matplotlib & pandas

Python/matplotlab/gallery/userdemo/anchored_box01.md

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+# 锚定Box01
+
+![锚定Box01示例](https://matplotlib.org/_images/sphx_glr_anchored_box01_001.png)
+
+```python
+import matplotlib.pyplot as plt
+from matplotlib.offsetbox import AnchoredText
+
+
+fig, ax = plt.subplots(figsize=(3, 3))
+
+at = AnchoredText("Figure 1a",
+                  prop=dict(size=15), frameon=True, loc='upper left')
+at.patch.set_boxstyle("round,pad=0.,rounding_size=0.2")
+ax.add_artist(at)
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: anchored_box01.py](https://matplotlib.org/_downloads/anchored_box01.py)
+- [下载Jupyter notebook: anchored_box01.ipynb](https://matplotlib.org/_downloads/anchored_box01.ipynb)

Python/matplotlab/gallery/userdemo/anchored_box02.md

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+# 锚定Box02
+
+![锚定Box02示例](https://matplotlib.org/_images/sphx_glr_anchored_box02_001.png)
+
+```python
+from matplotlib.patches import Circle
+import matplotlib.pyplot as plt
+from mpl_toolkits.axes_grid1.anchored_artists import AnchoredDrawingArea
+
+
+fig, ax = plt.subplots(figsize=(3, 3))
+
+ada = AnchoredDrawingArea(40, 20, 0, 0,
+                          loc='upper right', pad=0., frameon=False)
+p1 = Circle((10, 10), 10)
+ada.drawing_area.add_artist(p1)
+p2 = Circle((30, 10), 5, fc="r")
+ada.drawing_area.add_artist(p2)
+
+ax.add_artist(ada)
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: anchored_box02.py](https://matplotlib.org/_downloads/anchored_box02.py)
+- [下载Jupyter notebook: anchored_box02.ipynb](https://matplotlib.org/_downloads/anchored_box02.ipynb)

Python/matplotlab/gallery/userdemo/anchored_box03.md

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+# 锚定Box03
+
+![锚定Box03示例](https://matplotlib.org/_images/sphx_glr_anchored_box03_001.png)
+
+```python
+from matplotlib.patches import Ellipse
+import matplotlib.pyplot as plt
+from mpl_toolkits.axes_grid1.anchored_artists import AnchoredAuxTransformBox
+
+
+fig, ax = plt.subplots(figsize=(3, 3))
+
+box = AnchoredAuxTransformBox(ax.transData, loc='upper left')
+el = Ellipse((0, 0), width=0.1, height=0.4, angle=30)  # in data coordinates!
+box.drawing_area.add_artist(el)
+
+ax.add_artist(box)
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: anchored_box03.py](https://matplotlib.org/_downloads/anchored_box03.py)
+- [下载Jupyter notebook: anchored_box03.ipynb](https://matplotlib.org/_downloads/anchored_box03.ipynb)

Python/matplotlab/gallery/userdemo/anchored_box04.md

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+# 锚定Box04
+
+![锚定Box04示例](https://matplotlib.org/_images/sphx_glr_anchored_box04_001.png)
+
+```python
+from matplotlib.patches import Ellipse
+import matplotlib.pyplot as plt
+from matplotlib.offsetbox import (AnchoredOffsetbox, DrawingArea, HPacker,
+                                  TextArea)
+
+
+fig, ax = plt.subplots(figsize=(3, 3))
+
+box1 = TextArea(" Test : ", textprops=dict(color="k"))
+
+box2 = DrawingArea(60, 20, 0, 0)
+el1 = Ellipse((10, 10), width=16, height=5, angle=30, fc="r")
+el2 = Ellipse((30, 10), width=16, height=5, angle=170, fc="g")
+el3 = Ellipse((50, 10), width=16, height=5, angle=230, fc="b")
+box2.add_artist(el1)
+box2.add_artist(el2)
+box2.add_artist(el3)
+
+box = HPacker(children=[box1, box2],
+              align="center",
+              pad=0, sep=5)
+
+anchored_box = AnchoredOffsetbox(loc='lower left',
+                                 child=box, pad=0.,
+                                 frameon=True,
+                                 bbox_to_anchor=(0., 1.02),
+                                 bbox_transform=ax.transAxes,
+                                 borderpad=0.,
+                                 )
+
+ax.add_artist(anchored_box)
+
+fig.subplots_adjust(top=0.8)
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: anchored_box04.py](https://matplotlib.org/_downloads/anchored_box04.py)
+- [下载Jupyter notebook: anchored_box04.ipynb](https://matplotlib.org/_downloads/anchored_box04.ipynb)

Python/matplotlab/gallery/userdemo/annotate_explain.md

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+# 注释说明
+
+![注释说明示例](https://matplotlib.org/_images/sphx_glr_annotate_explain_001.png)
+
+```python
+import matplotlib.pyplot as plt
+import matplotlib.patches as mpatches
+
+
+fig, axs = plt.subplots(2, 2)
+x1, y1 = 0.3, 0.3
+x2, y2 = 0.7, 0.7
+
+ax = axs.flat[0]
+ax.plot([x1, x2], [y1, y2], ".")
+el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.2)
+ax.add_artist(el)
+ax.annotate("",
+            xy=(x1, y1), xycoords='data',
+            xytext=(x2, y2), textcoords='data',
+            arrowprops=dict(arrowstyle="-",
+                            color="0.5",
+                            patchB=None,
+                            shrinkB=0,
+                            connectionstyle="arc3,rad=0.3",
+                            ),
+            )
+ax.text(.05, .95, "connect", transform=ax.transAxes, ha="left", va="top")
+
+ax = axs.flat[1]
+ax.plot([x1, x2], [y1, y2], ".")
+el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.2)
+ax.add_artist(el)
+ax.annotate("",
+            xy=(x1, y1), xycoords='data',
+            xytext=(x2, y2), textcoords='data',
+            arrowprops=dict(arrowstyle="-",
+                            color="0.5",
+                            patchB=el,
+                            shrinkB=0,
+                            connectionstyle="arc3,rad=0.3",
+                            ),
+            )
+ax.text(.05, .95, "clip", transform=ax.transAxes, ha="left", va="top")
+
+ax = axs.flat[2]
+ax.plot([x1, x2], [y1, y2], ".")
+el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.2)
+ax.add_artist(el)
+ax.annotate("",
+            xy=(x1, y1), xycoords='data',
+            xytext=(x2, y2), textcoords='data',
+            arrowprops=dict(arrowstyle="-",
+                            color="0.5",
+                            patchB=el,
+                            shrinkB=5,
+                            connectionstyle="arc3,rad=0.3",
+                            ),
+            )
+ax.text(.05, .95, "shrink", transform=ax.transAxes, ha="left", va="top")
+
+ax = axs.flat[3]
+ax.plot([x1, x2], [y1, y2], ".")
+el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.2)
+ax.add_artist(el)
+ax.annotate("",
+            xy=(x1, y1), xycoords='data',
+            xytext=(x2, y2), textcoords='data',
+            arrowprops=dict(arrowstyle="fancy",
+                            color="0.5",
+                            patchB=el,
+                            shrinkB=5,
+                            connectionstyle="arc3,rad=0.3",
+                            ),
+            )
+ax.text(.05, .95, "mutate", transform=ax.transAxes, ha="left", va="top")
+
+for ax in axs.flat:
+    ax.set(xlim=(0, 1), ylim=(0, 1), xticks=[], yticks=[], aspect=1)
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: annotate_explain.py](https://matplotlib.org/_downloads/annotate_explain.py)
+- [下载Jupyter notebook: annotate_explain.ipynb](https://matplotlib.org/_downloads/annotate_explain.ipynb)

