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copy correct docs to top level
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‎Matplotlib.pdf‎

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‎_downloads/affine_image.ipynb‎

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},
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"outputs": [],
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"source": [
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"import numpy as np\nimport matplotlib.mlab as mlab\nimport matplotlib.pyplot as plt\nimport matplotlib.transforms as mtransforms\n\n\ndef get_image():\n delta = 0.25\n x = y = np.arange(-3.0, 3.0, delta)\n X, Y = np.meshgrid(x, y)\n Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)\n Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)\n Z = Z2 - Z1 # difference of Gaussians\n return Z\n\n\ndef do_plot(ax, Z, transform):\n im = ax.imshow(Z, interpolation='none',\n origin='lower',\n extent=[-2, 4, -3, 2], clip_on=True)\n\n trans_data = transform + ax.transData\n im.set_transform(trans_data)\n\n # display intended extent of the image\n x1, x2, y1, y2 = im.get_extent()\n ax.plot([x1, x2, x2, x1, x1], [y1, y1, y2, y2, y1], \"y--\",\n transform=trans_data)\n ax.set_xlim(-5, 5)\n ax.set_ylim(-4, 4)\n\n\n# prepare image and figure\nfig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)\nZ = get_image()\n\n# image rotation\ndo_plot(ax1, Z, mtransforms.Affine2D().rotate_deg(30))\n\n# image skew\ndo_plot(ax2, Z, mtransforms.Affine2D().skew_deg(30, 15))\n\n# scale and reflection\ndo_plot(ax3, Z, mtransforms.Affine2D().scale(-1, .5))\n\n# everything and a translation\ndo_plot(ax4, Z, mtransforms.Affine2D().\n rotate_deg(30).skew_deg(30, 15).scale(-1, .5).translate(.5, -1))\n\nplt.show()"
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"import numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib.transforms as mtransforms\n\n\ndef get_image():\n delta = 0.25\n x = y = np.arange(-3.0, 3.0, delta)\n X, Y = np.meshgrid(x, y)\n Z1 = np.exp(-X**2 - Y**2)\n Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)\n Z = (Z1 - Z2)\n return Z\n\n\ndef do_plot(ax, Z, transform):\n im = ax.imshow(Z, interpolation='none',\n origin='lower',\n extent=[-2, 4, -3, 2], clip_on=True)\n\n trans_data = transform + ax.transData\n im.set_transform(trans_data)\n\n # display intended extent of the image\n x1, x2, y1, y2 = im.get_extent()\n ax.plot([x1, x2, x2, x1, x1], [y1, y1, y2, y2, y1], \"y--\",\n transform=trans_data)\n ax.set_xlim(-5, 5)\n ax.set_ylim(-4, 4)\n\n\n# prepare image and figure\nfig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)\nZ = get_image()\n\n# image rotation\ndo_plot(ax1, Z, mtransforms.Affine2D().rotate_deg(30))\n\n# image skew\ndo_plot(ax2, Z, mtransforms.Affine2D().skew_deg(30, 15))\n\n# scale and reflection\ndo_plot(ax3, Z, mtransforms.Affine2D().scale(-1, .5))\n\n# everything and a translation\ndo_plot(ax4, Z, mtransforms.Affine2D().\n rotate_deg(30).skew_deg(30, 15).scale(-1, .5).translate(.5, -1))\n\nplt.show()"
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‎_downloads/affine_image.py‎

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"""
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import numpy as np
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import matplotlib.mlab as mlab
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import matplotlib.pyplot as plt
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import matplotlib.transforms as mtransforms
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delta = 0.25
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x = y = np.arange(-3.0, 3.0, delta)
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X, Y = np.meshgrid(x, y)
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Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
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Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
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Z = Z2 - Z1 # difference of Gaussians
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Z1 = np.exp(-X**2 - Y**2)
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Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
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Z = (Z1 - Z2)
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return Z
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‎_downloads/align_labels_demo.ipynb‎

