|
| SMS_BP.simulate_foci.get_lengths (str track_distribution, int track_length_mean, int total_tracks) |
|
dict | SMS_BP.simulate_foci.create_condensate_dict (np.ndarray initial_centers, np.ndarray initial_scale, np.ndarray diffusion_coefficient, np.ndarray hurst_exponent, np.ndarray cell_space, float cell_axial_range, **kwargs) |
|
| SMS_BP.simulate_foci.tophat_function_2d (var, center, radius, bias_subspace, space_prob, **kwargs) |
|
| SMS_BP.simulate_foci.generate_points (pdf, total_points, min_x, max_x, center, radius, bias_subspace_x, space_prob, density_dif) |
|
| SMS_BP.simulate_foci.generate_points_from_cls (pdf, total_points, min_x, max_x, min_y, max_y, min_z, max_z, density_dif) |
|
| SMS_BP.simulate_foci.generate_radial_points (total_points, center, radius) |
|
| SMS_BP.simulate_foci.generate_sphere_points (total_points, center, radius) |
|
| SMS_BP.simulate_foci.radius_spherical_cap (R, center, z_slice) |
|
| SMS_BP.simulate_foci.get_gaussian (mu, sigma, domain=[list(range(10)), list(range(10))]) |
|
float|np.ndarray | SMS_BP.simulate_foci.axial_intensity_factor (float|np.ndarray abs_axial_pos, float detection_range, **kwargs) |
|
np.ndarray | SMS_BP.simulate_foci.generate_map_from_points (np.ndarray points, float|np.ndarray point_intensity, np.ndarray|None map, bool movie, float base_noise, float psf_sigma) |
|