Python/matplotlab/gallery/userdemo/annotate_simple01.md

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+# 注释Simple01
+
+![注释Simple01示例](https://matplotlib.org/_images/sphx_glr_annotate_simple01_001.png)
+
+```python
+import matplotlib.pyplot as plt
+
+
+fig, ax = plt.subplots(figsize=(3, 3))
+
+ax.annotate("",
+            xy=(0.2, 0.2), xycoords='data',
+            xytext=(0.8, 0.8), textcoords='data',
+            arrowprops=dict(arrowstyle="->",
+                            connectionstyle="arc3"),
+            )
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: annotate_simple01.py](https://matplotlib.org/_downloads/annotate_simple01.py)
+- [下载Jupyter notebook: annotate_simple01.ipynb](https://matplotlib.org/_downloads/annotate_simple01.ipynb)

Python/matplotlab/gallery/userdemo/annotate_simple02.md

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+# 注释Simple02
+
+![注释Simple02示例](https://matplotlib.org/_images/sphx_glr_annotate_simple02_001.png)
+
+```python
+import matplotlib.pyplot as plt
+
+
+fig, ax = plt.subplots(figsize=(3, 3))
+
+ax.annotate("Test",
+            xy=(0.2, 0.2), xycoords='data',
+            xytext=(0.8, 0.8), textcoords='data',
+            size=20, va="center", ha="center",
+            arrowprops=dict(arrowstyle="simple",
+                            connectionstyle="arc3,rad=-0.2"),
+            )
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: annotate_simple02.py](https://matplotlib.org/_downloads/annotate_simple02.py)
+- [下载Jupyter notebook: annotate_simple02.ipynb](https://matplotlib.org/_downloads/annotate_simple02.ipynb)

Python/matplotlab/gallery/userdemo/annotate_simple03.md

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+# 注释Simple03
+
+![注释Simple03示例](https://matplotlib.org/_images/sphx_glr_annotate_simple03_001.png)
+
+```python
+import matplotlib.pyplot as plt
+
+
+fig, ax = plt.subplots(figsize=(3, 3))
+
+ann = ax.annotate("Test",
+                  xy=(0.2, 0.2), xycoords='data',
+                  xytext=(0.8, 0.8), textcoords='data',
+                  size=20, va="center", ha="center",
+                  bbox=dict(boxstyle="round4", fc="w"),
+                  arrowprops=dict(arrowstyle="-|>",
+                                  connectionstyle="arc3,rad=-0.2",
+                                  fc="w"),
+                  )
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: annotate_simple03.py](https://matplotlib.org/_downloads/annotate_simple03.py)
+- [下载Jupyter notebook: annotate_simple03.ipynb](https://matplotlib.org/_downloads/annotate_simple03.ipynb)

Python/matplotlab/gallery/userdemo/annotate_simple04.md

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+# 注释Simple04
+
+![注释Simple04示例](https://matplotlib.org/_images/sphx_glr_annotate_simple04_001.png)
+
+```python
+import matplotlib.pyplot as plt
+
+
+fig, ax = plt.subplots(figsize=(3, 3))
+
+ann = ax.annotate("Test",
+                  xy=(0.2, 0.2), xycoords='data',
+                  xytext=(0.8, 0.8), textcoords='data',
+                  size=20, va="center", ha="center",
+                  bbox=dict(boxstyle="round4", fc="w"),
+                  arrowprops=dict(arrowstyle="-|>",
+                                  connectionstyle="arc3,rad=0.2",
+                                  relpos=(0., 0.),
+                                  fc="w"),
+                  )
+
+ann = ax.annotate("Test",
+                  xy=(0.2, 0.2), xycoords='data',
+                  xytext=(0.8, 0.8), textcoords='data',
+                  size=20, va="center", ha="center",
+                  bbox=dict(boxstyle="round4", fc="w"),
+                  arrowprops=dict(arrowstyle="-|>",
+                                  connectionstyle="arc3,rad=-0.2",
+                                  relpos=(1., 0.),
+                                  fc="w"),
+                  )
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: annotate_simple04.py](https://matplotlib.org/_downloads/annotate_simple04.py)
+- [下载Jupyter notebook: annotate_simple04.ipynb](https://matplotlib.org/_downloads/annotate_simple04.ipynb)

Python/matplotlab/gallery/userdemo/annotate_simple_coord01.md

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+# 简单Coord01注释示例
+
+![简单Coord01注释示例](https://matplotlib.org/_images/sphx_glr_annotate_simple_coord01_001.png)
+
+```python
+import matplotlib.pyplot as plt
+
+fig, ax = plt.subplots(figsize=(3, 2))
+an1 = ax.annotate("Test 1", xy=(0.5, 0.5), xycoords="data",
+                  va="center", ha="center",
+                  bbox=dict(boxstyle="round", fc="w"))
+an2 = ax.annotate("Test 2", xy=(1, 0.5), xycoords=an1,
+                  xytext=(30, 0), textcoords="offset points",
+                  va="center", ha="left",
+                  bbox=dict(boxstyle="round", fc="w"),
+                  arrowprops=dict(arrowstyle="->"))
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: annotate_simple_coord01.py](https://matplotlib.org/_downloads/annotate_simple_coord01.py)
+- [下载Jupyter notebook: annotate_simple_coord01.ipynb](https://matplotlib.org/_downloads/annotate_simple_coord01.ipynb)
+

Python/matplotlab/gallery/userdemo/annotate_simple_coord02.md

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+# 简单Coord02注释示例
+
+![简单Coord02注释示例](https://matplotlib.org/_images/sphx_glr_annotate_simple_coord02_001.png)
+
+```python
+import matplotlib.pyplot as plt
+
+
+fig, ax = plt.subplots(figsize=(3, 2))
+an1 = ax.annotate("Test 1", xy=(0.5, 0.5), xycoords="data",
+                  va="center", ha="center",
+                  bbox=dict(boxstyle="round", fc="w"))
+
+an2 = ax.annotate("Test 2", xy=(0.5, 1.), xycoords=an1,
+                  xytext=(0.5, 1.1), textcoords=(an1, "axes fraction"),
+                  va="bottom", ha="center",
+                  bbox=dict(boxstyle="round", fc="w"),
+                  arrowprops=dict(arrowstyle="->"))
+
+fig.subplots_adjust(top=0.83)
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: annotate_simple_coord02.py](https://matplotlib.org/_downloads/annotate_simple_coord02.py)
+- [下载Jupyter notebook: annotate_simple_coord02.ipynb](https://matplotlib.org/_downloads/annotate_simple_coord02.ipynb)

