atomcloud.utils package

Submodules

• atomcloud.utils.check_utils module
  • check_1d_array()
  • check_2d_array()
  • check_2d_coords()
• atomcloud.utils.fit_utils module
  • approximate_jonquieress_function()
  • calc_diff_elements()
  • coordinate_transformation2D()
  • generate_elliptical_mask2D()
  • get_array_bounds()
  • get_lab_widths()
  • get_masked_data()
  • get_wrapped_angle()
  • is_nested_list()
  • polylog_val()
  • rotate_coordinates2D()
  • translate_coordinates2D()
• atomcloud.utils.img_utils module
  • aoi_area()
  • aoi_coordinates()
  • crop_data()
  • crop_image_data()
  • get_coordinates()
  • get_fit_data()
  • img_aoi_data()
  • img_data_to_sums()
  • sum_data_mask()
  • sum_img_data()
  • tuple_coords1d()
• atomcloud.utils.mask_utils module
  • find_square_mask()
• atomcloud.utils.uncertain_utils module
  • get_lab_widths()
  • nominal_list()
  • recursively_convert_nominal()

Module contents

Created on Mon Mar 14 19:26:59 2022

@author: hofer

atomcloud.utils.aoi_area(xmin, ymin, xmax, ymax)

atomcloud.utils.aoi_coordinates(aoi)

atomcloud.utils.approximate_jonquieress_function(z, gamma, n_max=10)

atomcloud.utils.calc_diff_elements(coords)

Calculate the difference between each element in the x and y arrays. This is used to calculate the average pixel size along each axis.

atomcloud.utils.check_1d_array(array)

atomcloud.utils.check_2d_array(array)

atomcloud.utils.check_2d_coords(coords)

atomcloud.utils.coordinate_transformation2D(XY_tuple, x0=0, y0=0, theta=0)

Transforms coordinates by first performing a translation and then a rotation

atomcloud.utils.crop_data(data, xmin, ymin, xmax, ymax)

atomcloud.utils.crop_image_data(aoi, img_data, XY_tuple)

atomcloud.utils.find_square_mask(mask)

Find the square mask that completely encompasses the elliptical mask.

Parameters:

• mask (np.ndarray) – The elliptical mask.

• Returns – np.ndarray: The square mask.

Return type:

ndarray

atomcloud.utils.generate_elliptical_mask2D(XY_tuple, x0, y0, sig_x, sig_y, theta, scale=1)

Currently does mask edge at wx (2 * sigmax), but change it to sigmax

atomcloud.utils.get_array_bounds(data)

atomcloud.utils.get_coordinates(shape)

Returns meshgrid of x and y coordinates of shape

Parameters:

shape (tuple) – shape of image

Returns:

meshgrid of x and y coordinates

Return type:

tuple

atomcloud.utils.get_fit_data(img, aoi)

atomcloud.utils.get_lab_widths(px, py, theta)

Given two orthogonal parameters which are rotated by theta with respect to the x and y axes, this function returns the widths in the lab frame.

Parameters:

• px – x width

• py – y width

• theta – angle in radians

Returns:

x and y widths in the lab frame

Return type:

list

atomcloud.utils.get_masked_data(XY_tuple, data, mask)

atomcloud.utils.get_wrapped_angle(angle, angle_range=3.141592653589793, min_angle=-1.5707963267948966)

wrap angles to be within a certain angle range

atomcloud.utils.img_aoi_data(img, aoi)

atomcloud.utils.img_data_to_sums(XY_tuple, data, mask=None)

atomcloud.utils.is_nested_list(obj, level)

atomcloud.utils.nominal_list(param_list)

atomcloud.utils.nominal_value(x)

Return the nominal value of x if it is a quantity with uncertainty (i.e., an AffineScalarFunc object); otherwise, returns x unchanged.

This utility function is useful for transforming a series of numbers, when only some of them generally carry an uncertainty.

atomcloud.utils.polylog_val(z, gamma, n_max=100)

atomcloud.utils.recursively_convert_nominal(param_list)

atomcloud.utils.rotate_coordinates2D(coordinates, theta)

Rotates coordinates by theta radians

Parameters:

• coordinates (tuple[numpy.ndarray, numpy.ndarray]) – tuple of x and y coordinates

• theta (float) – angle in radians

Returns:

rotated x and y coordinates

Return type:

tuple

atomcloud.utils.sum_data_mask(x, y, data, mask=None)

atomcloud.utils.sum_img_data(data, mask=None)

atomcloud.utils.translate_coordinates2D(coords, x0, y0)

Translates coordinates by x0 and y0

atomcloud.utils.tuple_coords1d(XY_tuple)