# `pycw_fn` - efficient piecewise functions in Python
This package is a Python wrapper around the `pcw_fn` Rust crate built using maturin. It supports arbitrary piecewise functions on the real line.
# Example
This example constructs a few piecewise functions, does some basic arithmetic with them and finally plots them:
```python
import numpy as np
import matplotlib.pyplot as plt
from numpy.polynomial import Polynomial
from pycw_fn import PcwFn
g_0 = PcwFn.from_funcs_and_jumps(
[
Polynomial([1, 5, -10], window=np.array([-1., 1.]),
domain=np.array([-1., 1.])),
Polynomial([0, 10, -20, 10], window=np.array([-1., 1.]),
domain=np.array([-1., 1.])),
],
[
0.5,
],
)
g_1 = PcwFn.from_funcs_and_jumps(
[
Polynomial([0.4*a**2, -4*a, 10], window=np.array([-1., 1.]),
domain=np.array([-1., 1.])) for a in range(6)
],
[
0.1,
0.3,
0.5,
0.7,
0.9,
],
)
b_2 = Polynomial([1/10, -4, 40])
g_2 = PcwFn.from_funcs_and_jumps(
[b_2(Polynomial([-0.1*a, 1])) for a in range(10)],
np.linspace(0.1, 1, num=9, endpoint=False),
)
g = g_0 + 5 * g_2
ts = np.linspace(0, 1, num=1000)
ys = g(ts)
plt.plot(ts, ys)
plt.show()
```
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"description": "# `pycw_fn` - efficient piecewise functions in Python\n\nThis package is a Python wrapper around the `pcw_fn` Rust crate built using maturin. It supports arbitrary piecewise functions on the real line.\n\n# Example\n\nThis example constructs a few piecewise functions, does some basic arithmetic with them and finally plots them:\n\n```python\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom numpy.polynomial import Polynomial\nfrom pycw_fn import PcwFn\n\ng_0 = PcwFn.from_funcs_and_jumps(\n [\n Polynomial([1, 5, -10], window=np.array([-1., 1.]),\n domain=np.array([-1., 1.])),\n Polynomial([0, 10, -20, 10], window=np.array([-1., 1.]),\n domain=np.array([-1., 1.])),\n ],\n [\n 0.5,\n ],\n)\n\n\ng_1 = PcwFn.from_funcs_and_jumps(\n [\n Polynomial([0.4*a**2, -4*a, 10], window=np.array([-1., 1.]),\n domain=np.array([-1., 1.])) for a in range(6)\n ],\n [\n 0.1,\n 0.3,\n 0.5,\n 0.7,\n 0.9,\n ],\n)\n\nb_2 = Polynomial([1/10, -4, 40])\ng_2 = PcwFn.from_funcs_and_jumps(\n [b_2(Polynomial([-0.1*a, 1])) for a in range(10)],\n np.linspace(0.1, 1, num=9, endpoint=False),\n)\n\ng = g_0 + 5 * g_2\n\nts = np.linspace(0, 1, num=1000)\nys = g(ts)\nplt.plot(ts, ys)\nplt.show()\n\n```\n\n",
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