squarenet.sampler

Functions

list_methods()	Return available sampling methods.
loaddatasets([force])	Download dataset files from GitHub into a local cache directory.
place_at(points[, position])	Normalize point cloud to [0,1]^D and shift it at the specified position
plotpoints(points)	plot a 2D projection of the point cloud
samplepoints([method, size, plot_points])	Generate point clouds using various sampling strategies.

class squarenet.sampler.Path(*args, **kwargs)

Bases: PurePath

PurePath subclass that can make system calls.

Path represents a filesystem path but unlike PurePath, also offers methods to do system calls on path objects. Depending on your system, instantiating a Path will return either a PosixPath or a WindowsPath object. You can also instantiate a PosixPath or WindowsPath directly, but cannot instantiate a WindowsPath on a POSIX system or vice versa.

absolute()

Return an absolute version of this path by prepending the current working directory. No normalization or symlink resolution is performed.

Use resolve() to get the canonical path to a file.

chmod(mode, *, follow_symlinks=True)

Change the permissions of the path, like os.chmod().

classmethod cwd()

Return a new path pointing to the current working directory.

exists(*, follow_symlinks=True)

Whether this path exists.

This method normally follows symlinks; to check whether a symlink exists, add the argument follow_symlinks=False.

expanduser()

Return a new path with expanded ~ and ~user constructs (as returned by os.path.expanduser)

glob(pattern, *, case_sensitive=None)

Iterate over this subtree and yield all existing files (of any kind, including directories) matching the given relative pattern.

group()

Return the group name of the file gid.

hardlink_to(target)

Make this path a hard link pointing to the same file as target.

Note the order of arguments (self, target) is the reverse of os.link’s.

classmethod home()

Return a new path pointing to the user’s home directory (as returned by os.path.expanduser(‘~’)).

is_block_device()

Whether this path is a block device.

is_char_device()

Whether this path is a character device.

is_dir()

Whether this path is a directory.

is_fifo()

Whether this path is a FIFO.

is_file()

Whether this path is a regular file (also True for symlinks pointing to regular files).

is_junction()

Whether this path is a junction.

is_mount()

Check if this path is a mount point

is_socket()

Whether this path is a socket.

is_symlink()

Whether this path is a symbolic link.

iterdir()

Yield path objects of the directory contents.

The children are yielded in arbitrary order, and the special entries ‘.’ and ‘..’ are not included.

lchmod(mode)

Like chmod(), except if the path points to a symlink, the symlink’s permissions are changed, rather than its target’s.

lstat()

Like stat(), except if the path points to a symlink, the symlink’s status information is returned, rather than its target’s.

mkdir(mode=511, parents=False, exist_ok=False)

Create a new directory at this given path.

open(mode='r', buffering=-1, encoding=None, errors=None, newline=None)

Open the file pointed to by this path and return a file object, as the built-in open() function does.

owner()

Return the login name of the file owner.

read_bytes()

Open the file in bytes mode, read it, and close the file.

read_text(encoding=None, errors=None)

Open the file in text mode, read it, and close the file.

readlink()

Return the path to which the symbolic link points.

rename(target)

Rename this path to the target path.

The target path may be absolute or relative. Relative paths are interpreted relative to the current working directory, not the directory of the Path object.

Returns the new Path instance pointing to the target path.

replace(target)

Rename this path to the target path, overwriting if that path exists.

The target path may be absolute or relative. Relative paths are interpreted relative to the current working directory, not the directory of the Path object.

Returns the new Path instance pointing to the target path.

resolve(strict=False)

Make the path absolute, resolving all symlinks on the way and also normalizing it.

rglob(pattern, *, case_sensitive=None)

Recursively yield all existing files (of any kind, including directories) matching the given relative pattern, anywhere in this subtree.

rmdir()

Remove this directory. The directory must be empty.

samefile(other_path)

Return whether other_path is the same or not as this file (as returned by os.path.samefile()).

stat(*, follow_symlinks=True)

Return the result of the stat() system call on this path, like os.stat() does.

symlink_to(target, target_is_directory=False)

Make this path a symlink pointing to the target path. Note the order of arguments (link, target) is the reverse of os.symlink.

touch(mode=438, exist_ok=True)

Create this file with the given access mode, if it doesn’t exist.

unlink(missing_ok=False)

Remove this file or link. If the path is a directory, use rmdir() instead.

walk(top_down=True, on_error=None, follow_symlinks=False)

Walk the directory tree from this directory, similar to os.walk().

write_bytes(data)

Open the file in bytes mode, write to it, and close the file.

write_text(data, encoding=None, errors=None, newline=None)

Open the file in text mode, write to it, and close the file.

squarenet.sampler.list_methods()

Return available sampling methods.

squarenet.sampler.loaddatasets(force=False)

Download dataset files from GitHub into a local cache directory.

Parameters:

force (bool) – If True, re-download files even if they already exist.

squarenet.sampler.place_at(points, position=(0, 0))

Normalize point cloud to [0,1]^D and shift it at the specified position

Parameters:

• points (numpy.ndarray) – Input point cloud.

• position (Target position of the minimum corner after normalization.)

Returns:

point cloud normalized and placed at the

Return type:

numpy.ndarray

squarenet.sampler.plotpoints(points)

plot a 2D projection of the point cloud

squarenet.sampler.samplepoints(method='gaussian', size=(1000000, 2), plot_points=True)

Generate point clouds using various sampling strategies.

Parameters:

• method (str) –

  Sampling method. Supported values:

  General methods (any dimension D): - “square” : uniform in [-1, 1]^D - “ball” : uniform in the unit ball - “ring” : Gaussian with radial offset - “gaussian” : standard normal distribution - “spiky” : L^alpha ball (alpha < 1) - “holy” : hypercube with spherical holes

  Dataset-based methods (fixed dimensions): - “barbara”, “lena”, “france”, “germany” : 2D datasets - “everest” : 3D dataset (elevation-based sampling)

• size (tuple of int) – (N, D) where N is the number of points and D the dimension. Note: D must match the dataset dimension for dataset-based methods.

• plot_points (bool, optional) – If True, display the generated points.

Returns:

Array of shape (N, D) containing sampled points.

Return type:

numpy.ndarray