Merge branch 'master' into 'master'

Integration of HAWCio into Windio and further fatigue tools marging

One further step toward fully integrating prepost routines with pydap functionalities.
Now prepost gives exactly the same results as pydap.

See merge request !4

wetb/fatigue_tools/fatigue.py

@@ -70,7 +70,6 @@ def eq_load(signals, no_bins=46, m=[3, 4, 6, 8, 10, 12], neq=1, rainflow_func=ra
         return [[np.nan] * len(np.atleast_1d(m))] * len(np.atleast_1d(neq))
 
 
-
 def eq_load_and_cycles(signals, no_bins=46, m=[3, 4, 6, 8, 10, 12], neq=[10 ** 6, 10 ** 7, 10 ** 8], rainflow_func=rainflow_windap):
     """Calculate combined fatigue equivalent load
 
@@ -109,7 +108,6 @@ def eq_load_and_cycles(signals, no_bins=46, m=[3, 4, 6, 8, 10, 12], neq=[10 ** 6
     return eq_loads, cycles, ampl_bin_mean, ampl_bin_edges
 
 
-
 def cycle_matrix(signals, ampl_bins=10, mean_bins=10, rainflow_func=rainflow_windap):
     """Markow load cycle matrix
 
@@ -132,7 +130,8 @@ def cycle_matrix(signals, ampl_bins=10, mean_bins=10, rainflow_func=rainflow_win
     Returns
     -------
     cycles : ndarray, shape(ampl_bins, mean_bins)
-        A bi-dimensional histogram of load cycles(full cycles). Amplitudes are histogrammed along the first dimension and mean values are histogrammed along the second dimension.
+        A bi-dimensional histogram of load cycles(full cycles). Amplitudes are\
+        histogrammed along the first dimension and mean values are histogrammed along the second dimension.
     ampl_bin_mean : ndarray, shape(ampl_bins,)
         The average cycle amplitude of the bins
     ampl_edges : ndarray, shape(ampl_bins+1,)

wetb/fatigue_tools/rainflowcounting/rfc_hist.py

-from __future__ import division
-from __future__ import unicode_literals
-from __future__ import print_function
-from __future__ import absolute_import
-from future import standard_library
-standard_library.install_aliases()
-import numpy as np
-def rfc_hist(sig_rf, nrbins=46):
-    """Histogram of rainflow counted cycles
-
-    hist, bin_edges, bin_avg = rfc_hist(sig, nrbins=46)
-
-    Divide the rainflow counted cycles of a signal into equally spaced bins.
-
-    Created on Wed Feb 16 16:53:18 2011
-    @author: David Verelst
-    Modified 10.10.2011 by Mads M Pedersen to elimintate __copy__ and __eq__
-
-    Parameters
-    ----------
-    sig_rf : array-like
-        As output by rfc_astm or rainflow
-
-    nrbins : int, optional
-        Divide the rainflow counted amplitudes in a number of equally spaced
-        bins.
-
-    Returns
-    -------
-    hist : array-like
-        Counted rainflow cycles per bin, has nrbins elements
-
-    bin_edges : array-like
-        Edges of the bins, has nrbins+1 elements.
-
-    bin_avg : array-like
-        Average rainflow cycle amplitude per bin, has nrbins elements.
-    """
-
-    rf_half = sig_rf
-
-    # the Matlab approach is to divide into 46 bins
-    bin_edges = np.linspace(0, 1, num=nrbins + 1) * rf_half.max()
-    hist = np.histogram(rf_half, bins=bin_edges)[0]
-    # calculate the average per bin
-    hist_sum = np.histogram(rf_half, weights=rf_half, bins=bin_edges)[0]
-    # replace zeros with one, to avoid 0/0
-    hist_ = hist.copy()
-    hist_[(hist == 0).nonzero()] = 1.0
-    # since the sum is also 0, the avg remains zero for those whos hist is zero
-    bin_avg = hist_sum / hist_
-
-    return hist, bin_edges, bin_avg

wetb/hawc2/Hawc2io.py

@@ -90,8 +90,8 @@ class ReadHawc2(object):
         Name = []; Unit = []; Description = [];
         for i in range(0, self.NrCh):
             temp = str(Lines[i + 12][12:43]); Name.append(temp.strip())
-            temp = str(Lines[i + 12][43:48]); Unit.append(temp.strip())
-            temp = str(Lines[i + 12][49:]); Description.append(temp.strip())
+            temp = str(Lines[i + 12][43:54]); Unit.append(temp.strip())
+            temp = str(Lines[i + 12][54:-1]); Description.append(temp.strip())
         self.ChInfo = [Name, Unit, Description]
         # if binary file format, scaling factors are read
         if Format.lower() == 'binary':