ptyrad.utils.image_proc

Image processing tools for fitting, cropping, normalization, etc.

Functions

center_crop(image, crop_height, crop_width)	Center crops a 2D or 3D array (e.g., an image).
create_one_hot_mask(image, percentile)
exponential_decay(r, a, b)
fit_background(image, mask[, fit_type])
fit_cbed_pattern(image[, initial_guess])	Estimate the center, radius, and std of a CBED pattern by minimizing the difference between the observed image and a synthetic model.
get_blob_size(dx, blob[, output, plot_profile])
guess_radius_of_bright_field_disk(image[, ...])	Utility function that returns an estimate of the radius of rbf from CBED
make_gaussian_mask(Npix, radius, std[, center])	Create a 2D Gaussian-blurred circular mask.
mfft2(im)
normalize_by_bit_depth(arr, bit_depth)
normalize_from_zero_to_one(arr)
power_law(r, a, b)

ptyrad.utils.image_proc.get_blob_size(dx, blob, output='d90', plot_profile=False)

ptyrad.utils.image_proc.guess_radius_of_bright_field_disk(image, thresh=0.5)

Utility function that returns an estimate of the radius of rbf from CBED

Parameters:

• image (ndarray)

• thresh (float)

ptyrad.utils.image_proc.fit_cbed_pattern(image, initial_guess=None)

Estimate the center, radius, and std of a CBED pattern by minimizing the difference between the observed image and a synthetic model.

Parameters:

• image (np.ndarray) – The input image to fit.

• initial_guess (dict, optional) – Dictionary with initial guess parameters.

Returns:

Dictionary containing the fitted parameters as dict[‘center’, ‘radius’, ‘std’].

Return type:

dict

ptyrad.utils.image_proc.make_gaussian_mask(Npix, radius, std, center=None)

Create a 2D Gaussian-blurred circular mask.

Parameters:

• Npix (int) – Size of the square mask (Npix x Npix).

• radius (float) – Radius of the circular mask.

• std (float) – Standard deviation of the Gaussian blur.

• center (tuple) – (y, x) coordinates of the center of the circle.

Returns:

A 2D Gaussian-blurred circular mask.

Return type:

np.ndarray

ptyrad.utils.image_proc.center_crop(image, crop_height, crop_width, offset=(0, 0))

Center crops a 2D or 3D array (e.g., an image).

Parameters:

• image (numpy.ndarray) – The input array to crop. Can be 2D (H, W) or 3D (H, W, C).

• crop_height (int) – The desired height of the crop.

• crop_width (int) – The desired width of the crop.

Returns:

The cropped image.

Return type:

numpy.ndarray

ptyrad.utils.image_proc.mfft2(im)

ptyrad.utils.image_proc.normalize_from_zero_to_one(arr)

ptyrad.utils.image_proc.normalize_by_bit_depth(arr, bit_depth)

ptyrad.utils.image_proc.create_one_hot_mask(image, percentile)

ptyrad.utils.image_proc.fit_background(image, mask, fit_type='exp')

ptyrad.utils.image_proc.exponential_decay(r, a, b)

ptyrad.utils.image_proc.power_law(r, a, b)