Collaboration diagram for laospy.metapupil_I9.MetaPupil:
Public Member Functions | |
| def | set_image (self, image, setup='SE') |
| def | find_centers (self, boxSize=40, medianSubtract=True, gauss=False) |
| def | create_mask (self, mask) |
| def | create_circular_pupil_mask (self, radius) |
| def | create_metapupil_mask (self, snr=100, radius=16) |
| def | find_mask_diameter (self) |
| def | get_mask (self) |
| def | delete_mask (self) |
| def | calculate_tilt (self) |
| def | calculate_flux (self) |
| def | calculate_background (self, radius) |
| def | create_zernike_reconstruction_matrix (self, maxmode, diam=None, rcond=1e-15) |
| def | calculate_slopes (self, normalization='subaperture') |
| def | set_zernike_conversion_factors (self, conversionFactors) |
| def | find_zernike_coefficients (self) |
| def | set_image (self, image, setup='SE') |
| def | find_centers (self, boxSize=40, medianSubtract=True, gauss=False) |
| def | create_mask (self, mask) |
| def | create_circular_pupil_mask (self, radius) |
| def | create_metapupil_mask (self, snr=100, radius=16) |
| def | find_mask_diameter (self) |
| def | get_mask (self) |
| def | delete_mask (self) |
| def | calculate_tilt (self) |
| def | calculate_flux (self) |
| def | calculate_background (self, radius) |
| def | create_zernike_reconstruction_matrix (self, maxmode, diam=None, rcond=1e-15) |
| def | calculate_slopes (self, normalization='subaperture') |
| def | set_zernike_conversion_factors (self, conversionFactors) |
| def | find_zernike_coefficients (self) |
Public Attributes | |
| setup | |
| mask | |
Static Public Attributes | |
| img = None | |
| string | setup = '' |
| quadrants = None | |
| float | centers = np.ones((4,2)) * 20.0 |
| meancenter = np.zeros(2) | |
| int | mask = 0 |
| maskcenters = np.zeros((4,2)) | |
| pyramidAngle = None | |
| slopes = None | |
| recMat = None | |
| zernikeCoeffs = None | |
| zernikeConvFactors = None | |
| int | noise = 0. |
| unmaskPositions = np.zeros(1600) | |
| illuminatedPositions = np.zeros(1600) | |
| metapupilMask = np.zeros((40,40)) | |
| illuminatedMask = np.zeros((40,40)) | |
Detailed Description
An MetaPupil object represents a measurement of the wavefront in the conjugated plane of
a pyramid wavefront sensor. The a metapupil measurement consists of an image with slope
information for each subaperture distributed across the 4 quadrants of the image. Each
subaperture is associated with 4 pixels, one in each quadrant. The gradient between the 4
associated pixels is the measurement of the slope of the wavefront in the corresponding
subaperture.
The association of the subaperture pixels is achieved by placing the same mask on each of the 4
quadrants. The pixels that are masked do not contain a useable signal. The mask also defines
the order of the subapertures.
During alignment it is necessary to introduce a mask in the optical path and/or measure
without a star enlarger in the optical path. Both affect the distribution of the signal on
the CCD. The setup attribute reflects the setup, with which the image is taken.
Attributes
----------
img : ndarray
the image
setup : string
the image type. can be 'SE', SE+mask', 'noSE+mask'
quadrants : ndarray (size: 4, imgsize/2, imgsize/2)
masked array cube with the quadrants of the image
centers : ndarray (size: 4,2)
the centers of the brightness distributions in the 4 quadrants
meancenter : ndarray
the mean center for all quadrants
mask : ndarray (bool)
the mask that is applied on quadrants
maskcenters : ndarray (size: 4, 2)
the coordinate of the pixel in each quadrant on which the mask is centered
slopes : ndarray
the slopes vector (sx0,sy0,sx1,sy1,...)
recMat : ndarray
the slopes-to-modes reconstruction matrix
zernikeCoeffs : ndarray
the reconstructed coefficients for each Zernike mode
zernikeConvFactors : ndarray
conversion factors to scale the zernikeCoeffs
Member Function Documentation
◆ calculate_background() [1/2]
| def laospy.metapupil_I9.MetaPupil.calculate_background | ( | self, | |
| radius | |||
| ) |
Determines the mean per-pixel background and its standard deviation in the image.
The background is determined outside circular avoidance regions in each quadrant.
Parameters
----------
radius : float
avoidance radius. Circular region to exclude in the determination of the background
Returns
-------
mean, std : tuple of floats
mean and standard deviation of background
◆ calculate_background() [2/2]
| def laospy.metapupil_I9.MetaPupil.calculate_background | ( | self, | |
| radius | |||
| ) |
Determines the mean per-pixel background and its standard deviation in the image.
The background is determined outside circular avoidance regions in each quadrant.
