prysm.degredations¶
Degredations in the image chain.

class
prysm.degredations.
Smear
(width, angle=0)¶ Bases:
prysm.convolution.Convolvable
Smear (motion blur).

analytic_ft
(x, y)¶ Analytic FT of the smear.
 Parameters
x (numpy.ndarray) – x Cartesian spatial frequency, cy/um
y (numpy.ndarray) – y Cartesian spatial frequency, cy/um
 Returns
analytical FT of the smear.
 Return type
numpy.ndarray

center_x
¶ Center “pixel” in x.

center_y
¶ Center “pixel” in y.

conv
(other)¶ Convolves this convolvable with another.
 Parameters
other (Convolvable) – A convolvable object
 Returns
a convolvable object
 Return type
Convolvable
Notes
If self and other both have analytic Fourier transforms, no math will be done and the aFTs are merged directly.
If only one of self or other has an analytic Fourier transform, the output grid will be defined by the object which does not have an analytic Fourier transform.
If neither has an analytic transform, the output grid will:  span max(self.support, other.support)  have sample spacing min(self.sample_spacing, other.sample_spacing)
This ensures the signal remains Nyquist sampled and (probably) doesn’t expand beyond the extent of the output window. The latter condition will be violated when two large convolvables are convolved.

copy
()¶ Return a (deep) copy of this instance.

deconv
(other, balance=1000, reg=None, is_real=True, clip=False, postnormalize=True)¶ Perform the deconvolution of this convolvable object by another.
 Parameters
other (Convolvable) – another convolvable object, used as the PSF in a Wiener deconvolution
balance (float, optional) – regularization parameter; passed through to skimage
reg (numpy.ndarray, optional) – regularization operator, passed through to skimage
is_real (bool, optional) – True if self and other are both real
clip (bool, optional) – clips self and other into (0,1)
postnormalize (bool, optional) – normalize the result such that it falls in [0,1]
 Returns
a new Convolable object
 Return type
Convolvable
Notes
See skimage: http://scikitimage.org/docs/dev/api/skimage.restoration.html#skimage.restoration.wiener

static
from_file
(path, scale)¶ Read a monochrome 8 bit per pixel file into a new Image instance.
 Parameters
path (string) – path to a file
scale (float) – pixel scale, in microns
 Returns
a new image object
 Return type
Convolvable

plot_slice_xy
(axlim=20, lw=3, zorder=3, fig=None, ax=None)¶ Create a plot of slices through the X and Y axes of the PSF.
 Parameters
axlim (float or int, optional) – axis limits, in microns
lw (float, optional) – line width
zorder (int, optional) – zorder
fig (matplotlib.figure.Figure, optional) – Figure to draw plot in
ax (matplotlib.axes.Axis) – Axis to draw plot in
 Returns
fig (matplotlib.figure.Figure, optional) – Figure containing the plot
ax (matplotlib.axes.Axis, optional) – Axis containing the plot

renorm
()¶ Renormalize so that the peak is at a value of unity.

sample_spacing
¶ centertocenter sample spacing.

samples_x
¶ Number of samples in the x dimension.

samples_y
¶ Number of samples in the y dimension.

save
(path, nbits=8)¶ Write the image to a png, jpg, tiff, etc.
 Parameters
path (string) – path to write the image to
nbits (int) – number of bits in the output image

shape
¶ Proxy to phase or data shape.

show
(xlim=None, ylim=None, interp_method=None, power=1, show_colorbar=True, fig=None, ax=None)¶ Display the image.
 Parameters
xlim (iterable, optional) – x axis limits
ylim (iterable,) – y axis limits
interp_method (string) – interpolation technique used in display
power (float) – inverse of power to stretch image by. E.g. power=2 will plot img ** (1/2)
show_colorbar (bool) – whether to show the colorbar or not.
fig (matplotlib.figure.Figure, optional:) – Figure containing the plot
ax (matplotlib.axes.Axis, optional:) – Axis containing the plot
 Returns
fig (matplotlib.figure.Figure, optional:) – Figure containing the plot
ax (matplotlib.axes.Axis, optional:) – Axis containing the plot

show_fourier
(freq_x=None, freq_y=None, interp_method='lanczos', fig=None, ax=None)¶ Display the fourier transform of the image.
 Parameters
interp_method (string) – method used to interpolate the data for display.
freq_x (iterable) – x frequencies to use for convolvable with analytical FT and no data
freq_y (iterable) – y frequencies to use for convolvable with analytic FT and no data
fig (matplotlib.figure.Figure) – Figure containing the plot
ax (matplotlib.axes.Axis) – Axis containing the plot
 Returns
fig (matplotlib.figure.Figure) – Figure containing the plot
ax (matplotlib.axes.Axis) – Axis containing the plot
Notes
freq_x and freq_y are unused when the convolvable has a .data field.

size
¶ Proxy to phase or data size.

slice_x
¶ Retrieve a slice through the X axis of the phase.
 Returns
self.unit (numpy.ndarray) – ordinate axis
slice of self.phase or self.data (numpy.ndarray)

slice_y
¶ Retrieve a slice through the Y axis of the phase.
 Returns
self.unit (numpy.ndarray) – ordinate axis
slice of self.phase or self.data (numpy.ndarray)

support
¶ Width of the domain.

support_x
¶ Width of the domain in X.

support_y
¶ Width of the domain in Y.


