Merge pull request #18652 from timhoffm/doc-plot

DOC: Update some plotting code to current Matplotlib idioms

7 files changed, 21 insertions, 15 deletions

diff --git a/doc/source/reference/routines.polynomials.classes.rst b/doc/source/reference/routines.polynomials.classes.rst
index 10331e9c1..5f575bed1 100644
--- a/doc/source/reference/routines.polynomials.classes.rst
+++ b/doc/source/reference/routines.polynomials.classes.rst
@@ -290,7 +290,8 @@ polynomials up to degree 5 are plotted below.
     >>> import matplotlib.pyplot as plt
     >>> from numpy.polynomial import Chebyshev as T
     >>> x = np.linspace(-1, 1, 100)
-    >>> for i in range(6): ax = plt.plot(x, T.basis(i)(x), lw=2, label="$T_%d$"%i)
+    >>> for i in range(6):
+    ...     ax = plt.plot(x, T.basis(i)(x), lw=2, label=f"$T_{i}$")
     ...
     >>> plt.legend(loc="upper left")
     <matplotlib.legend.Legend object at 0x3b3ee10>
@@ -304,7 +305,8 @@ The same plots over the range -2 <= `x` <= 2 look very different:
     >>> import matplotlib.pyplot as plt
     >>> from numpy.polynomial import Chebyshev as T
     >>> x = np.linspace(-2, 2, 100)
-    >>> for i in range(6): ax = plt.plot(x, T.basis(i)(x), lw=2, label="$T_%d$"%i)
+    >>> for i in range(6):
+    ...     ax = plt.plot(x, T.basis(i)(x), lw=2, label=f"$T_{i}$")
     ...
     >>> plt.legend(loc="lower right")
     <matplotlib.legend.Legend object at 0x3b3ee10>
diff --git a/doc/source/user/absolute_beginners.rst b/doc/source/user/absolute_beginners.rst
index 126f5f2a3..fda73c5fb 100644
--- a/doc/source/user/absolute_beginners.rst
+++ b/doc/source/user/absolute_beginners.rst
@@ -1672,9 +1672,8 @@ For example, you can plot a 1D array like this::
 
 With Matplotlib, you have access to an enormous number of visualization options. ::
 
-  >>> from mpl_toolkits.mplot3d import Axes3D
   >>> fig = plt.figure()
-  >>> ax = Axes3D(fig)
+  >>> ax = fig.add_subplot(projection='3d')
   >>> X = np.arange(-5, 5, 0.15)
   >>> Y = np.arange(-5, 5, 0.15)
   >>> X, Y = np.meshgrid(X, Y)
diff --git a/doc/source/user/plots/matplotlib3.py b/doc/source/user/plots/matplotlib3.py
index 20a8c0767..7b56067ef 100644
--- a/doc/source/user/plots/matplotlib3.py
+++ b/doc/source/user/plots/matplotlib3.py
@@ -1,9 +1,8 @@
 import numpy as np
 import matplotlib.pyplot as plt
-from mpl_toolkits.mplot3d import Axes3D
 
 fig = plt.figure()
-ax = Axes3D(fig)
+ax = fig.add_subplot(projection='3d')
 X = np.arange(-5, 5, 0.15)
 Y = np.arange(-5, 5, 0.15)
 X, Y = np.meshgrid(X, Y)
diff --git a/doc/source/user/quickstart.rst b/doc/source/user/quickstart.rst
index b50d8a5ba..28262c89e 100644
--- a/doc/source/user/quickstart.rst
+++ b/doc/source/user/quickstart.rst
@@ -1464,11 +1464,13 @@ that ``pylab.hist`` plots the histogram automatically, while
     >>> mu, sigma = 2, 0.5
     >>> v = rg.normal(mu, sigma, 10000)
     >>> # Plot a normalized histogram with 50 bins
-    >>> plt.hist(v, bins=50, density=1)       # matplotlib version (plot)
+    >>> plt.hist(v, bins=50, density=True)       # matplotlib version (plot)
     >>> # Compute the histogram with numpy and then plot it
     >>> (n, bins) = np.histogram(v, bins=50, density=True)  # NumPy version (no plot)
     >>> plt.plot(.5 * (bins[1:] + bins[:-1]), n)
 
+With Matplotlib >=3.4 you can also use ``plt.stairs(n, bins)``.
+
 
 Further reading
 ===============
diff --git a/doc/source/user/tutorial-ma.rst b/doc/source/user/tutorial-ma.rst
index 88bad3cbe..a21c4aae1 100644
--- a/doc/source/user/tutorial-ma.rst
+++ b/doc/source/user/tutorial-ma.rst
@@ -366,12 +366,13 @@ after the beginning of the records:
 
 .. ipython:: python
 
-    plt.plot(t, china_total);
-    plt.plot(t[china_total.mask], cubic_fit[china_total.mask], '--', color='orange');
-    plt.plot(7, np.polyval(params, 7), 'r*');
+    plt.plot(t, china_total, label='Mainland China');
+    plt.plot(t[china_total.mask], cubic_fit[china_total.mask], '--',
+             color='orange', label='Cubic estimate');
+    plt.plot(7, np.polyval(params, 7), 'r*', label='7 days after start');
     plt.xticks([0, 7, 13], dates[[0, 7, 13]]);
     plt.yticks([0, np.polyval(params, 7), 10000, 17500]);
-    plt.legend(['Mainland China', 'Cubic estimate', '7 days after start']);
+    plt.legend();
     @savefig plot_covid_5.png
     plt.title("COVID-19 cumulative cases from Jan 21 to Feb 3 2020 - Mainland China\n"
               "Cubic estimate for 7 days after start");
diff --git a/numpy/fft/_pocketfft.py b/numpy/fft/_pocketfft.py
index 4ed3042a6..ad69f7c83 100644
--- a/numpy/fft/_pocketfft.py
+++ b/numpy/fft/_pocketfft.py
@@ -300,9 +300,11 @@ def ifft(a, n=None, axis=-1, norm=None):
     >>> n = np.zeros((400,), dtype=complex)
     >>> n[40:60] = np.exp(1j*np.random.uniform(0, 2*np.pi, (20,)))
     >>> s = np.fft.ifft(n)
-    >>> plt.plot(t, s.real, 'b-', t, s.imag, 'r--')
-    [<matplotlib.lines.Line2D object at ...>, <matplotlib.lines.Line2D object at ...>]
-    >>> plt.legend(('real', 'imaginary'))
+    >>> plt.plot(t, s.real, label='real')
+    [<matplotlib.lines.Line2D object at ...>]
+    >>> plt.plot(t, s.imag, '--', label='imaginary')
+    [<matplotlib.lines.Line2D object at ...>]
+    >>> plt.legend()
     <matplotlib.legend.Legend object at ...>
     >>> plt.show()
 
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index 44eac31ef..285f90a6f 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -4276,7 +4276,8 @@ def meshgrid(*xi, copy=True, sparse=False, indexing='xy'):
     >>> y = np.arange(-5, 5, 0.1)
     >>> xx, yy = np.meshgrid(x, y, sparse=True)
     >>> z = np.sin(xx**2 + yy**2) / (xx**2 + yy**2)
-    >>> h = plt.contourf(x,y,z)
+    >>> h = plt.contourf(x, y, z)
+    >>> plt.axis('scaled')
     >>> plt.show()
 
     """