Parameters
----------
radius : float
avoidance radius. Circular region to exclude in the determination of the background
Returns
-------
mean, std : tuple of floats
mean and standard deviation of background
◆ calculate_flux() [1/2]
| def laospy.metapupil_I9.MetaPupil.calculate_flux | ( | self | ) |
◆ calculate_flux() [2/2]
| def laospy.metapupil_I9.MetaPupil.calculate_flux | ( | self | ) |
◆ calculate_slopes() [1/2]
| def laospy.metapupil_I9.MetaPupil.calculate_slopes | ( | self, | |
normalization = 'subaperture' |
|||
| ) |
Calculates the slope vector based on the pixels that are not masked
Slopes are sorted as sx0, sy0, sx1, sy1, ...
Parameters
----------
normalization : string
Defines the normaization method for the slopes. Possible values:
"subaperture" : normalization with the total flux of the 4 slope pixels belonging
to a subaperture
"metapupil" : normalization with the total flux in all slope pixels
"none" : no normalization
◆ calculate_slopes() [2/2]
| def laospy.metapupil_I9.MetaPupil.calculate_slopes | ( | self, | |
normalization = 'subaperture' |
|||
| ) |
Calculates the slope vector based on the pixels that are not masked
Slopes are sorted as sx0, sy0, sx1, sy1, ...
Parameters
----------
normalization : string
Defines the normaization method for the slopes. Possible values:
"subaperture" : normalization with the total flux of the 4 slope pixels belonging
to a subaperture
"metapupil" : normalization with the total flux in all slope pixels
"none" : no normalization
◆ calculate_tilt() [1/2]
| def laospy.metapupil_I9.MetaPupil.calculate_tilt | ( | self | ) |
Evaluates tip/tilt on based on the flux in each quadrant.
If a mask is defined, only the flux in the mask is considered
Returns
-------
tilt_x, tilt_y : tuple of floats
tilt values in arbitrary units
◆ calculate_tilt() [2/2]
| def laospy.metapupil_I9.MetaPupil.calculate_tilt | ( | self | ) |
Evaluates tip/tilt on based on the flux in each quadrant.
If a mask is defined, only the flux in the mask is considered
Returns
-------
tilt_x, tilt_y : tuple of floats
tilt values in arbitrary units
◆ create_circular_pupil_mask() [1/2]
| def laospy.metapupil_I9.MetaPupil.create_circular_pupil_mask | ( | self, | |
| radius | |||
| ) |
Creates a circular pupil mask for each of the 4 quadrants
The mask will be centered on the full integer pixel that is nearest to the center position
determined in each quadrant.
It is important to maintain the same geometry of the mask (distribution of pixels per row)
in order to identify the 4 pixels that belong to each subaperture.
Parameters
----------
radius : float
radius of the circle in pixels
◆ create_circular_pupil_mask() [2/2]
| def laospy.metapupil_I9.MetaPupil.create_circular_pupil_mask | ( | self, | |
| radius | |||
| ) |
Creates a circular pupil mask for each of the 4 quadrants
The mask will be centered on the full integer pixel that is nearest to the center position
determined in each quadrant.
It is important to maintain the same geometry of the mask (distribution of pixels per row)
in order to identify the 4 pixels that belong to each subaperture.
Parameters
----------
radius : float
radius of the circle in pixels
◆ create_mask() [1/2]
| def laospy.metapupil_I9.MetaPupil.create_mask | ( | self, | |
| mask | |||
| ) |
Creates a general pupil mask for each of the 4 quadrants.
All non-zero elements will be masked
Parameters
----------
mask : ndarray
the mask of the same dimension as a quadrant
◆ create_mask() [2/2]
| def laospy.metapupil_I9.MetaPupil.create_mask | ( | self, | |
| mask | |||
| ) |
Creates a general pupil mask for each of the 4 quadrants.
All non-zero elements will be masked
Parameters
----------
mask : ndarray
the mask of the same dimension as a quadrant
◆ create_metapupil_mask() [1/2]
| def laospy.metapupil_I9.MetaPupil.create_metapupil_mask | ( | self, | |
snr = 100, |
|||
radius = 16 |
|||
| ) |
Creates a mask based on the illumination pattern in the image
The mask represents the region, in which the mean of all quadrants has a SNR below the
specified value.
Parameters
----------
snr : float
signal-to-noise ratio
radius : float
avoidance radius. Circular region to exclude in the determination of the noise level
◆ create_metapupil_mask() [2/2]
| def laospy.metapupil_I9.MetaPupil.create_metapupil_mask | ( | self, | |
snr = 100, |
|||
radius = 16 |
|||
| ) |
Creates a mask based on the illumination pattern in the image
The mask represents the region, in which the mean of all quadrants has a SNR below the
specified value.
