Merge pull request #3437 from obspy/deprecations

adjust to a function name change in scipy

obspy/signal/array_analysis.py

@@ -21,7 +21,7 @@
 
 from matplotlib.dates import datestr2num
 import numpy as np
-from scipy.integrate import cumtrapz
+from scipy.integrate import cumulative_trapezoid
 
 from obspy.core import Stream
 from obspy.signal.headers import clibsignal
@@ -830,7 +830,7 @@ def array_transff_freqslowness(coords, slim, sstep, fmin, fmax, fstep,
                         complex(0., (coords[l, 0] * sx + coords[l, 1] * sy) *
                                 2 * np.pi * f))
                 buff[k] = abs(_sum) ** 2
-            transff[i, j] = cumtrapz(buff, dx=fstep)[-1]
+            transff[i, j] = cumulative_trapezoid(buff, dx=fstep)[-1]
 
     transff /= transff.max()
     return transff

obspy/signal/cpxtrace.py

@@ -17,7 +17,7 @@
 """
 import numpy as np
 from scipy import signal
-from scipy.integrate import cumtrapz
+from scipy.integrate import cumulative_trapezoid
 
 from . import util
 
@@ -94,7 +94,7 @@ def normalized_envelope(data, fs, smoothie, fk):
             # (dA/dt) / 2*PI*smooth(A)*fs/2
             t_ = t / (2. * np.pi * (a_win_smooth) * (fs / 2.0))
             # Integral within window
-            t_ = cumtrapz(t_, dx=(1. / fs))
+            t_ = cumulative_trapezoid(t_, dx=(1. / fs))
             t_ = np.concatenate((t_[0:1], t_))
             anorm[i] = ((np.exp(np.mean(t_))) - 1) * 100
             i = i + 1
@@ -123,7 +123,7 @@ def normalized_envelope(data, fs, smoothie, fk):
         a_win_smooth[a_win_smooth < 1] = 1
         t_ = t / (2. * np.pi * (a_win_smooth) * (fs / 2.0))
         # Integral within window
-        t_ = cumtrapz(t_, dx=(1.0 / fs))
+        t_ = cumulative_trapezoid(t_, dx=(1.0 / fs))
         t_ = np.concatenate((t_[0:1], t_))
         anorm = ((np.exp(np.mean(t_))) - 1) * 100
         return anorm

obspy/signal/differentiate_and_integrate.py

@@ -24,7 +24,7 @@ def integrate_cumtrapz(data, dx, **kwargs):
     # length of the array.
     # (manually adding the zero and not using `cumtrapz(..., initial=0)` is a
     # backwards compatibility fix for scipy versions < 0.11.
-    ret = scipy.integrate.cumtrapz(data, dx=dx)
+    ret = scipy.integrate.cumulative_trapezoid(data, dx=dx)
     return np.concatenate([np.array([0], dtype=ret.dtype), ret])