https://github.com/layerex/beizer-curves
A python library for generating beizer curves.
https://github.com/layerex/beizer-curves
beizer beizer-curves mouse-movement
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A python library for generating beizer curves.
- Host: GitHub
- URL: https://github.com/layerex/beizer-curves
- Owner: Layerex
- License: mpl-2.0
- Created: 2021-11-12T18:14:58.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2021-11-12T19:03:53.000Z (over 4 years ago)
- Last Synced: 2025-03-12T06:19:54.693Z (over 1 year ago)
- Topics: beizer, beizer-curves, mouse-movement
- Language: Python
- Homepage:
- Size: 10.7 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# beizer-curves
A python library for generating beizer curves.
## Installation
```sh
pip install beizer-curves
```
## Usage
```python
def beizer_curve(
points,
output_points_count: int,
destructive: bool = False,
dtype: np.dtype = np.int64,
):
```
Generate a beizer curve.
- `points` - Knots in format: `[[x1, x2, ..., xn], [y1, y2, ..., yn], [z1, z2, ..., zn]]`.
- `output_points_count` - How many points of the curve to generate.
- `destructive` - Allow function to modify `points` array. Don't set to true, if you want to use `points` array later.
- `dtype` - dtype of array of returned points of the curve.
Points of a curve are returned in format: `[[x1, x2, ..., xn], [y1, y2, ..., yn], [z1, z2, ..., zn]]`, where n is `output_points_count`.
```python
def random_beizer_curve(
start_point,
end_point,
output_points_count: int,
random_points_count: int = 1,
point_spread: float = 1,
noise_max_offset: float = 0,
noise_rate: float = 0.5,
dtype=np.int64,
return_forming_points: bool = False,
):
```
Generate a random beizer curve, which starts at start_point and ends at end_point.
- `start_point`, `end_point` - coordinates of start and end points of curve in format `[x, y, z, ...]`.
- `output_points_count` - How many points of the curve to generate.
```python
if output_points_count < 0:
output_points_count = math.ceil(distance / -output_points_count)
```
Where `distance` is distance between start and end.
- `random_points_count` - How many knots to generate.
- `point_spread` - A scale of a rectangular figure with corners of start_point and end_point, in bounds of which random knots are generated. Has to be > 0.
- `noise_max_offset` - Max offset of a curve point.
```python
if output_points_count < 0:
output_points_count = math.ceil(distance / -output_points_count)
```
Where `distance` is distance between start and end.
- `noise_rate` - A part of curve points to apply noise offset to. Has to belong to [0; 1].
- `dtype` - dtype array of returned points of the curve.
- `return_forming_points` - `return points, curve if return_forming_points else curve`, where `points` are randomly generated knots
## Usage example
```python
import random
import matplotlib.pyplot as plt
import numpy as np
from beizer_curves import *
def plot_curve(points_count, i):
start = [random.randrange(1, 2000), random.randrange(1, 2000)]
noise = -200 * i
end = [random.randrange(1, 2000), random.randrange(1, 2000)]
points, curve = random_beizer_curve(
start,
end,
output_points_count=50,
random_points_count=points_count,
noise_max_offset=noise,
noise_rate=0.25,
dtype=np.float64,
return_forming_points=True,
)
fig = plt.figure()
plt.axis("equal")
plt.scatter(curve[0], curve[1])
plt.scatter(points[0], points[1], color='red')
fig.savefig(f"example_{points_count}_{i + 1}.png")
```
## Example curves