Parameters
----------
snr : float
signal-to-noise ratio
radius : float
avoidance radius. Circular region to exclude in the determination of the noise level
◆ create_zernike_reconstruction_matrix() [1/2]
| def laospy.metapupil_I9.MetaPupil.create_zernike_reconstruction_matrix | ( | self, | |
| maxmode, | |||
diam = None, |
|||
rcond = 1e-15 |
|||
| ) |
creates the Zernike reconstruction Matrix for the given number of Zernike modes
For each mode a phase screen is created. The screen has to have a diameter which
circumvents the mask that is defined for quadrant 0. The gradient of each phase screen is
calculated. Then the slopes are determined for each subaperture defined by the mask. The
slopes vectors for all modes form the interaction matrix. The resulting
reconstruction matrix is the (Moore-Penrose) pseudo-inverse of the interaction matrix.
Note: the diameter of the array has to be odd, to have the Zernike polynomial centered on
a full pixel.
If not defined, the diameter of the phase screen is chosen automatically to be slightly
larger than the metapuil mask.
Parameters
----------
maxmode : integer
the maximum Zernike mode that will be considered in the reconstruction matrix
Note: J=1 (piston) will not be considered. Only modes J>1
diam : odd integer (optional)
the diameter in pixels the zernike modes should have. Cannot be smaller than the mask.
rcond : float
Cutoff for small singular values. Singular values smaller (in modulus) than
rcond * largest_singular_value (again, in modulus) are set to zero.
◆ create_zernike_reconstruction_matrix() [2/2]
| def laospy.metapupil_I9.MetaPupil.create_zernike_reconstruction_matrix | ( | self, | |
| maxmode, | |||
diam = None, |
|||
rcond = 1e-15 |
|||
| ) |
creates the Zernike reconstruction Matrix for the given number of Zernike modes
For each mode a phase screen is created. The screen has to have a diameter which
circumvents the mask that is defined for quadrant 0. The gradient of each phase screen is
calculated. Then the slopes are determined for each subaperture defined by the mask. The
slopes vectors for all modes form the interaction matrix. The resulting
reconstruction matrix is the (Moore-Penrose) pseudo-inverse of the interaction matrix.
Note: the diameter of the array has to be odd, to have the Zernike polynomial centered on
a full pixel.
If not defined, the diameter of the phase screen is chosen automatically to be slightly
larger than the metapuil mask.
Parameters
----------
maxmode : integer
the maximum Zernike mode that will be considered in the reconstruction matrix
Note: J=1 (piston) will not be considered. Only modes J>1
diam : odd integer (optional)
the diameter in pixels the zernike modes should have. Cannot be smaller than the mask.
rcond : float
Cutoff for small singular values. Singular values smaller (in modulus) than
rcond * largest_singular_value (again, in modulus) are set to zero.
◆ delete_mask() [1/2]
| def laospy.metapupil_I9.MetaPupil.delete_mask | ( | self | ) |
Deletes the metapupil mask, if it exists. This also deletes the Zernike reconstruction matrix and Zernike coefficients
◆ delete_mask() [2/2]
| def laospy.metapupil_I9.MetaPupil.delete_mask | ( | self | ) |
Deletes the metapupil mask, if it exists. This also deletes the Zernike reconstruction matrix and Zernike coefficients
◆ find_centers() [1/2]
| def laospy.metapupil_I9.MetaPupil.find_centers | ( | self, | |
boxSize = 40, |
|||
medianSubtract = True, |
|||
gauss = False |
|||
| ) |
Finds the centers of the brightness distributions in the image
If the image type is 'noSE+mask' the center is determined in the center of the image.
Otherwise centers are determined in each quadrant
Parameters
----------
boxSize : positive integer
the size of the box to compute the centroid. default value is 40
medianSubtract : bool
to subtract the median from the image or each quadrant
gauss : bool
if given will find the gaussian fit of the image passed and return the center
coordinates
◆ find_centers() [2/2]
| def laospy.metapupil_I9.MetaPupil.find_centers | ( | self, | |
boxSize = 40, |
|||
medianSubtract = True, |
|||
gauss = False |
|||
| ) |
Finds the centers of the brightness distributions in the image
If the image type is 'noSE+mask' the center is determined in the center of the image.
