https://github.com/nifadyev/cubic-spline-interpolator

Interpolate cubic spline using tridiagonal matrix algorithm
https://github.com/nifadyev/cubic-spline-interpolator

matplotlib numpy scipy spline-interpolation splines

Last synced: about 9 hours ago
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Interpolate cubic spline using tridiagonal matrix algorithm

• Host: GitHub
• URL: https://github.com/nifadyev/cubic-spline-interpolator
• Owner: nifadyev
• License: mit
• Created: 2019-11-18T17:46:10.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2022-06-22T06:52:51.000Z (over 2 years ago)
• Last Synced: 2023-03-05T16:03:28.165Z (over 1 year ago)
• Topics: matplotlib, numpy, scipy, spline-interpolation, splines
• Language: Python
• Homepage:
• Size: 171 KB
• Stars: 4
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Cubic Spline Interpolator

![](https://img.shields.io/badge/python-v3.8-blue) ![](https://img.shields.io/badge/numpy-1.18.2-blue) ![](https://img.shields.io/badge/scipy-1.4.1-blue) ![](https://img.shields.io/badge/matplotlib-3.2.1-blue) ![](https://img.shields.io/badge/platform-windows%20%7C%20linux-lightgrey) ![](https://img.shields.io/badge/license-MIT-green)

Tool for building splines based on pre-calculated (x, y) set of points.

## Requirements

- python3.8+

- pip

- virtualenv (optional)

### Pip packages

Install required packages using `virtualenv`

```bash

python -m virtualenv env && source env/bin/activate

python -m pip install -r requirements.txt

```

## Usage

The script can be run as:

`python main.py --options`

The set of available options are:

 * `--range_start`: left range boundary, default=-10.0, example: -7.5

 * `--range_end`: right range boundary, default=10.0, example: 5.0

 * `--range_length`: number of values in range, default=30000, example: 1000

 * `--intervals`: number of intervals, default=10, example: 50

 * `--compare_default/--do_not_compare`: compare custom spline with default `scipy` spline, default=False

## Example

Set range [-10.0, 20.0] with 50 intervals

`python main.py --range_end 20 --intervals 50`

### Output

Output contains:

 * function

 * first 8 pairs of arguments and function results

 * first 8 pairs of arguments and interpolated values

 * spline coefficients on each step

 * interpolation error

```bash

Function arguments and results:

 x | -10.000 |  -9.999 |  -9.999 |  -9.998 |  -9.997 |  -9.997 |  -9.996 |  -9.995 |

------------------------------------------------------------------------------------

 y |  -0.054 |  -0.054 |  -0.054 |  -0.054 |  -0.054 |  -0.054 |  -0.054 |  -0.053 |

Spline arguments and interpolated values:

 x | -10.000 |  -9.999 |  -9.999 |  -9.998 |  -9.997 |  -9.997 |  -9.996 |  -9.995 |

------------------------------------------------------------------------------------

 y |  -0.054 |  -0.054 |  -0.054 |  -0.054 |  -0.053 |  -0.053 |  -0.053 |  -0.053 |

Coefficients on each step:

Step|    x    |    a    |    b    |    c    |    d    

------------------------------------------------------

  1 | -10.000 |  -0.054 |   0.000 |   0.000 |   0.000

  2 |  -7.778 |   0.126 |  -0.031 |  -0.152 |  -0.068

  3 |  -5.556 |  -0.116 |  -0.095 |   0.094 |   0.111

  4 |  -3.333 |  -0.052 |   0.172 |   0.146 |   0.023

  5 |  -1.111 |   0.446 |   0.167 |  -0.150 |  -0.133

  6 |   1.111 |   0.446 |  -0.167 |  -0.150 |  -0.000

  7 |   3.333 |  -0.052 |  -0.172 |   0.146 |   0.133

  8 |   5.556 |  -0.116 |   0.095 |   0.094 |  -0.023

  9 |   7.778 |   0.126 |   0.031 |  -0.152 |  -0.111

 10 |  10.000 |  -0.054 |  -0.137 |   0.000 |   0.068

Interpolation error: 0.11198

```

### Plot

#### 10 intervals

![](./images/default_intervals.png)

#### 30 intervals

![](./images/30_intervals.png)