Python/matplotlab/gallery/userdemo/annotate_simple_coord03.md

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+# 简单Coord03注释示例
+
+![简单Coord03注释示例](https://matplotlib.org/_images/sphx_glr_annotate_simple_coord03_001.png)
+
+```python
+import matplotlib.pyplot as plt
+from matplotlib.text import OffsetFrom
+
+
+fig, ax = plt.subplots(figsize=(3, 2))
+an1 = ax.annotate("Test 1", xy=(0.5, 0.5), xycoords="data",
+                  va="center", ha="center",
+                  bbox=dict(boxstyle="round", fc="w"))
+
+offset_from = OffsetFrom(an1, (0.5, 0))
+an2 = ax.annotate("Test 2", xy=(0.1, 0.1), xycoords="data",
+                  xytext=(0, -10), textcoords=offset_from,
+                  # xytext is offset points from "xy=(0.5, 0), xycoords=an1"
+                  va="top", ha="center",
+                  bbox=dict(boxstyle="round", fc="w"),
+                  arrowprops=dict(arrowstyle="->"))
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: annotate_simple_coord03.py](https://matplotlib.org/_downloads/annotate_simple_coord03.py)
+- [下载Jupyter notebook: annotate_simple_coord03.ipynb](https://matplotlib.org/_downloads/annotate_simple_coord03.ipynb)

Python/matplotlab/gallery/userdemo/annotate_text_arrow.md

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+# 注释文本箭头
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+
+fig, ax = plt.subplots(figsize=(5, 5))
+ax.set_aspect(1)
+
+x1 = -1 + np.random.randn(100)
+y1 = -1 + np.random.randn(100)
+x2 = 1. + np.random.randn(100)
+y2 = 1. + np.random.randn(100)
+
+ax.scatter(x1, y1, color="r")
+ax.scatter(x2, y2, color="g")
+
+bbox_props = dict(boxstyle="round", fc="w", ec="0.5", alpha=0.9)
+ax.text(-2, -2, "Sample A", ha="center", va="center", size=20,
+        bbox=bbox_props)
+ax.text(2, 2, "Sample B", ha="center", va="center", size=20,
+        bbox=bbox_props)
+
+
+bbox_props = dict(boxstyle="rarrow", fc=(0.8, 0.9, 0.9), ec="b", lw=2)
+t = ax.text(0, 0, "Direction", ha="center", va="center", rotation=45,
+            size=15,
+            bbox=bbox_props)
+
+bb = t.get_bbox_patch()
+bb.set_boxstyle("rarrow", pad=0.6)
+
+ax.set_xlim(-4, 4)
+ax.set_ylim(-4, 4)
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: annotate_text_arrow.py](https://matplotlib.org/_downloads/annotate_text_arrow.py)
+- [下载Jupyter notebook: annotate_text_arrow.ipynb](https://matplotlib.org/_downloads/annotate_text_arrow.ipynb)

Python/matplotlab/gallery/userdemo/colormap_normalizations.md

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+# 色彩映射规范化
+
+演示使用norm以非线性方式映射颜色映射。
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.colors as colors
+```
+
+Lognorm: Instead of pcolor log10(Z1) you can have colorbars that have
+the exponential labels using a norm.
+
+```python
+N = 100
+X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)]
+
+# A low hump with a spike coming out of the top.  Needs to have
+# z/colour axis on a log scale so we see both hump and spike.  linear
+# scale only shows the spike.
+
+Z1 = np.exp(-(X)**2 - (Y)**2)
+Z2 = np.exp(-(X * 10)**2 - (Y * 10)**2)
+Z = Z1 + 50 * Z2
+
+fig, ax = plt.subplots(2, 1)
+
+pcm = ax[0].pcolor(X, Y, Z,
+                   norm=colors.LogNorm(vmin=Z.min(), vmax=Z.max()),
+                   cmap='PuBu_r')
+fig.colorbar(pcm, ax=ax[0], extend='max')
+
+pcm = ax[1].pcolor(X, Y, Z, cmap='PuBu_r')
+fig.colorbar(pcm, ax=ax[1], extend='max')
+```
+
+![色彩映射规范化示例](https://matplotlib.org/_images/sphx_glr_colormap_normalizations_001.png)
+
+PowerNorm：这是X中的幂律趋势，部分遮蔽了Y中的整流正弦波。我们可以使用PowerNorm来消除幂律。
+
+```python
+X, Y = np.mgrid[0:3:complex(0, N), 0:2:complex(0, N)]
+Z1 = (1 + np.sin(Y * 10.)) * X**(2.)
+
+fig, ax = plt.subplots(2, 1)
+
+pcm = ax[0].pcolormesh(X, Y, Z1, norm=colors.PowerNorm(gamma=1. / 2.),
+                       cmap='PuBu_r')
+fig.colorbar(pcm, ax=ax[0], extend='max')
+
+pcm = ax[1].pcolormesh(X, Y, Z1, cmap='PuBu_r')
+fig.colorbar(pcm, ax=ax[1], extend='max')
+```
+
+![色彩映射规范化示例2](https://matplotlib.org/_images/sphx_glr_colormap_normalizations_002.png)
+
+SymLogNorm：两个驼峰，一个正面和一个正面，正面具有5倍幅度。 线性地，你看不到负面的驼峰。 在这里，我们分别以对数方式对正负数据进行对数。
+
+请注意，颜色条标签看起来不是很好。
+
+```python
+X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)]
+Z1 = 5 * np.exp(-X**2 - Y**2)
+Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
+Z = (Z1 - Z2) * 2
+
+fig, ax = plt.subplots(2, 1)
+
+pcm = ax[0].pcolormesh(X, Y, Z1,
+                       norm=colors.SymLogNorm(linthresh=0.03, linscale=0.03,
+                                              vmin=-1.0, vmax=1.0),
+                       cmap='RdBu_r')
+fig.colorbar(pcm, ax=ax[0], extend='both')
+
+pcm = ax[1].pcolormesh(X, Y, Z1, cmap='RdBu_r', vmin=-np.max(Z1))
+fig.colorbar(pcm, ax=ax[1], extend='both')
+```
+
+![色彩映射规范化示例3](https://matplotlib.org/_images/sphx_glr_colormap_normalizations_003.png)
+
+自定义范例：自定义规范化的示例。这个使用上面的例子，并从负数标准化负数据。
+
+```python
+X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)]
+Z1 = np.exp(-X**2 - Y**2)
+Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
+Z = (Z1 - Z2) * 2
+
+# Example of making your own norm.  Also see matplotlib.colors.
+# From Joe Kington: This one gives two different linear ramps:
+
+
+class MidpointNormalize(colors.Normalize):
+    def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):
+        self.midpoint = midpoint
+        colors.Normalize.__init__(self, vmin, vmax, clip)
+
+    def __call__(self, value, clip=None):
+        # I'm ignoring masked values and all kinds of edge cases to make a
+        # simple example...
+        x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]
+        return np.ma.masked_array(np.interp(value, x, y))
+
+
+#####
+fig, ax = plt.subplots(2, 1)
+
+pcm = ax[0].pcolormesh(X, Y, Z,
+                       norm=MidpointNormalize(midpoint=0.),
+                       cmap='RdBu_r')
+fig.colorbar(pcm, ax=ax[0], extend='both')
+
+pcm = ax[1].pcolormesh(X, Y, Z, cmap='RdBu_r', vmin=-np.max(Z))
+fig.colorbar(pcm, ax=ax[1], extend='both')
+```
+
+![色彩映射规范化示例4](https://matplotlib.org/_images/sphx_glr_colormap_normalizations_004.png)
+
+常规颜色：对于这一种颜色，您提供了颜色的边界，并且Norm将第一种颜色放在第一对之间，第二种颜色放在第二对之间，依此类推。
+
+```python
+fig, ax = plt.subplots(3, 1, figsize=(8, 8))
+ax = ax.flatten()
+# even bounds gives a contour-like effect
+bounds = np.linspace(-1, 1, 10)
+norm = colors.BoundaryNorm(boundaries=bounds, ncolors=256)
+pcm = ax[0].pcolormesh(X, Y, Z,
+                       norm=norm,
+                       cmap='RdBu_r')
+fig.colorbar(pcm, ax=ax[0], extend='both', orientation='vertical')
+
+# uneven bounds changes the colormapping:
+bounds = np.array([-0.25, -0.125, 0, 0.5, 1])
+norm = colors.BoundaryNorm(boundaries=bounds, ncolors=256)
+pcm = ax[1].pcolormesh(X, Y, Z, norm=norm, cmap='RdBu_r')
+fig.colorbar(pcm, ax=ax[1], extend='both', orientation='vertical')
+
+pcm = ax[2].pcolormesh(X, Y, Z, cmap='RdBu_r', vmin=-np.max(Z1))
+fig.colorbar(pcm, ax=ax[2], extend='both', orientation='vertical')
+
+plt.show()
+```
+
+![色彩映射规范化示例5](https://matplotlib.org/_images/sphx_glr_colormap_normalizations_005.png)
+
+## 下载这个示例
+            
+- [下载python源码: colormap_normalizations.py](https://matplotlib.org/_downloads/colormap_normalizations.py)
+- [下载Jupyter notebook: colormap_normalizations.ipynb](https://matplotlib.org/_downloads/colormap_normalizations.ipynb)

