [ "%s.%s" % (root_package, sub_package)
for sub_package in find_packages(where)]
packages.insert(0... | [
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