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280 lines
14 KiB
Python
280 lines
14 KiB
Python
#===============================================================================
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# Copyright (c) 2015, Max Zwiessele
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# All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are met:
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#
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# * Redistributions of source code must retain the above copyright notice, this
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# list of conditions and the following disclaimer.
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#
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# * Redistributions in binary form must reproduce the above copyright notice,
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# this list of conditions and the following disclaimer in the documentation
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# and/or other materials provided with the distribution.
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#
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# * Neither the name of GPy.plotting.abstract_plotting_library nor the names of its
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# contributors may be used to endorse or promote products derived from
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# this software without specific prior written permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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#===============================================================================
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#===============================================================================
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# Make sure that the necessary files and functions are
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# defined in the plotting library:
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class AbstractPlottingLibrary(object):
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def __init__(self):
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"""
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Set the defaults dictionary in the _defaults variable:
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E.g. for matplotlib we define a file defaults.py and
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set the dictionary of it here:
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from . import defaults
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_defaults = defaults.__dict__
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"""
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self._defaults = {}
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self.__defaults = None
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@property
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def defaults(self):
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#===============================================================================
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if self.__defaults is None:
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from collections import defaultdict
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class defaultdict(defaultdict):
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def __getattr__(self, *args, **kwargs):
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return defaultdict.__getitem__(self, *args, **kwargs)
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self.__defaults = defaultdict(dict, self._defaults)
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return self.__defaults
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#===============================================================================
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def figure(self, nrows, ncols, **kwargs):
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"""
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Get a new figure with nrows and ncolumns subplots.
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Does not initialize the canvases yet.
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"""
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raise NotImplementedError("Implement all plot functions in AbstractPlottingLibrary in order to use your own plotting library")
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def new_canvas(self, figure=None, col=1, row=1, projection='2d', xlabel=None, ylabel=None, zlabel=None, title=None, xlim=None, ylim=None, zlim=None, **kwargs):
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"""
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Return a canvas, kwargupdate for your plotting library.
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if figure is not None, create a canvas in the figure
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at subplot position (col, row).
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This method does two things, it creates an empty canvas
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and updates the kwargs (deletes the unnecessary kwargs)
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for further usage in normal plotting.
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the kwargs are plotting library specific kwargs!
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:param {'2d'|'3d'} projection: The projection to use.
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E.g. in matplotlib this means it deletes references to ax, as
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plotting is done on the axis itself and is not a kwarg.
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:param xlabel: the label to put on the xaxis
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:param ylabel: the label to put on the yaxis
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:param zlabel: the label to put on the zaxis (if plotting in 3d)
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:param title: the title of the plot
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:param legend: if True, plot a legend, if int make legend rows in the legend
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:param (float, float) xlim: the limits for the xaxis
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:param (float, float) ylim: the limits for the yaxis
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:param (float, float) zlim: the limits for the zaxis (if plotting in 3d)
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"""
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raise NotImplementedError("Implement all plot functions in AbstractPlottingLibrary in order to use your own plotting library")
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def add_to_canvas(self, canvas, plots, legend=True, title=None, **kwargs):
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"""
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Add plots is a dictionary with the plots as the
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items or a list of plots as items to canvas.
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The kwargs are plotting library specific kwargs!
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E.g. in matplotlib this does not have to do anything to add stuff, but
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we set the legend and title.
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!This function returns the updated canvas!
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:param title: the title of the plot
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:param legend: whether to plot a legend or not
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"""
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raise NotImplementedError("Implement all plot functions in AbstractPlottingLibrary in order to use your own plotting library")
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def show_canvas(self, canvas, **kwargs):
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"""
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Draw/Plot the canvas given.
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"""
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raise NotImplementedError
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def plot(self, cavas, X, Y, Z=None, color=None, label=None, **kwargs):
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"""
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Make a line plot from for Y on X (Y = f(X)) on the canvas.
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If Z is not None, plot in 3d!
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the kwargs are plotting library specific kwargs!
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"""
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raise NotImplementedError("Implement all plot functions in AbstractPlottingLibrary in order to use your own plotting library")
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def plot_axis_lines(self, ax, X, color=None, label=None, **kwargs):
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"""
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Plot lines at the bottom (lower boundary of yaxis) of the axis at input location X.
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If X is two dimensional, plot in 3d and connect the axis lines to the bottom of the Z axis.
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the kwargs are plotting library specific kwargs!
