Merge remote-tracking branch 'matplotlib/v1.5.x' into v2.x

Conflicts:
     doc/_templates/layout.html
        Edited text removed from 2.x version of website

Author: tacaswell

lib/matplotlib/axes/_axes.py

@@ -16,7 +16,8 @@
 
 import matplotlib.cbook as cbook
 from matplotlib.cbook import (mplDeprecation, STEP_LOOKUP_MAP,
-                              iterable, is_string_like)
+                              iterable, is_string_like,
+                              safe_first_element)
 import matplotlib.collections as mcoll
 import matplotlib.colors as mcolors
 import matplotlib.contour as mcontour
@@ -2903,29 +2904,44 @@ def xywhere(xs, ys, mask):
             if key in kwargs:
                 plot_kw[key] = kwargs[key]
 
-        if xerr is not None:
-            if (iterable(xerr) and len(xerr) == 2 and
-                    iterable(xerr[0]) and iterable(xerr[1])):
-                # using list comps rather than arrays to preserve units
-                left = [thisx - thiserr for (thisx, thiserr)
-                        in cbook.safezip(x, xerr[0])]
-                right = [thisx + thiserr for (thisx, thiserr)
-                         in cbook.safezip(x, xerr[1])]
-            else:
-                # Check if xerr is scalar or symmetric. Asymmetric is handled
-                # above. This prevents Nx2 arrays from accidentally
-                # being accepted, when the user meant the 2xN transpose.
-                # special case for empty lists
-                if len(xerr) > 1 and not ((len(xerr) == len(x) and not (
-                        iterable(xerr[0]) and len(xerr[0]) > 1))):
-                    raise ValueError("xerr must be a scalar, the same "
+        def extract_err(err, data):
+            '''private function to compute error bars
+
+            Parameters
+            ----------
+            err : iterable
+                xerr or yerr from errorbar
+            data : iterable
+                x or y from errorbar
+            '''
+            if (iterable(err) and len(err) == 2):
+                a, b = err
+                if iterable(a) and iterable(b):
+                    # using list comps rather than arrays to preserve units
+                    low = [thisx - thiserr for (thisx, thiserr)
+                           in cbook.safezip(data, a)]
+                    high = [thisx + thiserr for (thisx, thiserr)
+                            in cbook.safezip(data, b)]
+                    return low, high
+            # Check if xerr is scalar or symmetric. Asymmetric is handled
+            # above. This prevents Nx2 arrays from accidentally
+            # being accepted, when the user meant the 2xN transpose.
+            # special case for empty lists
+            if len(err) > 1:
+                fe = safe_first_element(err)
+                if not ((len(err) == len(data) and not (iterable(fe) and
+                                                        len(fe) > 1))):
+                    raise ValueError("err must be a scalar, the same "
                                      "dimensions as x, or 2xN.")
-                # using list comps rather than arrays to preserve units
-                left = [thisx - thiserr for (thisx, thiserr)
-                        in cbook.safezip(x, xerr)]
-                right = [thisx + thiserr for (thisx, thiserr)
-                         in cbook.safezip(x, xerr)]
+            # using list comps rather than arrays to preserve units
+            low = [thisx - thiserr for (thisx, thiserr)
+                   in cbook.safezip(data, err)]
+            high = [thisx + thiserr for (thisx, thiserr)
+                    in cbook.safezip(data, err)]
+            return low, high
 
+        if xerr is not None:
+            left, right = extract_err(xerr, x)
             # select points without upper/lower limits in x and
             # draw normal errorbars for these points
             noxlims = ~(xlolims | xuplims)
@@ -2970,25 +2986,7 @@ def xywhere(xs, ys, mask):
                     caplines.extend(self.plot(xup, yup, 'k|', **plot_kw))
 
         if yerr is not None:
-            if (iterable(yerr) and len(yerr) == 2 and
-                    iterable(yerr[0]) and iterable(yerr[1])):
-                # using list comps rather than arrays to preserve units
-                lower = [thisy - thiserr for (thisy, thiserr)
-                         in cbook.safezip(y, yerr[0])]
-                upper = [thisy + thiserr for (thisy, thiserr)
-                         in cbook.safezip(y, yerr[1])]
-            else:
-                # Check for scalar or symmetric, as in xerr.
-                if len(yerr) > 1 and not ((len(yerr) == len(y) and not (
-                        iterable(yerr[0]) and len(yerr[0]) > 1))):
-                    raise ValueError("yerr must be a scalar, the same "
-                                     "dimensions as y, or 2xN.")
-                # using list comps rather than arrays to preserve units
-                lower = [thisy - thiserr for (thisy, thiserr)
-                         in cbook.safezip(y, yerr)]
-                upper = [thisy + thiserr for (thisy, thiserr)
-                         in cbook.safezip(y, yerr)]
-
+            lower, upper = extract_err(yerr, y)
             # select points without upper/lower limits in y and
             # draw normal errorbars for these points
             noylims = ~(lolims | uplims)

