Skip to main content

Implementation of ASTM E1049-85 rainflow cycle counting algorythm

Project description

Rainflow
========

[![Build Status](https://travis-ci.org/iamlikeme/rainflow.svg?branch=master)](https://travis-ci.org/iamlikeme/rainflow)

`rainflow` is a Python implementation of the ASTM E1049-85 rainflow cycle counting
algorythm for fatigue analysis. No dependencies beside Python's standard library.
Supports both Python 2 and 3.

Installation
------------

```
pip install rainflow
```

Usage
-----
Let's generate a sample time series of some load. Here we create a numpy array but any iterable of numbers would work:
```python
>>> import numpy as np
>>> x = np.linspace(0, 4, 200)
>>> y = 0.2 + 0.5 * np.sin(x) + 0.2 * np.cos(10*x) + 0.2 * np.sin(4*x)
```

Function `count_cycles` returns a sorted list of the load ranges and the corresponding
number of cycles:
```python
>>> import rainflow
>>> rainflow.count_cycles(y)
[(0.11022406179686783, 1.0), (0.11316419853821802, 0.5), (0.20607635324664902, 1.0),
(0.2148070281383265, 0.5), (0.36749670533564682, 0.5), (0.4389628182518176, 0.5),
(0.48294318988133728, 0.5), (0.52799626197601901, 0.5), (0.78150280937784777, 0.5),
(1.102640610792428, 0.5)]
```

Not interested in all the decimals? Use *ndigits*:
```python
>>> rainflow.count_cycles(y, ndigits=2)
[(0.11, 1.5), (0.21, 1.5), (0.37, 0.5), (0.44, 0.5), (0.48, 0.5), (0.53, 0.5),
(0.78, 0.5), (1.1, 0.5)]
```

If you need more detailed output, like cycle lows, highs or means, use `extract_cycles`:
```python
>>> for low, high, mult in rainflow.extract_cycles(y):
... mean = 0.5 * (high + low)
... rng = high - low
```

Running tests
-------------
```
python -m unittest tests/*.py
```

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for rainflow, version 2.1.2
Filename, size File type Python version Upload date Hashes
Filename, size rainflow-2.1.2.tar.gz (4.4 kB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page