.. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_gallery_shapes_and_collections_collections.py: ========================================================= Line, Poly and RegularPoly Collection with autoscaling ========================================================= For the first two subplots, we will use spirals. Their size will be set in plot units, not data units. Their positions will be set in data units by using the "offsets" and "transOffset" kwargs of the `~.collections.LineCollection` and `~.collections.PolyCollection`. The third subplot will make regular polygons, with the same type of scaling and positioning as in the first two. The last subplot illustrates the use of "offsets=(xo, yo)", that is, a single tuple instead of a list of tuples, to generate successively offset curves, with the offset given in data units. This behavior is available only for the LineCollection. .. code-block:: default import matplotlib.pyplot as plt from matplotlib import collections, colors, transforms import numpy as np nverts = 50 npts = 100 # Make some spirals r = np.arange(nverts) theta = np.linspace(0, 2*np.pi, nverts) xx = r * np.sin(theta) yy = r * np.cos(theta) spiral = np.column_stack([xx, yy]) # Fixing random state for reproducibility rs = np.random.RandomState(19680801) # Make some offsets xyo = rs.randn(npts, 2) # Make a list of colors cycling through the default series. colors = [colors.to_rgba(c) for c in plt.rcParams['axes.prop_cycle'].by_key()['color']] fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2) fig.subplots_adjust(top=0.92, left=0.07, right=0.97, hspace=0.3, wspace=0.3) col = collections.LineCollection([spiral], offsets=xyo, transOffset=ax1.transData) trans = fig.dpi_scale_trans + transforms.Affine2D().scale(1.0/72.0) col.set_transform(trans) # the points to pixels transform # Note: the first argument to the collection initializer # must be a list of sequences of (x, y) tuples; we have only # one sequence, but we still have to put it in a list. ax1.add_collection(col, autolim=True) # autolim=True enables autoscaling. For collections with # offsets like this, it is neither efficient nor accurate, # but it is good enough to generate a plot that you can use # as a starting point. If you know beforehand the range of # x and y that you want to show, it is better to set them # explicitly, leave out the autolim kwarg (or set it to False), # and omit the 'ax1.autoscale_view()' call below. # Make a transform for the line segments such that their size is # given in points: col.set_color(colors) ax1.autoscale_view() # See comment above, after ax1.add_collection. ax1.set_title('LineCollection using offsets') # The same data as above, but fill the curves. col = collections.PolyCollection([spiral], offsets=xyo, transOffset=ax2.transData) trans = transforms.Affine2D().scale(fig.dpi/72.0) col.set_transform(trans) # the points to pixels transform ax2.add_collection(col, autolim=True) col.set_color(colors) ax2.autoscale_view() ax2.set_title('PolyCollection using offsets') # 7-sided regular polygons col = collections.RegularPolyCollection( 7, sizes=np.abs(xx) * 10.0, offsets=xyo, transOffset=ax3.transData) trans = transforms.Affine2D().scale(fig.dpi / 72.0) col.set_transform(trans) # the points to pixels transform ax3.add_collection(col, autolim=True) col.set_color(colors) ax3.autoscale_view() ax3.set_title('RegularPolyCollection using offsets') # Simulate a series of ocean current profiles, successively # offset by 0.1 m/s so that they form what is sometimes called # a "waterfall" plot or a "stagger" plot. nverts = 60 ncurves = 20 offs = (0.1, 0.0) yy = np.linspace(0, 2*np.pi, nverts) ym = np.max(yy) xx = (0.2 + (ym - yy) / ym) ** 2 * np.cos(yy - 0.4) * 0.5 segs = [] for i in range(ncurves): xxx = xx + 0.02*rs.randn(nverts) curve = np.column_stack([xxx, yy * 100]) segs.append(curve) col = collections.LineCollection(segs, offsets=offs) ax4.add_collection(col, autolim=True) col.set_color(colors) ax4.autoscale_view() ax4.set_title('Successive data offsets') ax4.set_xlabel('Zonal velocity component (m/s)') ax4.set_ylabel('Depth (m)') # Reverse the y-axis so depth increases downward ax4.set_ylim(ax4.get_ylim()[::-1]) plt.show() .. image:: /gallery/shapes_and_collections/images/sphx_glr_collections_001.png :alt: LineCollection using offsets, PolyCollection using offsets, RegularPolyCollection using offsets, Successive data offsets :class: sphx-glr-single-img ------------ References """""""""" The use of the following functions, methods, classes and modules is shown in this example: .. code-block:: default import matplotlib matplotlib.figure.Figure matplotlib.collections matplotlib.collections.LineCollection matplotlib.collections.RegularPolyCollection matplotlib.axes.Axes.add_collection matplotlib.axes.Axes.autoscale_view matplotlib.transforms.Affine2D matplotlib.transforms.Affine2D.scale .. rst-class:: sphx-glr-script-out Out: .. code-block:: none .. _sphx_glr_download_gallery_shapes_and_collections_collections.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: collections.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: collections.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature Keywords: matplotlib code example, codex, python plot, pyplot `Gallery generated by Sphinx-Gallery `_