https://github.com/zulko/ddeint

Scipy-based Delay Differential Equation (DDE) solver
https://github.com/zulko/ddeint

Last synced: about 1 year ago
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Scipy-based Delay Differential Equation (DDE) solver

• Host: GitHub
• URL: https://github.com/zulko/ddeint
• Owner: Zulko
• License: cc0-1.0
• Created: 2014-05-04T08:03:55.000Z (over 12 years ago)
• Default Branch: master
• Last Pushed: 2024-08-28T15:02:41.000Z (almost 2 years ago)
• Last Synced: 2025-06-17T20:03:24.451Z (about 1 year ago)
• Language: Python
• Size: 110 KB
• Stars: 36
• Watchers: 4
• Forks: 24
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# ddeint

[![PyPI](https://img.shields.io/pypi/v/ddeint.svg)](https://pypi.org/project/ddeint/)

[![Tests](https://github.com/zulko/ddeint/actions/workflows/test.yml/badge.svg)](https://github.com/zulko/ddeint/actions/workflows/test.yml)

[![Changelog](https://img.shields.io/github/v/release/zulko/ddeint?include_prereleases&label=changelog)](https://github.com/zulko/ddeint/releases)

Scipy-based delay differential equation (DDE) solver. See the docstrings and examples for more infos.

## Examples

```python

from pylab import cos, linspace, subplots

from ddeint import ddeint

# We solve the following system:

# Y(t) = 1 for t < 0

# dY/dt = -Y(t - 3cos(t)**2) for t > 0

def values_before_zero(t):

    return 1

def model(Y, t):

    return -Y(t - 3 * cos(Y(t)) ** 2)

tt = linspace(0, 30, 2000)

yy = ddeint(model, values_before_zero, tt)

fig, ax = subplots(1, figsize=(4, 4))

ax.plot(tt, yy)

ax.figure.savefig("variable_delay.jpeg")

```

![screenshot](https://github.com/Zulko/ddeint/raw/master/examples/variable_delay.jpeg)

```python

from pylab import array, linspace, subplots

from ddeint import ddeint

# We solve the following system:

# X(t) = 1 (t < 0)

# Y(t) = 2 (t < 0)

# dX/dt = X * (1 - Y(t-d)) / 2

# dY/dt = -Y * (1 - X(t-d)) / 2

def model(Y, t, d):

    x, y = Y(t)

    xd, yd = Y(t - d)

    return array([0.5 * x * (1 - yd), -0.5 * y * (1 - xd)])

g = lambda t: array([1, 2])

tt = linspace(2, 30, 20000)

fig, ax = subplots(1, figsize=(4, 4))

for d in [0, 0.2]:

    print("Computing for d=%.02f" % d)

    yy = ddeint(model, g, tt, fargs=(d,))

    # WE PLOT X AGAINST Y

    ax.plot(yy[:, 0], yy[:, 1], lw=2, label="delay = %.01f" % d)

ax.figure.savefig("lotka.jpeg")

```

![screenshot](https://github.com/Zulko/ddeint/raw/master/examples/lotka.jpeg)

## Licence

Public domain. Everyone is welcome to contribute !

## Installation

Install with pip:

```

pip install ddeint 

```

Or install locally in dev mode with:

```

pip install -e . 

```