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"%matplotlib inline"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n# Aligning Labels\n\n\nAligning xlabel and ylabel using `Figure.align_xlabels` and\n`Figure.align_ylabels`\n\n`Figure.align_labels` wraps these two functions.\n\nNote that the xlabel \"XLabel1 1\" would normally be much closer to the\nx-axis, and \"YLabel1 0\" would be much closer to the y-axis of their\nrespective axes.\n\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt\nimport numpy as np\nimport matplotlib.gridspec as gridspec\n\nfig = plt.figure(tight_layout=True)\ngs = gridspec.GridSpec(2, 2)\n\nax = fig.add_subplot(gs[0, :])\nax.plot(np.arange(0, 1e6, 1000))\nax.set_ylabel('YLabel0')\nax.set_xlabel('XLabel0')\n\nfor i in range(2):\n ax = fig.add_subplot(gs[1, i])\n ax.plot(np.arange(1., 0., -0.1) * 2000., np.arange(1., 0., -0.1))\n ax.set_ylabel('YLabel1 %d' % i)\n ax.set_xlabel('XLabel1 %d' % i)\n if i == 0:\n for tick in ax.get_xticklabels():\n tick.set_rotation(55)\nfig.align_labels() # same as fig.align_xlabels(); fig.align_ylabels()\n\nplt.show()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}

‎_downloads/align_labels_demo.py‎

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"""
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===============
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Aligning Labels
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===============
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Aligning xlabel and ylabel using `Figure.align_xlabels` and
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`Figure.align_ylabels`
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`Figure.align_labels` wraps these two functions.
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Note that the xlabel "XLabel1 1" would normally be much closer to the
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x-axis, and "YLabel1 0" would be much closer to the y-axis of their
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respective axes.
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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import matplotlib.gridspec as gridspec
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fig = plt.figure(tight_layout=True)
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gs = gridspec.GridSpec(2, 2)
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ax = fig.add_subplot(gs[0, :])
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ax.plot(np.arange(0, 1e6, 1000))
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ax.set_ylabel('YLabel0')
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ax.set_xlabel('XLabel0')
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for i in range(2):
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ax = fig.add_subplot(gs[1, i])
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ax.plot(np.arange(1., 0., -0.1) * 2000., np.arange(1., 0., -0.1))
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ax.set_ylabel('YLabel1 %d' % i)
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ax.set_xlabel('XLabel1 %d' % i)
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if i == 0:
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for tick in ax.get_xticklabels():
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tick.set_rotation(55)
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fig.align_labels() # same as fig.align_xlabels(); fig.align_ylabels()
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plt.show()