Otherwise centers are determined in each quadrant
Parameters
----------
boxSize : positive integer
the size of the box to compute the centroid. default value is 40
medianSubtract : bool
to subtract the median from the image or each quadrant
gauss : bool
if given will find the gaussian fit of the image passed and return the center
coordinates
◆ find_mask_diameter() [1/2]
| def laospy.metapupil_I9.MetaPupil.find_mask_diameter | ( | self | ) |
Determines the diameter of the circle that circumvents the mask defined in the quadrants Internally it calculates the distance of every pixel to the center of the metapupil mask and returns twice the largest distance
◆ find_mask_diameter() [2/2]
| def laospy.metapupil_I9.MetaPupil.find_mask_diameter | ( | self | ) |
Determines the diameter of the circle that circumvents the mask defined in the quadrants Internally it calculates the distance of every pixel to the center of the metapupil mask and returns twice the largest distance
◆ find_zernike_coefficients() [1/2]
| def laospy.metapupil_I9.MetaPupil.find_zernike_coefficients | ( | self | ) |
Reconstructs Zernike coefficients from measured slopes. A zernike reconstruction matrix has to be created before!. Conversion factors are applied, if set.
◆ find_zernike_coefficients() [2/2]
| def laospy.metapupil_I9.MetaPupil.find_zernike_coefficients | ( | self | ) |
Reconstructs Zernike coefficients from measured slopes. A zernike reconstruction matrix has to be created before!. Conversion factors are applied, if set.
◆ get_mask() [1/2]
| def laospy.metapupil_I9.MetaPupil.get_mask | ( | self | ) |
returns the mask for WFC Returns ------ mask : SeqDynamicBitset
◆ get_mask() [2/2]
| def laospy.metapupil_I9.MetaPupil.get_mask | ( | self | ) |
returns the mask for WFC Returns ------ mask : SeqDynamicBitset
◆ set_image() [1/2]
| def laospy.metapupil_I9.MetaPupil.set_image | ( | self, | |
| image, | |||
setup = 'SE' |
|||
| ) |
Sets a new image, rearranges it into quadrants. If defined: applies mask
Parameters
----------
image : ndarray
The image data
setup : string
describes the condition with which the image is taken. Possible values:
"SE" : Star Enlarger in place. a Metapupil images in each quadrant is
expected
"SE+mask" : Star Enlarger in place and a mask in the pupil or DM plane. A
peaked brightness distribution is expected in each quadrant
"noSE+mask" : No star enlarger is in the optical path. A mask is in the pupil or
DM plane. A peaked brightness distribution is expected in the center
of the image.
◆ set_image() [2/2]
| def laospy.metapupil_I9.MetaPupil.set_image | ( | self, | |
| image, | |||
setup = 'SE' |
|||
| ) |
Sets a new image, rearranges it into quadrants. If defined: applies mask
Parameters
----------
image : ndarray
The image data
setup : string
describes the condition with which the image is taken. Possible values:
"SE" : Star Enlarger in place. a Metapupil images in each quadrant is
expected
"SE+mask" : Star Enlarger in place and a mask in the pupil or DM plane. A
peaked brightness distribution is expected in each quadrant
"noSE+mask" : No star enlarger is in the optical path. A mask is in the pupil or
DM plane. A peaked brightness distribution is expected in the center
of the image.
◆ set_zernike_conversion_factors() [1/2]
| def laospy.metapupil_I9.MetaPupil.set_zernike_conversion_factors | ( | self, | |
| conversionFactors | |||
| ) |
Sets the conversion factors for each Zernike mode.
This allows to scale the fitted zernike coefficients into useful units such as steps or
mu. The array must have the same number of elements as Zernike modes considered in the
reconstruction matrix. Zernike mode J=1 is not considered; the first element corresponds
to J=2
Parameters
----------
conversionFactors : ndarray
array with conversion factors
◆ set_zernike_conversion_factors() [2/2]
| def laospy.metapupil_I9.MetaPupil.set_zernike_conversion_factors | ( | self, | |
| conversionFactors | |||
| ) |
Sets the conversion factors for each Zernike mode.
This allows to scale the fitted zernike coefficients into useful units such as steps or
mu. The array must have the same number of elements as Zernike modes considered in the
reconstruction matrix. Zernike mode J=1 is not considered; the first element corresponds
to J=2
Parameters
----------
conversionFactors : ndarray
array with conversion factors
Member Data Documentation
◆ centers
|
static |
◆ illuminatedMask
|
static |
◆ illuminatedPositions
|
static |
◆ img
|
static |
◆ mask [1/2]
|
static |
◆ mask [2/2]
| laospy.metapupil_I9.MetaPupil.mask |
◆ maskcenters
|
static |
◆ meancenter
|
static |
◆ metapupilMask
|
static |
◆ noise
|
static |
◆ pyramidAngle
|
static |
◆ quadrants
|
static |
◆ recMat
|
static |
◆ setup [1/2]
|
static |
◆ setup [2/2]
| laospy.metapupil_I9.MetaPupil.setup |
◆ slopes
|
static |
◆ unmaskPositions
|
static |
◆ zernikeCoeffs
|
static |
◆ zernikeConvFactors
|
static |
The documentation for this class was generated from the following file:
- /home/nirva/insroot/lib/python/site-packages/laospy/metapupil_I9.py