lib/matplotlib/mlab.py

@@ -3185,35 +3185,20 @@ def get_type(item, atype=int):
         return atype
 
     def get_justify(colname, column, precision):
-        ntype = type(column[0])
+        ntype = column.dtype
 
-        if (ntype == np.str or ntype == np.str_ or ntype == np.string0 or
-                ntype == np.string_):
-            length = max(len(colname), column.itemsize)
+        if np.issubdtype(ntype, str) or np.issubdtype(ntype, bytes):
+            # The division below handles unicode stored in array, which could
+            # have 4 bytes per char
+            length = max(len(colname), column.itemsize // column[0].itemsize)
             return 0, length+padding, "%s"  # left justify
 
-        if (ntype == np.int or ntype == np.int16 or ntype == np.int32 or
-                ntype == np.int64 or ntype == np.int8 or ntype == np.int_):
+        if np.issubdtype(ntype, np.int):
             length = max(len(colname),
                          np.max(list(map(len, list(map(str, column))))))
             return 1, length+padding, "%d"  # right justify
 
-        # JDH: my powerbook does not have np.float96 using np 1.3.0
-        """
-        In [2]: np.__version__
-        Out[2]: '1.3.0.dev5948'
-
-        In [3]: !uname -a
-        Darwin Macintosh-5.local 9.4.0 Darwin Kernel Version 9.4.0: Mon Jun
-        9 19:30:53 PDT 2008; root:xnu-1228.5.20~1/RELEASE_I386 i386 i386
-
-        In [4]: np.float96
-        ---------------------------------------------------------------------------
-        AttributeError                           Traceback (most recent call la
-        """
-        if (ntype == np.float or ntype == np.float32 or ntype == np.float64 or
-                (hasattr(np, 'float96') and (ntype == np.float96)) or
-                ntype == np.float_):
+        if np.issubdtype(ntype, np.float):
             fmt = "%." + str(precision) + "f"
             length = max(
                 len(colname),

lib/matplotlib/tests/test_axes.py

@@ -4339,6 +4339,20 @@ def test_pandas_indexing_dates():
     ax.plot('dates', 'values', data=without_zero_index)
 
 
+@cleanup
+def test_pandas_errorbar_indexing():
+    try:
+        import pandas as pd
+    except ImportError:
+        raise SkipTest("Pandas not installed")
+
+    df = pd.DataFrame(np.random.uniform(size=(5, 4)),
+                      columns=['x', 'y', 'xe', 'ye'],
+                      index=[1, 2, 3, 4, 5])
+    fig, ax = plt.subplots()
+    ax.errorbar('x', 'y', xerr='xe', yerr='ye', data=df)
+
+
 @cleanup
 def test_pandas_indexing_hist():
     try:

lib/matplotlib/tests/test_mlab.py

@@ -393,6 +393,22 @@ def test_csv2rec_yearfirst(self):
         assert_array_equal(array['a'].tolist(), expected)
 
 
+class rec2txt_testcase(CleanupTestCase):
+    def test_csv2txt_basic(self):
+        # str() calls around field names necessary b/c as of numpy 1.11
+        # dtype doesn't like unicode names (caused by unicode_literals import)
+        a = np.array([(1.0, 2, 'foo', 'bing'),
+                      (2.0, 3, 'bar', 'blah')],
+                     dtype=np.dtype([(str('x'), np.float32),
+                                     (str('y'), np.int8),
+                                     (str('s'), str, 3),
+                                     (str('s2'), str, 4)]))
+        truth = ('       x   y   s   s2\n'
+                 '   1.000   2   foo bing \n'
+                 '   2.000   3   bar blah ')
+        assert_equal(mlab.rec2txt(a), truth)
+
+
 class window_testcase(CleanupTestCase):
     def setUp(self):
         np.random.seed(0)