‎_downloads/align_ylabels.ipynb‎

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},
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"outputs": [],
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"source": [
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"import numpy as np\nimport matplotlib.pyplot as plt\n\nbox = dict(facecolor='yellow', pad=5, alpha=0.2)\n\nfig = plt.figure()\nfig.subplots_adjust(left=0.2, wspace=0.6)\n\n# Fixing random state for reproducibility\nnp.random.seed(19680801)\n\nax1 = fig.add_subplot(221)\nax1.plot(2000*np.random.rand(10))\nax1.set_title('ylabels not aligned')\nax1.set_ylabel('misaligned 1', bbox=box)\nax1.set_ylim(0, 2000)\nax3 = fig.add_subplot(223)\nax3.set_ylabel('misaligned 2',bbox=box)\nax3.plot(np.random.rand(10))\n\n\nlabelx = -0.3 # axes coords\n\nax2 = fig.add_subplot(222)\nax2.set_title('ylabels aligned')\nax2.plot(2000*np.random.rand(10))\nax2.set_ylabel('aligned 1', bbox=box)\nax2.yaxis.set_label_coords(labelx, 0.5)\nax2.set_ylim(0, 2000)\n\nax4 = fig.add_subplot(224)\nax4.plot(np.random.rand(10))\nax4.set_ylabel('aligned 2', bbox=box)\nax4.yaxis.set_label_coords(labelx, 0.5)\n\n\nplt.show()"
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"import numpy as np\nimport matplotlib.pyplot as plt\n\nbox = dict(facecolor='yellow', pad=5, alpha=0.2)\n\nfig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)\nfig.subplots_adjust(left=0.2, wspace=0.6)\n\n# Fixing random state for reproducibility\nnp.random.seed(19680801)\n\nax1.plot(2000*np.random.rand(10))\nax1.set_title('ylabels not aligned')\nax1.set_ylabel('misaligned 1', bbox=box)\nax1.set_ylim(0, 2000)\n\nax3.set_ylabel('misaligned 2',bbox=box)\nax3.plot(np.random.rand(10))\n\nlabelx = -0.3 # axes coords\n\nax2.set_title('ylabels aligned')\nax2.plot(2000*np.random.rand(10))\nax2.set_ylabel('aligned 1', bbox=box)\nax2.yaxis.set_label_coords(labelx, 0.5)\nax2.set_ylim(0, 2000)\n\nax4.plot(np.random.rand(10))\nax4.set_ylabel('aligned 2', bbox=box)\nax4.yaxis.set_label_coords(labelx, 0.5)\n\nplt.show()"
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‎_downloads/align_ylabels.py‎

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box = dict(facecolor='yellow', pad=5, alpha=0.2)
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fig = plt.figure()
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fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)
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fig.subplots_adjust(left=0.2, wspace=0.6)
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# Fixing random state for reproducibility
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np.random.seed(19680801)
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ax1 = fig.add_subplot(221)
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ax1.plot(2000*np.random.rand(10))
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ax1.set_title('ylabels not aligned')
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ax1.set_ylabel('misaligned 1', bbox=box)
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ax1.set_ylim(0, 2000)
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ax3 = fig.add_subplot(223)
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ax3.set_ylabel('misaligned 2',bbox=box)
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ax3.plot(np.random.rand(10))
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labelx = -0.3 # axes coords
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ax2 = fig.add_subplot(222)
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ax2.set_title('ylabels aligned')
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ax2.plot(2000*np.random.rand(10))
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ax2.set_ylabel('aligned 1', bbox=box)
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ax2.yaxis.set_label_coords(labelx, 0.5)
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ax2.set_ylim(0, 2000)
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ax4 = fig.add_subplot(224)
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ax4.plot(np.random.rand(10))
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ax4.set_ylabel('aligned 2', bbox=box)
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ax4.yaxis.set_label_coords(labelx, 0.5)
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plt.show()

