matplotlib & pandas

Python/matplotlab/gallery/misc/demo_ribbon_box.md

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+# 演示丝带盒
+
+![演示丝带盒示例](https://matplotlib.org/_images/sphx_glr_demo_ribbon_box_001.png)
+
+```python
+import numpy as np
+
+from matplotlib import cbook, colors as mcolors
+from matplotlib.image import BboxImage
+import matplotlib.pyplot as plt
+
+
+class RibbonBox:
+
+    original_image = plt.imread(
+        cbook.get_sample_data("Minduka_Present_Blue_Pack.png"))
+    cut_location = 70
+    b_and_h = original_image[:, :, 2:3]
+    color = original_image[:, :, 2:3] - original_image[:, :, 0:1]
+    alpha = original_image[:, :, 3:4]
+    nx = original_image.shape[1]
+
+    def __init__(self, color):
+        rgb = mcolors.to_rgba(color)[:3]
+        self.im = np.dstack(
+            [self.b_and_h - self.color * (1 - np.array(rgb)), self.alpha])
+
+    def get_stretched_image(self, stretch_factor):
+        stretch_factor = max(stretch_factor, 1)
+        ny, nx, nch = self.im.shape
+        ny2 = int(ny*stretch_factor)
+        return np.vstack(
+            [self.im[:self.cut_location],
+             np.broadcast_to(
+                 self.im[self.cut_location], (ny2 - ny, nx, nch)),
+             self.im[self.cut_location:]])
+
+
+class RibbonBoxImage(BboxImage):
+    zorder = 1
+
+    def __init__(self, bbox, color, **kwargs):
+        super().__init__(bbox, **kwargs)
+        self._ribbonbox = RibbonBox(color)
+
+    def draw(self, renderer, *args, **kwargs):
+        bbox = self.get_window_extent(renderer)
+        stretch_factor = bbox.height / bbox.width
+
+        ny = int(stretch_factor*self._ribbonbox.nx)
+        if self.get_array() is None or self.get_array().shape[0] != ny:
+            arr = self._ribbonbox.get_stretched_image(stretch_factor)
+            self.set_array(arr)
+
+        super().draw(renderer, *args, **kwargs)
+
+
+if True:
+    from matplotlib.transforms import Bbox, TransformedBbox
+    from matplotlib.ticker import ScalarFormatter
+
+    # Fixing random state for reproducibility
+    np.random.seed(19680801)
+
+    fig, ax = plt.subplots()
+
+    years = np.arange(2004, 2009)
+    box_colors = [(0.8, 0.2, 0.2),
+                  (0.2, 0.8, 0.2),
+                  (0.2, 0.2, 0.8),
+                  (0.7, 0.5, 0.8),
+                  (0.3, 0.8, 0.7),
+                  ]
+    heights = np.random.random(years.shape) * 7000 + 3000
+
+    fmt = ScalarFormatter(useOffset=False)
+    ax.xaxis.set_major_formatter(fmt)
+
+    for year, h, bc in zip(years, heights, box_colors):
+        bbox0 = Bbox.from_extents(year - 0.4, 0., year + 0.4, h)
+        bbox = TransformedBbox(bbox0, ax.transData)
+        rb_patch = RibbonBoxImage(bbox, bc, interpolation="bicubic")
+
+        ax.add_artist(rb_patch)
+
+        ax.annotate(r"%d" % (int(h/100.)*100),
+                    (year, h), va="bottom", ha="center")
+
+    patch_gradient = BboxImage(ax.bbox, interpolation="bicubic", zorder=0.1)
+    gradient = np.zeros((2, 2, 4))
+    gradient[:, :, :3] = [1, 1, 0.]
+    gradient[:, :, 3] = [[0.1, 0.3], [0.3, 0.5]]  # alpha channel
+    patch_gradient.set_array(gradient)
+    ax.add_artist(patch_gradient)
+
+    ax.set_xlim(years[0] - 0.5, years[-1] + 0.5)
+    ax.set_ylim(0, 10000)
+
+    plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: demo_ribbon_box.py](https://matplotlib.org/_downloads/demo_ribbon_box.py)
+- [下载Jupyter notebook: demo_ribbon_box.ipynb](https://matplotlib.org/_downloads/demo_ribbon_box.ipynb)