pyyeti.cyclecount.rainflow

pyyeti.cyclecount.rainflow(peaks, getoffsets=False, use_pandas=True)[source]

Rainflow cycle counting.

Parameters:

  • peaks (1d array_like) – Vector of alternating peaks (as returned by findap(), for example)

  • getoffsets (bool; optional) – If True, the tuple (rf, os) is returned; otherwise, only rf is returned.

  • use_pandas (bool; optional) – If True, this routine will return pandas DataFrames

Returns:

  • rf (pandas DataFrame or 2d ndarray) – n x 3 matrix with the rainflow cycle count information with the index going from 0 to n-1 and the columns being [‘amp’, ‘mean’, ‘count’]:

    • amp is the cycle amplitude (half the peak-to-peak range)

    • mean is mean of the cycle

    • count is either 0.5 or 1.0 depending on whether it’s half or full cycle

  • os (pandas DataFrame or 2d ndarray) – Only returned if getoffsets is True. n x 2 matrix of cycle offsets with index going from 0 to n-1 and the columns being [‘start’, ‘stop’]:

    • start is the offset into peaks for start of cycle

    • stop is the offset into peaks for end of cycle

Notes

This algorithm is derived from reference [1]. This routine is a wrapper for either the C version (pyyeti.rainflow.c_rain()) or the Python version (pyyeti.rainflow.py_rain()) of the algorithm. Both versions give identical results. They also run in comparable times if numba.jit() is available (if import numba works). If numba.jit() is not available, the C version is much faster.

References

Examples

Run the example from the ASTM paper:

>>> from pyyeti.cyclecount import rainflow
>>> rainflow([-2, 1, -3, 5, -1, 3, -4, 4, -2])
   amp  mean  count
0  1.5  -0.5    0.5
1  2.0  -1.0    0.5
2  2.0   1.0    1.0
3  4.0   1.0    0.5
4  4.5   0.5    0.5
5  4.0   0.0    0.5
6  3.0   1.0    0.5

With offsets:

>>> rf, os = rainflow([-2, 1, -3, 5, -1, 3, -4, 4, -2],
...                   getoffsets=True)
>>> rf
   amp  mean  count
0  1.5  -0.5    0.5
1  2.0  -1.0    0.5
2  2.0   1.0    1.0
3  4.0   1.0    0.5
4  4.5   0.5    0.5
5  4.0   0.0    0.5
6  3.0   1.0    0.5
>>> os
   start  stop
0      0     1
1      1     2
2      4     5
3      2     3
4      3     6
5      6     7
6      7     8

If not using pandas:

>>> rf, os = rainflow([-2, 1, -3, 5, -1, 3, -4, 4, -2],
...                   getoffsets=True, use_pandas=False)
>>> rf
array([[ 1.5, -0.5,  0.5],
       [ 2. , -1. ,  0.5],
       [ 2. ,  1. ,  1. ],
       [ 4. ,  1. ,  0.5],
       [ 4.5,  0.5,  0.5],
       [ 4. ,  0. ,  0.5],
       [ 3. ,  1. ,  0.5]])
>>> os
array([[0, 1],
       [1, 2],
       [4, 5],
       [2, 3],
       [3, 6],
       [6, 7],
       [7, 8]]...)