"""misc
==================
a collection of useful functions
"""
# % IMPORTS
import numpy as np
from random import choice
# % ARGUMENT PROCESSORS / CHECKERS
[docs]
def check_positive_float(param_name: str, value: float) -> None:
"""internal function to check that a parameter is a positive float, raises a `ValueError` if not.
Args:
param_name (str): name of the checked parameter, to give context in the exception
value (float): value of the paramater to check
"""
if isinstance(value, int):
value = float(value)
if not isinstance(value, float):
raise ValueError(f"'{param_name}' has to be a float")
if value < 0:
raise ValueError(f"'{param_name}' has to be a positive")
[docs]
def check_position_array(position, nocheck=False):
"""Checks that a position array matches our vectorization convention.
It raises an error if the shape is not good.
Parameters
----------
position : array
the array to check
nocheck : bool, optional
if set to True, the function is bypasses
Returns
-------
position
the array
Notes
------
positions array should have a shape (3,) or (n1, n2, .., 3).
In all cases, the last dimension contains cordinates (x, y, z),
in meter and in the lab frame
"""
if nocheck:
return position
# convert to array
position = np.asanyarray(position)
# check that shape is fine : should be (3,) or (n,3)
if not position.shape or position.shape[-1] != 3:
raise ValueError("The position array should be of shape (3,) or (n, m, .., 3)")
return position
[docs]
def check_position_speed_array(position, nocheck=False):
"""Checks that a position array matches our vectorization convention.
It raises an error if the shape is not good.
Parameters
----------
position : array
the array to check
nocheck : bool, optional
if set to True, the function is bypasses
Returns
-------
position
the array
Notes
------
positions array should have a shape (6,) or (n1, n2, .., 6).
In all cases, the last dimension contains cordinates (x, y, z, vx, vy, vz),
in meter and in the lab frame
"""
if nocheck:
return position
# convert to array
position = np.asanyarray(position)
# check that shape is fine : should be (6,) or (n,6)
if not position.shape or position.shape[-1] != 6:
raise ValueError("The position array should be of shape (6,) or (n, m, .., 6)")
return position
[docs]
def check_scalar_field_value_function(func):
"""Used in tests : checks that a function yielding values of a 3D **scalar** field
field behaves correctly with numpy arrays.
for input of shape (..., 1) should return shape (..., 1)
Parameters
----------
func : function
the function to check
"""
# - 1 check that it works with a single position
position = (0, 0, 0)
value = func(position)
assert value.ndim == 0
# - 2 with arrays
# -
position = np.mgrid[0:1:8j, 0:5:10j, 0:0:1j].T
X, _, _ = position.T
X = X.T
value = func(position)
assert value.shape == X.shape
# -
position = position[0]
X, _, _ = position.T
X = X.T
value = func(position)
assert value.shape == X.shape
[docs]
def check_vector_field_value_function(func):
"""Used in tests : checks that a function yielding values of a 3D **vector** field
field behaves correctly with numpy arrays.
for input of shape (..., 3) should return shape (..., 3)
Parameters
----------
func : function
the function to check
"""
# - 1 check that it works with a single position
position = (0, 0, 0)
value = func(position)
assert value.shape == (3,)
# - 2 with arrays
# -
position = np.mgrid[0:1:8j, 0:5:10j, 0:0:1j].T
value = func(position)
assert value.shape == position.shape
# -
position = position[0]
value = func(position)
assert value.shape == position.shape
# % RANDOM TAG
[docs]
def random_word(syl=3):
"""Generates a random word
Parameters
----------
syl : int, optional
number of syllabs, by default 3
Returns
-------
word: str
the random word
"""
voy = "aeiou"
cons = "zrtpqsdfghklmwxvbn"
res = ""
for i in range(syl):
res += choice(cons) + choice(voy)
return res