Python/matplotlab/gallery/userdemo/colormap_normalizations_bounds.md

@@ -0,0 +1,49 @@
+# 色彩映射规范化边界
+
+演示使用规范以非线性方式将颜色映射映射到数据上。
+
+![色彩映射规范化边界示例](https://matplotlib.org/_images/sphx_glr_colormap_normalizations_bounds_001.png)
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.colors as colors
+
+N = 100
+X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)]
+Z1 = np.exp(-X**2 - Y**2)
+Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
+Z = (Z1 - Z2) * 2
+
+'''
+BoundaryNorm: For this one you provide the boundaries for your colors,
+and the Norm puts the first color in between the first pair, the
+second color between the second pair, etc.
+'''
+
+fig, ax = plt.subplots(3, 1, figsize=(8, 8))
+ax = ax.flatten()
+# even bounds gives a contour-like effect
+bounds = np.linspace(-1, 1, 10)
+norm = colors.BoundaryNorm(boundaries=bounds, ncolors=256)
+pcm = ax[0].pcolormesh(X, Y, Z,
+                       norm=norm,
+                       cmap='RdBu_r')
+fig.colorbar(pcm, ax=ax[0], extend='both', orientation='vertical')
+
+# uneven bounds changes the colormapping:
+bounds = np.array([-0.25, -0.125, 0, 0.5, 1])
+norm = colors.BoundaryNorm(boundaries=bounds, ncolors=256)
+pcm = ax[1].pcolormesh(X, Y, Z, norm=norm, cmap='RdBu_r')
+fig.colorbar(pcm, ax=ax[1], extend='both', orientation='vertical')
+
+pcm = ax[2].pcolormesh(X, Y, Z, cmap='RdBu_r', vmin=-np.max(Z))
+fig.colorbar(pcm, ax=ax[2], extend='both', orientation='vertical')
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: colormap_normalizations_bounds.py](https://matplotlib.org/_downloads/colormap_normalizations_bounds.py)
+- [下载Jupyter notebook: colormap_normalizations_bounds.ipynb](https://matplotlib.org/_downloads/colormap_normalizations_bounds.ipynb)

Python/matplotlab/gallery/userdemo/colormap_normalizations_custom.md

@@ -0,0 +1,55 @@
+# 色彩映射标准化自定义
+
+演示使用规范以非线性方式将颜色映射映射到数据上。
+
+![色彩映射标准化自定义示例](https://matplotlib.org/_images/sphx_glr_colormap_normalizations_custom_001.png)
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.colors as colors
+
+N = 100
+'''
+Custom Norm: An example with a customized normalization.  This one
+uses the example above, and normalizes the negative data differently
+from the positive.
+'''
+X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)]
+Z1 = np.exp(-X**2 - Y**2)
+Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
+Z = (Z1 - Z2) * 2
+
+
+# Example of making your own norm.  Also see matplotlib.colors.
+# From Joe Kington: This one gives two different linear ramps:
+class MidpointNormalize(colors.Normalize):
+    def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):
+        self.midpoint = midpoint
+        colors.Normalize.__init__(self, vmin, vmax, clip)
+
+    def __call__(self, value, clip=None):
+        # I'm ignoring masked values and all kinds of edge cases to make a
+        # simple example...
+        x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]
+        return np.ma.masked_array(np.interp(value, x, y))
+
+
+#####
+fig, ax = plt.subplots(2, 1)
+
+pcm = ax[0].pcolormesh(X, Y, Z,
+                       norm=MidpointNormalize(midpoint=0.),
+                       cmap='RdBu_r')
+fig.colorbar(pcm, ax=ax[0], extend='both')
+
+pcm = ax[1].pcolormesh(X, Y, Z, cmap='RdBu_r', vmin=-np.max(Z))
+fig.colorbar(pcm, ax=ax[1], extend='both')
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: colormap_normalizations_custom.py](https://matplotlib.org/_downloads/colormap_normalizations_custom.py)
+- [下载Jupyter notebook: colormap_normalizations_custom.ipynb](https://matplotlib.org/_downloads/colormap_normalizations_custom.ipynb)

Python/matplotlab/gallery/userdemo/colormap_normalizations_lognorm.md

@@ -0,0 +1,40 @@
+# 颜色映射规格化
+
+演示使用规范以非线性方式将颜色映射映射到数据上。
+
+![颜色映射规格化示例](https://matplotlib.org/_images/sphx_glr_colormap_normalizations_lognorm_001.png)
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.colors as colors
+
+'''
+Lognorm: Instead of pcolor log10(Z1) you can have colorbars that have
+the exponential labels using a norm.
+'''
+N = 100
+X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)]
+
+# A low hump with a spike coming out of the top right.  Needs to have
+# z/colour axis on a log scale so we see both hump and spike.  linear
+# scale only shows the spike.
+Z = np.exp(-X**2 - Y**2)
+
+fig, ax = plt.subplots(2, 1)
+
+pcm = ax[0].pcolor(X, Y, Z,
+                   norm=colors.LogNorm(vmin=Z.min(), vmax=Z.max()),
+                   cmap='PuBu_r')
+fig.colorbar(pcm, ax=ax[0], extend='max')
+
+pcm = ax[1].pcolor(X, Y, Z, cmap='PuBu_r')
+fig.colorbar(pcm, ax=ax[1], extend='max')
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: colormap_normalizations_lognorm.py](https://matplotlib.org/_downloads/colormap_normalizations_lognorm.py)
+- [下载Jupyter notebook: colormap_normalizations_lognorm.ipynb](https://matplotlib.org/_downloads/colormap_normalizations_lognorm.ipynb)

