"""Numerical/mathemetical related functions.
.. versionadded:: 2.1.0
"""
from __future__ import absolute_import, division
import math
import pydash as pyd
from .helpers import itercallback, iterator
from ._compat import _range
__all__ = (
'add',
'average',
'avg',
'curve',
'mean',
'median',
'moving_average',
'moving_avg',
'pow_',
'power',
'round_',
'scale',
'sigma',
'slope',
'std_deviation',
'sum_',
'transpose',
'variance',
'zscore',
)
INFINITY = float('inf')
[docs]def add(collection, callback=None):
"""Sum each element in `collection`. If callback is passed, each element of
`collection` is passed through a callback before the summation is computed.
Args:
collection (list|dict): Collection to process.
callback (mixed, optional): Callback applied per iteration.
Returns:
number: Result of summation.
See Also:
- :func:`add` (main definition)
- :func:`sum_` (alias)
.. versionadded:: 2.1.0
"""
return sum(result[0] for result in itercallback(collection, callback))
sum_ = add
[docs]def average(collection, callback=None):
"""Calculate arithmetic mean of each element in `collection`. If callback
is passed, each element of `collection` is passed through a callback before
the mean is computed.
Args:
collection (list|dict): Collection to process.
callback (mixed, optional): Callback applied per iteration.
Returns:
float: Result of mean.
See Also:
- :func:`average` (main definition)
- :func:`avg` (alias)
- :func:`mean` (alias)
.. versionadded:: 2.1.0
"""
return add(collection, callback) / pyd.size(collection)
avg = average
mean = average
[docs]def moving_average(array, size):
"""Calculate moving average of each element of `array`. If callback is
passed, each element of `array` is passed through a callback before the
moving average is computed.
Args:
array (list): List to process.
size (int): Window size.
Returns:
list: Result of moving average.
See Also:
- :func:`moving_averge` (main definition)
- :func:`moving_avg` (alias)
.. versionadded:: 2.1.0
"""
result = []
size = int(size)
for i in _range(size - 1, len(array) + 1):
window = array[i - size:i]
if len(window) == size:
result.append(average(window))
return result
moving_avg = moving_average
[docs]def power(x, n):
"""Calculate exponentiation of `x` raised to the `n` power.
Args:
x (number): Base number.
n (number): Exponent.
Returns:
number: Result of calculation.
See Also:
- :func:`power` (main definition)
- :func:`pow_` (alias)
.. versionadded:: 2.1.0
"""
if pyd.is_number(x):
result = pow(x, n)
elif pyd.is_list(x):
result = pyd.map_(x, lambda item: pow(item, n))
else:
result = None
return result
pow_ = power
[docs]def round_(x, precision=0):
"""Round number to precision.
Args:
x (number): Number to round.
precision (int, optional): Rounding precision. Defaults to ``0``.
Returns:
int: Rounded number.
See Also:
- :func:`round_` (main definition)
- :func:`curve` (alias)
.. versionadded:: 2.1.0
"""
rounder = pyd.partial_right(round, precision)
if pyd.is_number(x):
result = rounder(x)
elif pyd.is_list(x):
# pylint: disable=unnecessary-lambda
result = pyd.map_(x, lambda item: rounder(item))
else:
result = None
return result
curve = round_
[docs]def scale(array, maximum=1):
"""Scale list of value to a maximum number.
Args:
array (list): Numbers to scale.
maximum (number): Maximum scale value.
Returns:
list: Scaled numbers.
.. versionadded:: 2.1.0
"""
array_max = max(array)
return pyd.map_(array, lambda item: item * (maximum / array_max))
[docs]def slope(point1, point2):
"""Calculate the slope between two points.
Args:
point1 (list|tuple): X and Y coordinates of first point.
point2 (list|tuple): X and Y cooredinates of second point.
Returns:
float: Calculated slope.
.. versionadded:: 2.1.0
"""
x1, y1 = point1[0], point1[1]
x2, y2 = point2[0], point2[1]
if x1 == x2:
result = INFINITY
else:
result = (y2 - y1) / (x2 - x1)
return result
[docs]def std_deviation(array):
"""Calculate standard deviation of list of numbers.
Args:
array (list): List to process.
Returns:
float: Calculated standard deviation.
See Also:
- :func:`std_deviation` (main definition)
- :func:`sigma` (alias)
.. versionadded:: 2.1.0
"""
return math.sqrt(variance(array))
sigma = std_deviation
[docs]def transpose(array):
"""Transpose the elements of `array`.
Args:
array (list): List to process.
Returns:
list: Transposed list.
.. versionadded:: 2.1.0
"""
trans = []
for y, row in iterator(array):
for x, col in iterator(row):
trans = pyd.set_path(trans, col, [x, y])
return trans
[docs]def variance(array):
"""Calculate the variance of the elements in `array`.
Args:
array (list): List to process.
Returns:
float: Calculated variance.
.. versionadded:: 2.1.0
"""
ave = average(array)
var = lambda x: power(x - ave, 2)
return pyd._(array).map_(var).average().value()
[docs]def zscore(collection, callback=None):
"""Calculate the standard score assuming normal distribution. If callback
is passed, each element of `collection` is passed through a callback before
the standard score is computed.
Args:
collection (list|dict): Collection to process.
callback (mixed, optional): Callback applied per iteration.
Returns:
float: Calculated standard score.
.. versionadded:: 2.1.0
"""
array = pyd.map_(collection, callback)
ave = average(array)
sig = sigma(array)
return pyd.map_(array, lambda item: (item - ave) / sig)