class
prysm.degredations.
Jitter
(scale, sample_spacing=None, samples=None)¶ Bases:
prysm.convolution.Convolvable
Jitter (high frequency motion).

analytic_ft
(x, y)¶ Analytic FT of jitter.
 Parameters
x (numpy.ndarray) – x Cartesian spatial frequency, units of cy/um
y (numpy.ndarray) – y Cartesian spatial frequency, units of cy/um
 Returns
value of analytic FT
 Return type
numpy.ndarray

center_x
¶ Center “pixel” in x.

center_y
¶ Center “pixel” in y.

conv
(other)¶ Convolves this convolvable with another.
 Parameters
other (Convolvable) – A convolvable object
 Returns
a convolvable object
 Return type
Convolvable
Notes
If self and other both have analytic Fourier transforms, no math will be done and the aFTs are merged directly.
If only one of self or other has an analytic Fourier transform, the output grid will be defined by the object which does not have an analytic Fourier transform.
If neither has an analytic transform, the output grid will:  span max(self.support, other.support)  have sample spacing min(self.sample_spacing, other.sample_spacing)
This ensures the signal remains Nyquist sampled and (probably) doesn’t expand beyond the extent of the output window. The latter condition will be violated when two large convolvables are convolved.

copy
()¶ Return a (deep) copy of this instance.

deconv
(other, balance=1000, reg=None, is_real=True, clip=False, postnormalize=True)¶ Perform the deconvolution of this convolvable object by another.
 Parameters
other (Convolvable) – another convolvable object, used as the PSF in a Wiener deconvolution
balance (float, optional) – regularization parameter; passed through to skimage
reg (numpy.ndarray, optional) – regularization operator, passed through to skimage
is_real (bool, optional) – True if self and other are both real
clip (bool, optional) – clips self and other into (0,1)
postnormalize (bool, optional) – normalize the result such that it falls in [0,1]
 Returns
a new Convolable object
 Return type
Convolvable
Notes
See skimage: http://scikitimage.org/docs/dev/api/skimage.restoration.html#skimage.restoration.wiener

static
from_file
(path, scale)¶ Read a monochrome 8 bit per pixel file into a new Image instance.
 Parameters
path (string) – path to a file
scale (float) – pixel scale, in microns
 Returns
a new image object
 Return type
Convolvable

plot_slice_xy
(axlim=20, lw=3, zorder=3, fig=None, ax=None)¶ Create a plot of slices through the X and Y axes of the PSF.
 Parameters
axlim (float or int, optional) – axis limits, in microns
lw (float, optional) – line width
zorder (int, optional) – zorder
fig (matplotlib.figure.Figure, optional) – Figure to draw plot in
ax (matplotlib.axes.Axis) – Axis to draw plot in
 Returns
fig (matplotlib.figure.Figure, optional) – Figure containing the plot
ax (matplotlib.axes.Axis, optional) – Axis containing the plot

renorm
()¶ Renormalize so that the peak is at a value of unity.

sample_spacing
¶ centertocenter sample spacing.

samples_x
¶ Number of samples in the x dimension.

samples_y
¶ Number of samples in the y dimension.

save
(path, nbits=8)¶ Write the image to a png, jpg, tiff, etc.
 Parameters
path (string) – path to write the image to
nbits (int) – number of bits in the output image

shape
¶ Proxy to phase or data shape.

show
(xlim=None, ylim=None, interp_method=None, power=1, show_colorbar=True, fig=None, ax=None)¶ Display the image.
 Parameters
xlim (iterable, optional) – x axis limits
ylim (iterable,) – y axis limits
interp_method (string) – interpolation technique used in display
power (float) – inverse of power to stretch image by. E.g. power=2 will plot img ** (1/2)
show_colorbar (bool) – whether to show the colorbar or not.
fig (matplotlib.figure.Figure, optional:) – Figure containing the plot
ax (matplotlib.axes.Axis, optional:) – Axis containing the plot
 Returns
fig (matplotlib.figure.Figure, optional:) – Figure containing the plot
ax (matplotlib.axes.Axis, optional:) – Axis containing the plot

show_fourier
(freq_x=None, freq_y=None, interp_method='lanczos', fig=None, ax=None)¶ Display the fourier transform of the image.
 Parameters
interp_method (string) – method used to interpolate the data for display.
freq_x (iterable) – x frequencies to use for convolvable with analytical FT and no data
freq_y (iterable) – y frequencies to use for convolvable with analytic FT and no data
fig (matplotlib.figure.Figure) – Figure containing the plot
ax (matplotlib.axes.Axis) – Axis containing the plot
 Returns
fig (matplotlib.figure.Figure) – Figure containing the plot
ax (matplotlib.axes.Axis) – Axis containing the plot
Notes
freq_x and freq_y are unused when the convolvable has a .data field.

size
¶ Proxy to phase or data size.

slice_x
¶ Retrieve a slice through the X axis of the phase.
 Returns
self.unit (numpy.ndarray) – ordinate axis
slice of self.phase or self.data (numpy.ndarray)

slice_y
¶ Retrieve a slice through the Y axis of the phase.
 Returns
self.unit (numpy.ndarray) – ordinate axis
slice of self.phase or self.data (numpy.ndarray)

support
¶ Width of the domain.

support_x
¶ Width of the domain in X.

support_y
¶ Width of the domain in Y.
