API Reference¶
quanfima.morphology module¶
quanfima.simulation module¶
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quanfima.simulation.additive_noise(params, noise_lvl, smooth_lvl, use_median=True, median_rad=3)[source]¶ Contaminates datasets with a speficied additive Gaussian noise and smoothing level.
Contaminates the datasets (generated with generate_datasets function) with the specified level of additive Gaussian noise and smoothing, uneven illumination can be added by extracting blobs from params tuple with some other arguments.
- params : tuple
- Contains name, dataset_path, blobs, output_dir arguments passed from generate_noised_data.
- noise_level : float
- Indicates the standard deviations of noise.
- smooth_level : float
- Indicates the sigma value of Gaussian filter.
- use_median : boolean
- Specifies if the median filter should be applied after addition of noise.
- median_rad : integer
- Indicates the size of median filter.
- datasets_props : dict
- The dictionary containing the path to the reference dataset, the path to the contaminated dataset, the generated name, the SNR level, the precision, the recall and f1-score, and the level of noise and smoothing.
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quanfima.simulation.generate_blobs(volume_size, blob_size_fraction=0.1, transparency_ratio=0.5, sigma=90.0)[source]¶ Generates random blobs smoothed with Gaussian filter in a volume.
Generates several blobs of random size in a volume using function from scikit-image, which are subsequently smoothed with a Gaussian filter of a large sigma to imitate 3D uneven illumination of the volume.
- volume_size : tuple
- Indicates the size of the volume.
- blob_size_fraction : float
- Indicates the fraction of volume occupied by blobs.
- transparency_ratio : float
- Indicates the transparency of blobs in a range [0, 1].
- sigma : float
- Indicates the sigma of Gaussian filter.
- blobs_smeared : ndarray
- The volume with smoothed blobs of a specified transparency.
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quanfima.simulation.generate_datasets(volume_size=(512, 512, 512), n_fibers=50, radius_lim=(4, 10), length_lim=(0.2, 0.8), gap_lim=(3, 10), max_fails=100, median_rad=3, intersect=False, output_dir=None, params=None)[source]¶ Simulates speficied configurations of fibers and stores in a npy file.
Simulates a number of fiber configurations speficied in params with n_fibers of the radii and lengths in ranges radius_lim and length_lim, separated with gaps in a range of gap_lim. The simulation process stops if the number of attempts to generate a fiber exceeds max_fails.
- volume_size : tuple
- Indicates the size of the volume.
- n_fibers : integer
- Indicates the number of fibers to be generated.
- radius_lim : tuple
- Indicates the range of radii for fibers to be generated.
- length_lim : tuple
- Indicates the range of lengths for fibers to be generated.
- gap_lim : tuple
- Indicates the range of gaps separating the fibers from each other.
- max_fails : integer
- Indicates the maximum number of failures during the simulation process.
- median_rad : integer
- Indicates the radius of median filter to fill holes occured due to rounding of coordinates of the generated fibers.
- intersect : boolean
- Specifies if generated fibers can intersect.
- output_dir : str
- Indicates the path to the output folder where the data will be stored.
- params : dict
- Indicates the configurations of orientation of fibers to be generated.
- out : dict
- The dictionary of generated datasets of specified configurations.
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quanfima.simulation.generate_noised_data(datasets_path, noise_levels=[0.0, 0.15, 0.3], smooth_levels=[0.0, 1.0, 2.0], blobs=None, use_median=True, median_rad=3, output_dir=None, n_processes=9)[source]¶ Contaminates datasets with a speficied additive Gaussian noise and smoothing level.
Contaminates the datasets (generated with generate_datasets function) with the specified level of additive Gaussian noise and smoothing, uneven illumination can be added if blobs is provided. The contaminating process can be performed in a parallel n_processes processes.
- datasets_path : str
- Indicates the path to dataset.
- noise_levels : array
- Indicates the array of standard deviations of noise.
- smooth_levels : array
- Indicates the array of sigma values of Gaussian filter.
- blobs : ndarray
- Indicates the volume of uneven illumination generated by generate_blobs.
- use_median : boolean
- Specifies if the median filter should be applied after addition of noise.
- median_rad : integer
- Indicates the size of median filter.
- output_dir : str
- Indicates the path to the output folder where the data will be stored.
