Correlations API¤
stamox.correlation.cor(x: ArrayLike, y: Optional[ArrayLike] = None, axis: int = 0, method: str = 'pearson') -> ArrayLike
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Calculates correlation between two arrays.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
x |
ArrayLike |
The first array. |
required |
y |
Optional[ArrayLike] |
The second array. Defaults to None. |
None |
axis |
int |
Axis along which the correlation is calculated. Defaults to 0. |
0 |
method |
str |
Method used for calculating correlation. Defaults to "pearson". |
'pearson' |
Returns:
| Type | Description |
|---|---|
ArrayLike |
Correlation between two arrays. |
Exceptions:
| Type | Description |
|---|---|
NotImplementedError |
If the specified method is not supported. |
Examples:
>>> import jax.numpy as jnp
>>> from stamox.functions import cor
>>> x = jnp.array([1, 2, 3, 4, 5])
>>> y = jnp.array([5, 6, 7, 8, 7])
>>> cor(x, y)
Array(0.8320503, dtype=float32)
stamox.correlation.pearsonr(x: ArrayLike, y: Optional[ArrayLike] = None, axis: int = 0) -> ArrayLike
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Computes Pearson correlation coefficient for two arrays.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
x |
ArrayLike |
An array-like object containing the first set of data. |
required |
y |
Optional[ArrayLike] |
An optional array-like object containing the second set of data. If not |
None |
axis |
int |
The axis along which the correlation coefficient should be computed. |
0 |
Returns:
| Type | Description |
|---|---|
ArrayLike |
An array-like object containing the Pearson correlation coefficient. |
Examples:
>>> import jax.numpy as jnp
>>> from stamox.functions import pearsonr
>>> x = jnp.array([1, 2, 3, 4, 5])
>>> y = jnp.array([5, 6, 7, 8, 7])
>>> pearsonr(x, y)
Array(0.8320503, dtype=float32)
stamox.correlation.spearmanr(x: ArrayLike, y: Optional[ArrayLike] = None, axis: int = 0) -> ArrayLike
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Calculates a Spearman rank-order correlation coefficient and the p-value to test for non-correlation.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
x |
ArrayLike |
An array of values. |
required |
y |
Optional[ArrayLike] |
An array of values. Defaults to None. |
None |
axis |
int |
The axis along which to calculate. Defaults to 0. |
0 |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the supplied axis argument is greater than 1 or if the number of dimensions of the array is greater than 2. |
Returns:
| Type | Description |
|---|---|
ArrayLike |
A array-like containing the Spearman rank-order correlation coefficient and the p-value to test for non-correlation. |
Examples:
>>> import jax.numpy as jnp
>>> from stamox.functions import spearmanr
>>> x = jnp.array([1, 2, 3, 4, 5])
>>> y = jnp.array([5, 6, 7, 8, 7])
>>> spearmanr(x, y)
Array(0.8207823038101196, dtype=float32)