Python/matplotlab/gallery/userdemo/colormap_normalizations_power.md

@@ -0,0 +1,37 @@
+# 颜色映射规格化功能
+
+演示使用规范以非线性方式将颜色映射映射到数据上。
+
+![颜色映射规格化功能示例](https://matplotlib.org/_images/sphx_glr_colormap_normalizations_power_001.png)
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.colors as colors
+
+N = 100
+X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)]
+
+'''
+PowerNorm: Here a power-law trend in X partially obscures a rectified
+sine wave in Y. We can remove the power law using a PowerNorm.
+'''
+X, Y = np.mgrid[0:3:complex(0, N), 0:2:complex(0, N)]
+Z1 = (1 + np.sin(Y * 10.)) * X**(2.)
+
+fig, ax = plt.subplots(2, 1)
+
+pcm = ax[0].pcolormesh(X, Y, Z1, norm=colors.PowerNorm(gamma=1./2.),
+                       cmap='PuBu_r')
+fig.colorbar(pcm, ax=ax[0], extend='max')
+
+pcm = ax[1].pcolormesh(X, Y, Z1, cmap='PuBu_r')
+fig.colorbar(pcm, ax=ax[1], extend='max')
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: colormap_normalizations_power.py](https://matplotlib.org/_downloads/colormap_normalizations_power.py)
+- [下载Jupyter notebook: colormap_normalizations_power.ipynb](https://matplotlib.org/_downloads/colormap_normalizations_power.ipynb)

Python/matplotlab/gallery/userdemo/colormap_normalizations_symlognorm.md

@@ -0,0 +1,44 @@
+# 色彩映射规范化Symlognorm
+
+演示使用规范以非线性方式将颜色映射映射到数据上。
+
+![色彩映射规范化Symlognorm示例](https://matplotlib.org/_images/sphx_glr_colormap_normalizations_symlognorm_001.png)
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.colors as colors
+
+"""
+SymLogNorm: two humps, one negative and one positive, The positive
+with 5-times the amplitude. Linearly, you cannot see detail in the
+negative hump.  Here we logarithmically scale the positive and
+negative data separately.
+
+Note that colorbar labels do not come out looking very good.
+"""
+
+N = 100
+X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)]
+Z1 = np.exp(-X**2 - Y**2)
+Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
+Z = (Z1 - Z2) * 2
+
+fig, ax = plt.subplots(2, 1)
+
+pcm = ax[0].pcolormesh(X, Y, Z,
+                       norm=colors.SymLogNorm(linthresh=0.03, linscale=0.03,
+                                              vmin=-1.0, vmax=1.0),
+                       cmap='RdBu_r')
+fig.colorbar(pcm, ax=ax[0], extend='both')
+
+pcm = ax[1].pcolormesh(X, Y, Z, cmap='RdBu_r', vmin=-np.max(Z))
+fig.colorbar(pcm, ax=ax[1], extend='both')
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: colormap_normalizations_symlognorm.py](https://matplotlib.org/_downloads/colormap_normalizations_symlognorm.py)
+- [下载Jupyter notebook: colormap_normalizations_symlognorm.ipynb](https://matplotlib.org/_downloads/colormap_normalizations_symlognorm.ipynb)

Python/matplotlab/gallery/userdemo/connect_simple01.md

@@ -0,0 +1,40 @@
+# 连接简单例子01
+
+![连接简单例子01示例](https://matplotlib.org/_images/sphx_glr_connect_simple01_001.png)
+
+```python
+from matplotlib.patches import ConnectionPatch
+import matplotlib.pyplot as plt
+
+fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(6, 3))
+
+xyA = (0.2, 0.2)
+xyB = (0.8, 0.8)
+coordsA = "data"
+coordsB = "data"
+con = ConnectionPatch(xyA, xyB, coordsA, coordsB,
+                      arrowstyle="-|>", shrinkA=5, shrinkB=5,
+                      mutation_scale=20, fc="w")
+ax1.plot([xyA[0], xyB[0]], [xyA[1], xyB[1]], "o")
+ax1.add_artist(con)
+
+xy = (0.3, 0.2)
+coordsA = "data"
+coordsB = "data"
+con = ConnectionPatch(xyA=xy, xyB=xy, coordsA=coordsA, coordsB=coordsB,
+                      axesA=ax2, axesB=ax1,
+                      arrowstyle="->", shrinkB=5)
+ax2.add_artist(con)
+
+ax1.set_xlim(0, 1)
+ax1.set_ylim(0, 1)
+ax2.set_xlim(0, .5)
+ax2.set_ylim(0, .5)
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: connect_simple01.py](https://matplotlib.org/_downloads/connect_simple01.py)
+- [下载Jupyter notebook: connect_simple01.ipynb](https://matplotlib.org/_downloads/connect_simple01.ipynb)

Python/matplotlab/gallery/userdemo/connectionstyle_demo.md

@@ -0,0 +1,60 @@
+# 连接样式演示
+
+![连接样式演示](https://matplotlib.org/_images/sphx_glr_connectionstyle_demo_001.png)
+
+```python
+import matplotlib.pyplot as plt
+
+
+fig, axs = plt.subplots(3, 5, figsize=(8, 4.8))
+x1, y1 = 0.3, 0.3
+x2, y2 = 0.7, 0.7
+
+
+def demo_con_style(ax, connectionstyle, label=None):
+    x1, y1 = 0.3, 0.2
+    x2, y2 = 0.8, 0.6
+
+    ax.plot([x1, x2], [y1, y2], ".")
+    ax.annotate("",
+                xy=(x1, y1), xycoords='data',
+                xytext=(x2, y2), textcoords='data',
+                arrowprops=dict(arrowstyle="->",
+                                color="0.5",
+                                shrinkA=5, shrinkB=5,
+                                patchA=None,
+                                patchB=None,
+                                connectionstyle=connectionstyle,
+                                ),
+                )
+
+    ax.text(.05, .95, connectionstyle.replace(",", ",\n"),
+            transform=ax.transAxes, ha="left", va="top")
+
+
+demo_con_style(axs[0, 0], "angle3,angleA=90,angleB=0")
+demo_con_style(axs[1, 0], "angle3,angleA=0,angleB=90")
+demo_con_style(axs[0, 1], "arc3,rad=0.")
+demo_con_style(axs[1, 1], "arc3,rad=0.3")
+demo_con_style(axs[2, 1], "arc3,rad=-0.3")
+demo_con_style(axs[0, 2], "angle,angleA=-90,angleB=180,rad=0")
+demo_con_style(axs[1, 2], "angle,angleA=-90,angleB=180,rad=5")
+demo_con_style(axs[2, 2], "angle,angleA=-90,angleB=10,rad=5")
+demo_con_style(axs[0, 3], "arc,angleA=-90,angleB=0,armA=30,armB=30,rad=0")
+demo_con_style(axs[1, 3], "arc,angleA=-90,angleB=0,armA=30,armB=30,rad=5")
+demo_con_style(axs[2, 3], "arc,angleA=-90,angleB=0,armA=0,armB=40,rad=0")
+demo_con_style(axs[0, 4], "bar,fraction=0.3")
+demo_con_style(axs[1, 4], "bar,fraction=-0.3")
+demo_con_style(axs[2, 4], "bar,angle=180,fraction=-0.2")
+
+for ax in axs.flat:
+    ax.set(xlim=(0, 1), ylim=(0, 1), xticks=[], yticks=[], aspect=1)
+fig.tight_layout(pad=0)
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: connectionstyle_demo.py](https://matplotlib.org/_downloads/connectionstyle_demo.py)
+- [下载Jupyter notebook: connectionstyle_demo.ipynb](https://matplotlib.org/_downloads/connectionstyle_demo.ipynb)

