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        "\n# 2D Mixed-Histogram\n\nData on a regular two-dimensional grid which is the combination\nof an image and a histogram.\n\nThe x-axis defines the bin edges along the second dimension.\nThe y-axis defines the grid coordinates along the first dimension.\n\n.. code::\n\n  @NX_class = \"NXroot\"\n  @default = \"scan1\"\n  scan1:\n    @NX_class = \"NXentry\"\n    @default = \"data\"\n    data:\n      @NX_class = \"NXdata\"\n      @axes = [\"y\", \"x\"]\n      @signal = \"z\"\n      x: NX_FLOAT64[7]\n      y: NX_FLOAT64[16]\n      z: NX_FLOAT64[16,6]\n\nExplanation:\n\n1. ``@axes`` has two values which corresponds to the signal rank of two.\n\n2. ``z`` is the default signal to be plotted versus ``x`` and ``y``.\n\n3. ``z`` has 16 rows and 6 columns.\n\n4. ``x`` has one more value than the second dimension of ``z`` since it contains the bin edges.\n"
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    {
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      "source": [
        "# Data\nimport numpy as np\n\nx = [-3.0, -2.5, -1.0, 0.0, 1.0, 2.5, 3.0]\ny = np.linspace(-3, 3, 16)\n\nnx = len(x) - 1\nny = len(y)\nz = np.zeros((ny, nx))\nxx = np.linspace(-3, 3, 200)\nfor i in range(ny):\n    zi = (1 - xx / 2 + xx**5 + y[i] ** 3) * np.exp(-(xx**2) - y[i] ** 2)\n    z[i, :], _ = np.histogram(xx, bins=x, weights=zi)\n\n# Plot\nimport matplotlib.pyplot as plt  # noqa E402\n\nplt.style.use(\"_mpl-gallery-nogrid\")\n\nfig, ax = plt.subplots()\n\ny_new = np.empty_like(y, shape=(len(y) + 1,))\ny_new[0] = 2 * y[0] - y[1]\ny_new[1:-1] = (y[:-1] + y[1:]) / 2\ny_new[-1] = 2 * y[-1] - y[-2]\n\nmesh = ax.pcolormesh(x, y_new, z, linewidth=0.7)\n\nplt.show()"
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