Remove mlab.rk4

dstansby · dstansby · commit d3e26368b393 · 2018-09-29T11:05:05.000+01:00
diff --git a/doc/api/next_api_changes/2018-09-18-DS.rst b/doc/api/next_api_changes/2018-09-18-DS.rst
@@ -15,4 +15,5 @@ in Matplotlib 2.2 has been removed. See below for a list:
 - `mlab.prctile` (use numpy.percentile instead)
 - `mlab.prctile_rank`
 - `mlab.center_matrix`
+- `mlab.rk4` (use scipy.integrate.ode instead)
 - `mlab.donothing_callback`
diff --git a/lib/matplotlib/mlab.py b/lib/matplotlib/mlab.py
@@ -1194,77 +1194,6 @@ def cohere(x, y, NFFT=256, Fs=2, detrend=detrend_none, window=window_hanning,
     return Cxy, f
 
 
-@cbook.deprecated('2.2', 'scipy.integrate.ode')
-def rk4(derivs, y0, t):
-    """
-    Integrate 1D or ND system of ODEs using 4-th order Runge-Kutta.
-    This is a toy implementation which may be useful if you find
-    yourself stranded on a system w/o scipy.  Otherwise use
-    :func:`scipy.integrate`.
-
-    Parameters
-    ----------
-    y0
-        initial state vector
-
-    t
-        sample times
-
-    derivs
-        returns the derivative of the system and has the
-        signature ``dy = derivs(yi, ti)``
-
-    Examples
-    --------
-
-    A 2D system::
-
-        def derivs6(x,t):
-            d1 =  x[0] + 2*x[1]
-            d2 =  -3*x[0] + 4*x[1]
-            return (d1, d2)
-        dt = 0.0005
-        t = arange(0.0, 2.0, dt)
-        y0 = (1,2)
-        yout = rk4(derivs6, y0, t)
-
-    A 1D system::
-
-        alpha = 2
-        def derivs(x,t):
-            return -alpha*x + exp(-t)
-
-        y0 = 1
-        yout = rk4(derivs, y0, t)
-
-    If you have access to scipy, you should probably be using the
-    scipy.integrate tools rather than this function.
-    """
-
-    try:
-        Ny = len(y0)
-    except TypeError:
-        yout = np.zeros((len(t),), float)
-    else:
-        yout = np.zeros((len(t), Ny), float)
-
-    yout[0] = y0
-
-    for i in np.arange(len(t)-1):
-
-        thist = t[i]
-        dt = t[i+1] - thist
-        dt2 = dt/2.0
-        y0 = yout[i]
-
-        k1 = np.asarray(derivs(y0, thist))
-        k2 = np.asarray(derivs(y0 + dt2*k1, thist+dt2))
-        k3 = np.asarray(derivs(y0 + dt2*k2, thist+dt2))
-        k4 = np.asarray(derivs(y0 + dt*k3, thist+dt))
-        yout[i+1] = y0 + dt/6.0*(k1 + 2*k2 + 2*k3 + k4)
-    return yout
-
-
 @cbook.deprecated('2.2')
 def bivariate_normal(X, Y, sigmax=1.0, sigmay=1.0,
                      mux=0.0, muy=0.0, sigmaxy=0.0):
diff --git a/lib/matplotlib/pylab.py b/lib/matplotlib/pylab.py
@@ -237,7 +237,7 @@
     identity, inside_poly, is_closed_polygon, ispower2, isvector, l1norm,
     l2norm, log2, movavg, norm_flat,
     path_length, poly_below, poly_between,
-    rec2csv, rec_append_fields, rec_drop_fields, rec_join, rk4, rms_flat,
+    rec2csv, rec_append_fields, rec_drop_fields, rec_join, rms_flat,
     segments_intersect, slopes, stineman_interp, vector_lengths,
     window_hanning, window_none)
 