Python/matplotlab/gallery/userdemo/custom_boxstyle01.md

@@ -0,0 +1,60 @@
+# 自定义Boxstyle01
+
+![自定义Boxstyle01示例](https://matplotlib.org/_images/sphx_glr_custom_boxstyle01_001.png)
+
+```python
+from matplotlib.path import Path
+
+
+def custom_box_style(x0, y0, width, height, mutation_size, mutation_aspect=1):
+    """
+    Given the location and size of the box, return the path of
+    the box around it.
+
+     - *x0*, *y0*, *width*, *height* : location and size of the box
+     - *mutation_size* : a reference scale for the mutation.
+     - *aspect_ratio* : aspect-ration for the mutation.
+    """
+
+    # note that we are ignoring mutation_aspect. This is okay in general.
+
+    # padding
+    mypad = 0.3
+    pad = mutation_size * mypad
+
+    # width and height with padding added.
+    width = width + 2 * pad
+    height = height + 2 * pad
+
+    # boundary of the padded box
+    x0, y0 = x0 - pad, y0 - pad
+    x1, y1 = x0 + width, y0 + height
+
+    cp = [(x0, y0),
+          (x1, y0), (x1, y1), (x0, y1),
+          (x0-pad, (y0+y1)/2.), (x0, y0),
+          (x0, y0)]
+
+    com = [Path.MOVETO,
+           Path.LINETO, Path.LINETO, Path.LINETO,
+           Path.LINETO, Path.LINETO,
+           Path.CLOSEPOLY]
+
+    path = Path(cp, com)
+
+    return path
+
+
+import matplotlib.pyplot as plt
+
+fig, ax = plt.subplots(figsize=(3, 3))
+ax.text(0.5, 0.5, "Test", size=30, va="center", ha="center",
+        bbox=dict(boxstyle=custom_box_style, alpha=0.2))
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: custom_boxstyle01.py](https://matplotlib.org/_downloads/custom_boxstyle01.py)
+- [下载Jupyter notebook: custom_boxstyle01.ipynb](https://matplotlib.org/_downloads/custom_boxstyle01.ipynb)

Python/matplotlab/gallery/userdemo/custom_boxstyle02.md

@@ -0,0 +1,85 @@
+# 自定义Boxstyle02
+
+![自定义Boxstyle02示例](https://matplotlib.org/_images/sphx_glr_custom_boxstyle02_001.png)
+
+```python
+from matplotlib.path import Path
+from matplotlib.patches import BoxStyle
+import matplotlib.pyplot as plt
+
+
+# we may derive from matplotlib.patches.BoxStyle._Base class.
+# You need to override transmute method in this case.
+class MyStyle(BoxStyle._Base):
+    """
+    A simple box.
+    """
+
+    def __init__(self, pad=0.3):
+        """
+        The arguments need to be floating numbers and need to have
+        default values.
+
+         *pad*
+            amount of padding
+        """
+
+        self.pad = pad
+        super().__init__()
+
+    def transmute(self, x0, y0, width, height, mutation_size):
+        """
+        Given the location and size of the box, return the path of
+        the box around it.
+
+         - *x0*, *y0*, *width*, *height* : location and size of the box
+         - *mutation_size* : a reference scale for the mutation.
+
+        Often, the *mutation_size* is the font size of the text.
+        You don't need to worry about the rotation as it is
+        automatically taken care of.
+        """
+
+        # padding
+        pad = mutation_size * self.pad
+
+        # width and height with padding added.
+        width, height = width + 2.*pad, \
+                        height + 2.*pad,
+
+        # boundary of the padded box
+        x0, y0 = x0-pad, y0-pad,
+        x1, y1 = x0+width, y0 + height
+
+        cp = [(x0, y0),
+              (x1, y0), (x1, y1), (x0, y1),
+              (x0-pad, (y0+y1)/2.), (x0, y0),
+              (x0, y0)]
+
+        com = [Path.MOVETO,
+               Path.LINETO, Path.LINETO, Path.LINETO,
+               Path.LINETO, Path.LINETO,
+               Path.CLOSEPOLY]
+
+        path = Path(cp, com)
+
+        return path
+
+
+# register the custom style
+BoxStyle._style_list["angled"] = MyStyle
+
+fig, ax = plt.subplots(figsize=(3, 3))
+ax.text(0.5, 0.5, "Test", size=30, va="center", ha="center", rotation=30,
+        bbox=dict(boxstyle="angled,pad=0.5", alpha=0.2))
+
+del BoxStyle._style_list["angled"]
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: custom_boxstyle02.py](https://matplotlib.org/_downloads/custom_boxstyle02.py)
+- [下载Jupyter notebook: custom_boxstyle02.ipynb](https://matplotlib.org/_downloads/custom_boxstyle02.ipynb)
+

Python/matplotlab/gallery/userdemo/demo_gridspec01.md

@@ -0,0 +1,31 @@
+# Gridspec演示01
+
+![Gridspec演示01](https://matplotlib.org/_images/sphx_glr_demo_gridspec01_000.png)
+
+```python
+import matplotlib.pyplot as plt
+
+
+def make_ticklabels_invisible(fig):
+    for i, ax in enumerate(fig.axes):
+        ax.text(0.5, 0.5, "ax%d" % (i+1), va="center", ha="center")
+        ax.tick_params(labelbottom=False, labelleft=False)
+
+
+fig = plt.figure(0)
+ax1 = plt.subplot2grid((3, 3), (0, 0), colspan=3)
+ax2 = plt.subplot2grid((3, 3), (1, 0), colspan=2)
+ax3 = plt.subplot2grid((3, 3), (1, 2), rowspan=2)
+ax4 = plt.subplot2grid((3, 3), (2, 0))
+ax5 = plt.subplot2grid((3, 3), (2, 1))
+
+fig.suptitle("subplot2grid")
+make_ticklabels_invisible(fig)
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: demo_gridspec01.py](https://matplotlib.org/_downloads/demo_gridspec01.py)
+- [下载Jupyter notebook: demo_gridspec01.ipynb](https://matplotlib.org/_downloads/demo_gridspec01.ipynb)