- n_processes : integer
- Indicates the number of parallel processes.
- results : array of dicts
- The array of dictionaries containing paths to contaminated datasets, and other properties.
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quanfima.simulation.generate_particle_dataset(volume_size=(512, 512, 512), n_particles=500, radius_lim=(4, 10), max_fails=100, output_dir=None)[source]¶ Simulates a speficied number of particles and stores complete dataset in a npy file.
- volume_size : tuple
- Indicates the size of the volume.
- n_particles : integer
- Indicates the number of particles to be generated.
- radius_lim : tuple
- Indicates the range of radii for particles to be generated.
- max_fails : integer
- Indicates the maximum number of failures during the simulation process.
- output_dir : str
- Indicates the path to the output folder where the data will be stored.
- out : dict
- The dictionary of generated dataset.
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quanfima.simulation.mkfiber(dims_size, length, radius, azth, lat, offset_xyz)[source]¶ Computes fiber coordinates and its length.
Computes a fiber of speficied length, radius, oriented under azimuth azth and latitude / elevation lat angles shifted to offset_xyz from the center of a volume of size dims_size.
- dims_size : tuple
- Indicates the size of the volume.
- length : integer
- Indicates the length of the simulated fiber.
- radius : integer
- Indicates the radius of the simulated fiber.
- azth : float
- Indicates the azimuth component of the orientation angles of the fiber in radians.
- lat : float
- Indicates the latitude / elevation component of the orientation angles of the fiber in radians.
- offset_xyz : tuple
- Indicates the offset from the center of the volume where the fiber will be generated.
- fiber_pts, fiber_len : tuple of array and number
- The array of fiber coordinates and the length.
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quanfima.simulation.simulate_fibers(volume_shape, n_fibers=1, radius_lim=(4, 10), length_lim=(0.2, 0.8), lat_lim=(0, 3.141592653589793), azth_lim=(0, 3.141592653589793), gap_lim=(3, 10), max_fails=10, max_len_loss=0.5, intersect=False)[source]¶ Simulates fibers in a volume.
Simulates n_fibers of the radii and lengths in ranges radius_lim and length_lim, oriented in a range of azimuth azth_lim and latitude elevation ‘lat_lim’ angles, separated with a gap in a range of gap_lim. The simulation process stops if the number of attempts to generate a fiber exceeds max_fails.
- volume_shape : tuple
- Indicates the size of the volume.
- n_fibers : integer
- Indicates the number of fibers to be generated.
- radius_lim : tuple
- Indicates the range of radii for fibers to be generated.
- length_lim : tuple
- Indicates the range of lengths for fibers to be generated.
- lat_lim : tuple
- Indicates the range of latitude / elevation component of the orientation angles of the fibers to be generated.
- azth_lim : tuple
- Indicates the range of azimuth component of the orientation angles of the fibers to be generated.
- gap_lim : tuple
- Indicates the range of gaps separating the fibers from each other.
- max_fails : integer
- Indicates the maximum number of failures during the simulation process.
- max_len_loss : float
- Indicates the maximum fraction of the generated fiber placed out of volume, exceeding which the fiber is counted as failed.
- intersect : boolean
- Specifies if generated fibers can intersect.
- (volume, lat_ref, azth_ref, diameter, n_generated, elapsed_time) : tuple of arrays and numbers
- The binary volume of generated fibers, the volumes of latitude / elevation and azimuth angles at every fiber point, the volume of diameters at every fibers point, the number of generated fibers and the simulation time.
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quanfima.simulation.simulate_particles(volume_shape, n_particles=1, radius_lim=(3, 30), max_fails=10)[source]¶ Simulates particles in a volume.
Simulates n_particles of the radii in a range radius_lim. The simulation process stops if the number of attempts to generate a particle exceeds max_fails.
- volume_shape : tuple
- Indicates the size of the volume.
- n_particles : integer
- Indicates the number of particles to be generated.
- radius_lim : tuple
- Indicates the range of radii for particles to be generated.
- max_fails : integer
- Indicates the maximum number of failures during the simulation process.
- (volume, diameter, n_generated, elapsed_time) : tuple of arrays and numbers
- The binary volume of generated particles, the volume of diameters at every point of particles, the number of generated particles and the simulation time.