miv_simulator.geometry.geometry#

Classes and procedures related to neuronal geometry and distance calculation.

Functions

`distance_interpolant`(comm, layer_extents, ...)
`euclidean_distance`(a, b)	Row-wise euclidean distance.
`generate_nodes`(alpha, nsample, nodeitr)
`get_layer_extents`(layer_extents, layer)
`get_total_extents`(layer_extents)
`get_volume_distances`(ip_vol[, origin_spec, ...])	Computes arc-distances along the dimensions of an RBFVolume instance.
`icp_transform`(comm, geometry_config, volume, ...)	Uses the iterative closest point (ICP) algorithm of the PCL library to transform soma coordinates onto a surface for a particular L value.
`interp_soma_distances`(comm, ip_dist_u, ...)	Interpolates path lengths of cell coordinates along the dimensions of an RBFVolume instance.
`load_alpha_shape`(file_path, dataset_path)
`make_alpha_shape`(vol[, alpha_radius])
`make_distance_interpolant`(comm, ...[, ...])
`make_rotate3d`(rotate)	Creates a rotation matrix based on angles in degrees.
`make_uvl_distance`(vol, xyz_coords[, rotate])
`measure_distance_extents`(geometry_config, volume)
`measure_distances`(comm, geometry_config, ...)
`measure_soma_distances`(comm, layer_extents, ...)
`optimize_inverse_uvl_coords`(vol, xyz_coords, ...)
`rotate2d`(theta)	Returns the 2D rotation matrix associated with counterclockwise rotation around the origin by theta radians.
`rotate3d`(axis, theta)	Returns the 3D rotation matrix associated with counterclockwise rotation about the given axis by theta radians.
`save_alpha_shape`(file_path, dataset_path, ...)
`transform_volume`(transform, u, v, l[, rotate])	Transform to Euclidean volume.
`uvl_in_bounds`(uvl_coords, layer_extents, ...)

miv_simulator.geometry.geometry.rotate2d(theta)[source]#: Returns the 2D rotation matrix associated with counterclockwise rotation around the origin by theta radians.

miv_simulator.geometry.geometry.rotate3d(axis, theta)[source]#: Returns the 3D rotation matrix associated with counterclockwise rotation about the given axis by theta radians.

miv_simulator.geometry.geometry.make_rotate3d(rotate)[source]#: Creates a rotation matrix based on angles in degrees.

miv_simulator.geometry.geometry.transform_volume(transform, u, v, l, rotate=None)[source]#: Transform to Euclidean volume.

miv_simulator.geometry.geometry.euclidean_distance(a, b)[source]#: Row-wise euclidean distance. a, b are row vectors of points.

miv_simulator.geometry.geometry.get_volume_distances(ip_vol, origin_spec=None, nsample=1000, alpha_radius=None, nodeitr=20, comm=None)[source]#

Computes arc-distances along the dimensions of an RBFVolume instance.

Parameters:

ip_volRBFVolume: An interpolated volume instance of class RBFVolume.
origin_coordsarray(float): Origin point to use for distance computation.
nsampleint: Number of points to sample inside the volume.
alpha_radiusfloat: Parameter for creation of alpha volume that encloses the RBFVolume. Smaller values improve the quality of alpha volume, but increase the time for sampling points inside the volume.
nodeitrint: Number of iterations for distributing sampled points inside the volume.
commMPIComm (optional): mpi4py MPI communicator: if provided, node generation and distance computation will be performed in parallel
Returns
——-
(Y1, X1, … , YN, XN) where N is the number of dimensions of the volume.
Xarray of coordinates: The sampled coordinates.
Yarray of distances: The arc-distance from the starting index of the coordinate space to the corresponding coordinates in X.

miv_simulator.geometry.geometry.interp_soma_distances(comm, ip_dist_u, ip_dist_v, soma_coords, layer_extents, population_layers, interp_chunk_size=1000, populations=None, allgather=False)[source]#

Interpolates path lengths of cell coordinates along the dimensions of an RBFVolume instance.

Parameters:

commMPIComm

mpi4py MPI communicator

ip_dist_uRBFInterpolant

Interpolation function for computing arc distances along the first dimension of the volume.

ip_dist_vRBFInterpolant

Interpolation function for computing arc distances along the second dimension of the volume.

soma_coords{ population_namecoords_dict }

A dictionary that maps each cell population name to a dictionary of coordinates. The dictionary of coordinates must have the following type:: coords_dict : { gid : (u, v, l) } where: - gid: cell identifier - u, v, l: floating point coordinates

population_layers: { population_namelayers }

A dictionary of population count per layer Argument layers has the following type:

{ layer_name: count }

allgather: boolean (default: False)

if True, the results are gathered from all ranks and combined

Returns

——-

A dictionary of the form:

{ population: { gid: (distance_U, distance_V } }

miv_simulator.geometry.geometry.icp_transform(comm, geometry_config, volume, make_surface, soma_coords, projection_ls, population_extents, rotate=None, populations=None, icp_iter=1000, opt_iter=100)[source]#: Uses the iterative closest point (ICP) algorithm of the PCL library to transform soma coordinates onto a surface for a particular L value. http://pointclouds.org/documentation/tutorials/iterative_closest_point.php#iterative-closest-point