Python/matplotlab/gallery/userdemo/demo_gridspec03.md

@@ -0,0 +1,42 @@
+# Gridspec演示03
+
+![Gridspec演示03](https://matplotlib.org/_images/sphx_glr_demo_gridspec03_001.png)
+
+```python
+import matplotlib.pyplot as plt
+from matplotlib.gridspec import GridSpec
+
+
+def make_ticklabels_invisible(fig):
+    for i, ax in enumerate(fig.axes):
+        ax.text(0.5, 0.5, "ax%d" % (i+1), va="center", ha="center")
+        ax.tick_params(labelbottom=False, labelleft=False)
+
+
+# demo 3 : gridspec with subplotpars set.
+
+fig = plt.figure()
+
+fig.suptitle("GridSpec w/ different subplotpars")
+
+gs1 = GridSpec(3, 3)
+gs1.update(left=0.05, right=0.48, wspace=0.05)
+ax1 = plt.subplot(gs1[:-1, :])
+ax2 = plt.subplot(gs1[-1, :-1])
+ax3 = plt.subplot(gs1[-1, -1])
+
+gs2 = GridSpec(3, 3)
+gs2.update(left=0.55, right=0.98, hspace=0.05)
+ax4 = plt.subplot(gs2[:, :-1])
+ax5 = plt.subplot(gs2[:-1, -1])
+ax6 = plt.subplot(gs2[-1, -1])
+
+make_ticklabels_invisible(fig)
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: demo_gridspec03.py](https://matplotlib.org/_downloads/demo_gridspec03.py)
+- [下载Jupyter notebook: demo_gridspec03.ipynb](https://matplotlib.org/_downloads/demo_gridspec03.ipynb)

Python/matplotlab/gallery/userdemo/demo_gridspec05.md

@@ -0,0 +1,33 @@
+# Gridspec演示05
+
+![Gridspec演示05](https://matplotlib.org/_images/sphx_glr_demo_gridspec05_001.png)
+
+```python
+import matplotlib.pyplot as plt
+import matplotlib.gridspec as gridspec
+
+
+def make_ticklabels_invisible(fig):
+    for i, ax in enumerate(fig.axes):
+        ax.text(0.5, 0.5, "ax%d" % (i+1), va="center", ha="center")
+        ax.tick_params(labelbottom=False, labelleft=False)
+
+
+f = plt.figure()
+
+gs = gridspec.GridSpec(2, 2,
+                       width_ratios=[1, 2], height_ratios=[4, 1])
+
+ax1 = plt.subplot(gs[0])
+ax2 = plt.subplot(gs[1])
+ax3 = plt.subplot(gs[2])
+ax4 = plt.subplot(gs[3])
+
+make_ticklabels_invisible(f)
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: demo_gridspec05.py](https://matplotlib.org/_downloads/demo_gridspec05.py)
+- [下载Jupyter notebook: demo_gridspec05.ipynb](https://matplotlib.org/_downloads/demo_gridspec05.ipynb)

Python/matplotlab/gallery/userdemo/demo_gridspec06.md

@@ -0,0 +1,57 @@
+# Gridspec演示06
+
+![Gridspec演示06](https://matplotlib.org/_images/sphx_glr_demo_gridspec06_001.png)
+
+```python
+import matplotlib.pyplot as plt
+import matplotlib.gridspec as gridspec
+import numpy as np
+from itertools import product
+
+
+def squiggle_xy(a, b, c, d):
+    i = np.arange(0.0, 2*np.pi, 0.05)
+    return np.sin(i*a)*np.cos(i*b), np.sin(i*c)*np.cos(i*d)
+
+
+fig = plt.figure(figsize=(8, 8))
+
+# gridspec inside gridspec
+outer_grid = gridspec.GridSpec(4, 4, wspace=0.0, hspace=0.0)
+
+for i in range(16):
+    inner_grid = gridspec.GridSpecFromSubplotSpec(3, 3,
+            subplot_spec=outer_grid[i], wspace=0.0, hspace=0.0)
+    a = i // 4 + 1
+    b = i % 4 + 1
+    for j, (c, d) in enumerate(product(range(1, 4), repeat=2)):
+        ax = plt.Subplot(fig, inner_grid[j])
+        ax.plot(*squiggle_xy(a, b, c, d))
+        ax.set_xticks([])
+        ax.set_yticks([])
+        fig.add_subplot(ax)
+
+all_axes = fig.get_axes()
+
+#show only the outside spines
+for ax in all_axes:
+    for sp in ax.spines.values():
+        sp.set_visible(False)
+    if ax.is_first_row():
+        ax.spines['top'].set_visible(True)
+    if ax.is_last_row():
+        ax.spines['bottom'].set_visible(True)
+    if ax.is_first_col():
+        ax.spines['left'].set_visible(True)
+    if ax.is_last_col():
+        ax.spines['right'].set_visible(True)
+
+plt.show()
+```
+
+Total running time of the script: ( 0 minutes 2.041 seconds)
+
+## 下载这个示例
+            
+- [下载python源码: demo_gridspec06.py](https://matplotlib.org/_downloads/demo_gridspec06.py)
+- [下载Jupyter notebook: demo_gridspec06.ipynb](https://matplotlib.org/_downloads/demo_gridspec06.ipynb)

Python/matplotlab/gallery/userdemo/pgf_fonts.md

@@ -0,0 +1,29 @@
+# Pgf字体
+
+![Pgf字体](https://matplotlib.org/_images/sphx_glr_pgf_fonts_001.png)
+
+```python
+import matplotlib.pyplot as plt
+plt.rcParams.update({
+    "font.family": "serif",
+    "font.serif": [],                    # use latex default serif font
+    "font.sans-serif": ["DejaVu Sans"],  # use a specific sans-serif font
+})
+
+plt.figure(figsize=(4.5, 2.5))
+plt.plot(range(5))
+plt.text(0.5, 3., "serif")
+plt.text(0.5, 2., "monospace", family="monospace")
+plt.text(2.5, 2., "sans-serif", family="sans-serif")
+plt.text(2.5, 1., "comic sans", family="Comic Sans MS")
+plt.xlabel("µ is not $\\mu$")
+plt.tight_layout(.5)
+
+plt.savefig("pgf_fonts.pdf")
+plt.savefig("pgf_fonts.png")
+```
+
+## 下载这个示例
+            
+- [下载python源码: pgf_fonts.py](https://matplotlib.org/_downloads/pgf_fonts.py)
+- [下载Jupyter notebook: pgf_fonts.ipynb](https://matplotlib.org/_downloads/pgf_fonts.ipynb)

Python/matplotlab/gallery/userdemo/pgf_preamble_sgskip.md

@@ -0,0 +1,34 @@
+# Pgf序言
+
+```python
+import matplotlib as mpl
+mpl.use("pgf")
+import matplotlib.pyplot as plt
+plt.rcParams.update({
+    "font.family": "serif",  # use serif/main font for text elements
+    "text.usetex": True,     # use inline math for ticks
+    "pgf.rcfonts": False,    # don't setup fonts from rc parameters
+    "pgf.preamble": [
+         "\\usepackage{units}",          # load additional packages
+         "\\usepackage{metalogo}",
+         "\\usepackage{unicode-math}",   # unicode math setup
+         r"\setmathfont{xits-math.otf}",
+         r"\setmainfont{DejaVu Serif}",  # serif font via preamble
+         ]
+})
+
+plt.figure(figsize=(4.5, 2.5))
+plt.plot(range(5))
+plt.xlabel("unicode text: я, ψ, €, ü, \\unitfrac[10]{°}{µm}")
+plt.ylabel("\\XeLaTeX")
+plt.legend(["unicode math: $λ=∑_i^∞ μ_i^2$"])
+plt.tight_layout(.5)
+
+plt.savefig("pgf_preamble.pdf")
+plt.savefig("pgf_preamble.png")
+```
+
+## 下载这个示例
+            
+- [下载python源码: pgf_preamble_sgskip.py](https://matplotlib.org/_downloads/pgf_preamble_sgskip.py)
+- [下载Jupyter notebook: pgf_preamble_sgskip.ipynb](https://matplotlib.org/_downloads/pgf_preamble_sgskip.ipynb)

