surkit.data package
Submodules
surkit.data.dataset module
surkit.data.processing module
surkit.data.sampling module
- surkit.data.sampling.get(sampler)[source]
Return a sampler based on the given string
- Parameters:
sampler (str) – “random” or “uniform”
- Returns:
a pre-defined sampler function
- Return type:
function
- surkit.data.sampling.random_sampler(lower=0, upper=1, n=1)[source]
A random sampler
- Parameters:
lower (float | ndarray | Iterable | int | None) – lower bound
upper (float | ndarray | Iterable | int | None) – upper bound
n (int | Iterable | tuple[int] | None]) – sample size
- Returns:
a set of sampling data
- Return type:
numpy.ndarray
- surkit.data.sampling.uniform_sampler(lower=0, upper=1, n=1)[source]
A uniform sampler
- Parameters:
lower (float | ndarray | Iterable | int | None) – lower bound
upper (float | ndarray | Iterable | int | None) – upper bound
n (int | Iterable | tuple[int] | None]) – sample size
- Returns:
a set of sampling data
- Return type:
numpy.ndarray
- surkit.data.sampling.weight_1d(x, xrange)[source]
Assign weight according to 1-dimensional coordinates
- Parameters:
x (float) – value
xrange (list[float, float] | tuple[float, float]) – boundary
- Returns:
weight
- Return type:
float
- surkit.data.sampling.weight_2d(x, y, xrange, yrange, dt)[source]
Assign weight according to 2-dimensional coordinates
- Parameters:
x (float) – the value of the first dimension
y (float) – the value of the second dimension
xrange (list[float, float] | tuple[float, float]) – the boundary of the first dimension
yrange (list[float, float] | tuple[float, float]) – the boundary of the second dimension
dt (float) – empirical parameters controlling the extent of the weighted area
- Returns:
weight
- Return type:
float