‎_downloads/anchored_artists.ipynb‎

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},
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"outputs": [],
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"source": [
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"from matplotlib.patches import Rectangle, Ellipse\n\nfrom matplotlib.offsetbox import AnchoredOffsetbox, AuxTransformBox, VPacker,\\\n TextArea, DrawingArea\n\n\nclass AnchoredText(AnchoredOffsetbox):\n def __init__(self, s, loc, pad=0.4, borderpad=0.5,\n prop=None, frameon=True):\n\n self.txt = TextArea(s,\n minimumdescent=False)\n\n super(AnchoredText, self).__init__(loc, pad=pad, borderpad=borderpad,\n child=self.txt,\n prop=prop,\n frameon=frameon)\n\n\nclass AnchoredSizeBar(AnchoredOffsetbox):\n def __init__(self, transform, size, label, loc,\n pad=0.1, borderpad=0.1, sep=2, prop=None, frameon=True):\n \"\"\"\n Draw a horizontal bar with the size in data coordinate of the given\n axes. A label will be drawn underneath (center-aligned).\n\n pad, borderpad in fraction of the legend font size (or prop)\n sep in points.\n \"\"\"\n self.size_bar = AuxTransformBox(transform)\n self.size_bar.add_artist(Rectangle((0, 0), size, 0, fc=\"none\", lw=1.0))\n\n self.txt_label = TextArea(label, minimumdescent=False)\n\n self._box = VPacker(children=[self.size_bar, self.txt_label],\n align=\"center\",\n pad=0, sep=sep)\n\n AnchoredOffsetbox.__init__(self, loc, pad=pad, borderpad=borderpad,\n child=self._box,\n prop=prop,\n frameon=frameon)\n\n\nclass AnchoredEllipse(AnchoredOffsetbox):\n def __init__(self, transform, width, height, angle, loc,\n pad=0.1, borderpad=0.1, prop=None, frameon=True):\n \"\"\"\n Draw an ellipse the size in data coordinate of the give axes.\n\n pad, borderpad in fraction of the legend font size (or prop)\n \"\"\"\n self._box = AuxTransformBox(transform)\n self.ellipse = Ellipse((0, 0), width, height, angle)\n self._box.add_artist(self.ellipse)\n\n AnchoredOffsetbox.__init__(self, loc, pad=pad, borderpad=borderpad,\n child=self._box,\n prop=prop,\n frameon=frameon)\n\n\nclass AnchoredDrawingArea(AnchoredOffsetbox):\n def __init__(self, width, height, xdescent, ydescent,\n loc, pad=0.4, borderpad=0.5, prop=None, frameon=True):\n\n self.da = DrawingArea(width, height, xdescent, ydescent)\n\n super(AnchoredDrawingArea, self).__init__(loc, pad=pad,\n borderpad=borderpad,\n child=self.da,\n prop=None,\n frameon=frameon)\n\n\nif __name__ == \"__main__\":\n\n import matplotlib.pyplot as plt\n\n ax = plt.gca()\n ax.set_aspect(1.)\n\n at = AnchoredText(\"Figure 1a\",\n loc=2, frameon=True)\n at.patch.set_boxstyle(\"round,pad=0.,rounding_size=0.2\")\n ax.add_artist(at)\n\n from matplotlib.patches import Circle\n ada = AnchoredDrawingArea(20, 20, 0, 0,\n loc=1, pad=0., frameon=False)\n p = Circle((10, 10), 10)\n ada.da.add_artist(p)\n ax.add_artist(ada)\n\n # draw an ellipse of width=0.1, height=0.15 in the data coordinate\n ae = AnchoredEllipse(ax.transData, width=0.1, height=0.15, angle=0.,\n loc=3, pad=0.5, borderpad=0.4, frameon=True)\n\n ax.add_artist(ae)\n\n # draw a horizontal bar with length of 0.1 in Data coordinate\n # (ax.transData) with a label underneath.\n asb = AnchoredSizeBar(ax.transData,\n 0.1,\n r\"1$^{\\prime}$\",\n loc=8,\n pad=0.1, borderpad=0.5, sep=5,\n frameon=False)\n ax.add_artist(asb)\n\n plt.draw()\n plt.show()"