Python/matplotlab/gallery/userdemo/pgf_texsystem.md

@@ -0,0 +1,31 @@
+# Pgf文本系统
+
+![Pgf文本系统示例](https://matplotlib.org/_images/sphx_glr_pgf_texsystem_001.png)
+
+```python
+import matplotlib.pyplot as plt
+plt.rcParams.update({
+    "pgf.texsystem": "pdflatex",
+    "pgf.preamble": [
+         r"\usepackage[utf8x]{inputenc}",
+         r"\usepackage[T1]{fontenc}",
+         r"\usepackage{cmbright}",
+         ]
+})
+
+plt.figure(figsize=(4.5, 2.5))
+plt.plot(range(5))
+plt.text(0.5, 3., "serif", family="serif")
+plt.text(0.5, 2., "monospace", family="monospace")
+plt.text(2.5, 2., "sans-serif", family="sans-serif")
+plt.xlabel(r"µ is not $\mu$")
+plt.tight_layout(.5)
+
+plt.savefig("pgf_texsystem.pdf")
+plt.savefig("pgf_texsystem.png")
+```
+
+## 下载这个示例
+            
+- [下载python源码: pgf_texsystem.py](https://matplotlib.org/_downloads/pgf_texsystem.py)
+- [下载Jupyter notebook: pgf_texsystem.ipynb](https://matplotlib.org/_downloads/pgf_texsystem.ipynb)

Python/matplotlab/gallery/userdemo/simple_annotate01.md

@@ -0,0 +1,93 @@
+# 简单的Annotate01
+
+![简单的Annotate01示例](https://matplotlib.org/_images/sphx_glr_simple_annotate01_001.png)
+
+```python
+import matplotlib.pyplot as plt
+import matplotlib.patches as mpatches
+
+
+fig, axs = plt.subplots(2, 4)
+x1, y1 = 0.3, 0.3
+x2, y2 = 0.7, 0.7
+
+ax = axs.flat[0]
+ax.plot([x1, x2], [y1, y2], "o")
+ax.annotate("",
+            xy=(x1, y1), xycoords='data',
+            xytext=(x2, y2), textcoords='data',
+            arrowprops=dict(arrowstyle="->"))
+ax.text(.05, .95, "A $->$ B", transform=ax.transAxes, ha="left", va="top")
+
+ax = axs.flat[2]
+ax.plot([x1, x2], [y1, y2], "o")
+ax.annotate("",
+            xy=(x1, y1), xycoords='data',
+            xytext=(x2, y2), textcoords='data',
+            arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=0.3",
+                            shrinkB=5)
+            )
+ax.text(.05, .95, "shrinkB=5", transform=ax.transAxes, ha="left", va="top")
+
+ax = axs.flat[3]
+ax.plot([x1, x2], [y1, y2], "o")
+ax.annotate("",
+            xy=(x1, y1), xycoords='data',
+            xytext=(x2, y2), textcoords='data',
+            arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=0.3"))
+ax.text(.05, .95, "connectionstyle=arc3", transform=ax.transAxes, ha="left", va="top")
+
+ax = axs.flat[4]
+ax.plot([x1, x2], [y1, y2], "o")
+el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.5)
+ax.add_artist(el)
+ax.annotate("",
+            xy=(x1, y1), xycoords='data',
+            xytext=(x2, y2), textcoords='data',
+            arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=0.2")
+            )
+
+ax = axs.flat[5]
+ax.plot([x1, x2], [y1, y2], "o")
+el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.5)
+ax.add_artist(el)
+ax.annotate("",
+            xy=(x1, y1), xycoords='data',
+            xytext=(x2, y2), textcoords='data',
+            arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=0.2",
+                            patchB=el)
+            )
+ax.text(.05, .95, "patchB", transform=ax.transAxes, ha="left", va="top")
+
+ax = axs.flat[6]
+ax.plot([x1], [y1], "o")
+ax.annotate("Test",
+            xy=(x1, y1), xycoords='data',
+            xytext=(x2, y2), textcoords='data',
+            ha="center", va="center",
+            bbox=dict(boxstyle="round", fc="w"),
+            arrowprops=dict(arrowstyle="->")
+            )
+ax.text(.05, .95, "annotate", transform=ax.transAxes, ha="left", va="top")
+
+ax = axs.flat[7]
+ax.plot([x1], [y1], "o")
+ax.annotate("Test",
+            xy=(x1, y1), xycoords='data',
+            xytext=(x2, y2), textcoords='data',
+            ha="center", va="center",
+            bbox=dict(boxstyle="round", fc="w", ),
+            arrowprops=dict(arrowstyle="->", relpos=(0., 0.))
+            )
+ax.text(.05, .95, "relpos=(0,0)", transform=ax.transAxes, ha="left", va="top")
+
+for ax in axs.flat:
+    ax.set(xlim=(0, 1), ylim=(0, 1), xticks=[], yticks=[], aspect=1)
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: simple_annotate01.py](https://matplotlib.org/_downloads/simple_annotate01.py)
+- [下载Jupyter notebook: simple_annotate01.ipynb](https://matplotlib.org/_downloads/simple_annotate01.ipynb)

Python/matplotlab/gallery/userdemo/simple_legend01.md

@@ -0,0 +1,29 @@
+# 简单的Legend01
+
+![简单的Legend01示例](https://matplotlib.org/_images/sphx_glr_simple_legend01_001.png)
+
+```python
+import matplotlib.pyplot as plt
+
+
+plt.subplot(211)
+plt.plot([1, 2, 3], label="test1")
+plt.plot([3, 2, 1], label="test2")
+# Place a legend above this subplot, expanding itself to
+# fully use the given bounding box.
+plt.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc='lower left',
+           ncol=2, mode="expand", borderaxespad=0.)
+
+plt.subplot(223)
+plt.plot([1, 2, 3], label="test1")
+plt.plot([3, 2, 1], label="test2")
+# Place a legend to the right of this smaller subplot.
+plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0.)
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: simple_legend01.py](https://matplotlib.org/_downloads/simple_legend01.py)
+- [下载Jupyter notebook: simple_legend01.ipynb](https://matplotlib.org/_downloads/simple_legend01.ipynb)

Python/matplotlab/gallery/userdemo/simple_legend02.md

@@ -0,0 +1,28 @@
+# 简单的Legend02
+
+![简单的Legend02示例](https://matplotlib.org/_images/sphx_glr_simple_legend02_001.png)
+
+```python
+import matplotlib.pyplot as plt
+
+fig, ax = plt.subplots()
+
+line1, = ax.plot([1, 2, 3], label="Line 1", linestyle='--')
+line2, = ax.plot([3, 2, 1], label="Line 2", linewidth=4)
+
+# Create a legend for the first line.
+first_legend = ax.legend(handles=[line1], loc='upper right')
+
+# Add the legend manually to the current Axes.
+ax.add_artist(first_legend)
+
+# Create another legend for the second line.
+ax.legend(handles=[line2], loc='lower right')
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: simple_legend02.py](https://matplotlib.org/_downloads/simple_legend02.py)
+- [下载Jupyter notebook: simple_legend02.ipynb](https://matplotlib.org/_downloads/simple_legend02.ipynb)