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"from matplotlib.patches import Rectangle, Ellipse\n\nfrom matplotlib.offsetbox import AnchoredOffsetbox, AuxTransformBox, VPacker,\\\n TextArea, DrawingArea\n\n\nclass AnchoredText(AnchoredOffsetbox):\n def __init__(self, s, loc, pad=0.4, borderpad=0.5,\n prop=None, frameon=True):\n\n self.txt = TextArea(s,\n minimumdescent=False)\n\n super(AnchoredText, self).__init__(loc, pad=pad, borderpad=borderpad,\n child=self.txt,\n prop=prop,\n frameon=frameon)\n\n\nclass AnchoredSizeBar(AnchoredOffsetbox):\n def __init__(self, transform, size, label, loc,\n pad=0.1, borderpad=0.1, sep=2, prop=None, frameon=True):\n \"\"\"\n Draw a horizontal bar with the size in data coordinate of the given\n axes. A label will be drawn underneath (center-aligned).\n\n pad, borderpad in fraction of the legend font size (or prop)\n sep in points.\n \"\"\"\n self.size_bar = AuxTransformBox(transform)\n self.size_bar.add_artist(Rectangle((0, 0), size, 0, ec=\"black\", lw=1.0))\n\n self.txt_label = TextArea(label, minimumdescent=False)\n\n self._box = VPacker(children=[self.size_bar, self.txt_label],\n align=\"center\",\n pad=0, sep=sep)\n\n AnchoredOffsetbox.__init__(self, loc, pad=pad, borderpad=borderpad,\n child=self._box,\n prop=prop,\n frameon=frameon)\n\n\nclass AnchoredEllipse(AnchoredOffsetbox):\n def __init__(self, transform, width, height, angle, loc,\n pad=0.1, borderpad=0.1, prop=None, frameon=True):\n \"\"\"\n Draw an ellipse the size in data coordinate of the give axes.\n\n pad, borderpad in fraction of the legend font size (or prop)\n \"\"\"\n self._box = AuxTransformBox(transform)\n self.ellipse = Ellipse((0, 0), width, height, angle)\n self._box.add_artist(self.ellipse)\n\n AnchoredOffsetbox.__init__(self, loc, pad=pad, borderpad=borderpad,\n child=self._box,\n prop=prop,\n frameon=frameon)\n\n\nclass AnchoredDrawingArea(AnchoredOffsetbox):\n def __init__(self, width, height, xdescent, ydescent,\n loc, pad=0.4, borderpad=0.5, prop=None, frameon=True):\n\n self.da = DrawingArea(width, height, xdescent, ydescent)\n\n super(AnchoredDrawingArea, self).__init__(loc, pad=pad,\n borderpad=borderpad,\n child=self.da,\n prop=None,\n frameon=frameon)\n\n\nif __name__ == \"__main__\":\n\n import matplotlib.pyplot as plt\n\n ax = plt.gca()\n ax.set_aspect(1.)\n\n at = AnchoredText(\"Figure 1a\",\n loc=2, frameon=True)\n at.patch.set_boxstyle(\"round,pad=0.,rounding_size=0.2\")\n ax.add_artist(at)\n\n from matplotlib.patches import Circle\n ada = AnchoredDrawingArea(20, 20, 0, 0,\n loc=1, pad=0., frameon=False)\n p = Circle((10, 10), 10)\n ada.da.add_artist(p)\n ax.add_artist(ada)\n\n # draw an ellipse of width=0.1, height=0.15 in the data coordinate\n ae = AnchoredEllipse(ax.transData, width=0.1, height=0.15, angle=0.,\n loc=3, pad=0.5, borderpad=0.4, frameon=True)\n\n ax.add_artist(ae)\n\n # draw a horizontal bar with length of 0.1 in Data coordinate\n # (ax.transData) with a label underneath.\n asb = AnchoredSizeBar(ax.transData,\n 0.1,\n r\"1$^{\\prime}$\",\n loc=8,\n pad=0.1, borderpad=0.5, sep=5,\n frameon=False)\n ax.add_artist(asb)\n\n plt.draw()\n plt.show()"
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‎_downloads/anchored_artists.py‎

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sep in points.
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"""
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self.size_bar = AuxTransformBox(transform)
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self.size_bar.add_artist(Rectangle((0, 0), size, 0, fc="none", lw=1.0))
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self.size_bar.add_artist(Rectangle((0, 0), size, 0, ec="black", lw=1.0))
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self.txt_label = TextArea(label, minimumdescent=False)
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‎_downloads/animate_decay.ipynb‎

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n# Decay\n\n\nA sinusoidal decay animation.\n\n"
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"\n# Decay\n\n\nThis example showcases:\n- using a generator to drive an animation,\n- changing axes limits during an animation.\n\n"
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]
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},
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{

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