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"""
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raise NotImplementedError("Implement all plot functions in AbstractPlottingLibrary in order to use your own plotting library")
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def surface(self, canvas, X, Y, Z, color=None, label=None, **kwargs):
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"""
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Plot a surface for 3d plotting for the inputs (X, Y, Z).
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the kwargs are plotting library specific kwargs!
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"""
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raise NotImplementedError("Implement all plot functions in AbstractPlottingLibrary in order to use your own plotting library")
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def scatter(self, canvas, X, Y, Z=None, color=None, vmin=None, vmax=None, label=None, **kwargs):
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"""
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Make a scatter plot between X and Y on the canvas given.
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the kwargs are plotting library specific kwargs!
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:param canvas: the plotting librarys specific canvas to plot on.
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:param array-like X: the inputs to plot.
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:param array-like Y: the outputs to plot.
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:param array-like Z: the Z level to plot (if plotting 3d).
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:param array-like c: the colorlevel for each point.
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:param float vmin: minimum colorscale
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:param float vmax: maximum colorscale
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:param kwargs: the specific kwargs for your plotting library
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"""
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raise NotImplementedError("Implement all plot functions in AbstractPlottingLibrary in order to use your own plotting library")
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def barplot(self, canvas, x, height, width=0.8, bottom=0, color=None, label=None, **kwargs):
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"""
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Plot vertical bar plot centered at x with height
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and width of bars. The y level is at bottom.
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the kwargs are plotting library specific kwargs!
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:param array-like x: the center points of the bars
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:param array-like height: the height of the bars
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:param array-like width: the width of the bars
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:param array-like bottom: the start y level of the bars
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:param kwargs: kwargs for the specific library you are using.
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"""
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raise NotImplementedError("Implement all plot functions in AbstractPlottingLibrary in order to use your own plotting library")
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def xerrorbar(self, canvas, X, Y, error, color=None, label=None, **kwargs):
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"""
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Make an errorbar along the xaxis for points at (X,Y) on the canvas.
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if error is two dimensional, the lower error is error[:,0] and
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the upper error is error[:,1]
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the kwargs are plotting library specific kwargs!
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"""
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raise NotImplementedError("Implement all plot functions in AbstractPlottingLibrary in order to use your own plotting library")
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def yerrorbar(self, canvas, X, Y, error, color=None, label=None, **kwargs):
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"""
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Make errorbars along the yaxis on the canvas given.
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if error is two dimensional, the lower error is error[0, :] and
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the upper error is error[1, :]
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the kwargs are plotting library specific kwargs!
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"""
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raise NotImplementedError("Implement all plot functions in AbstractPlottingLibrary in order to use your own plotting library")
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def imshow(self, canvas, X, extent=None, label=None, vmin=None, vmax=None, **kwargs):
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"""
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Show the image stored in X on the canvas.
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The origin of the image show is (0,0), such that X[0,0] gets plotted at [0,0] of the image!
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the kwargs are plotting library specific kwargs!
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"""
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raise NotImplementedError("Implement all plot functions in AbstractPlottingLibrary in order to use your own plotting library")
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def imshow_interact(self, canvas, plot_function, extent=None, label=None, vmin=None, vmax=None, **kwargs):
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"""
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This function is optional!
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Create an imshow controller to stream
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the image returned by the plot_function. There is an imshow controller written for
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mmatplotlib, which updates the imshow on changes in axis.
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The origin of the image show is (0,0), such that X[0,0] gets plotted at [0,0] of the image!
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the kwargs are plotting library specific kwargs!
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"""
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raise NotImplementedError("Implement all plot functions in AbstractPlottingLibrary in order to use your own plotting library")
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def annotation_heatmap(self, canvas, X, annotation, extent, label=None, **kwargs):
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"""
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Plot an annotation heatmap. That is like an imshow, but
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put the text of the annotation inside the cells of the heatmap (centered).
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:param canvas: the canvas to plot on
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:param array-like annotation: the annotation labels for the heatmap
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:param [horizontal_min,horizontal_max,vertical_min,vertical_max] extent: the extent of where to place the heatmap
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:param str label: the label for the heatmap
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:return: a list of both the heatmap and annotation plots [heatmap, annotation], or the interactive update object (alone)
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"""
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raise NotImplementedError("Implement all plot functions in AbstractPlottingLibrary in order to use your own plotting library")
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def annotation_heatmap_interact(self, canvas, plot_function, extent, label=None, resolution=15, **kwargs):
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"""
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if plot_function is not None, return an interactive updated
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heatmap, which updates on axis events, so that one can zoom in
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and out and the heatmap gets updated. See the matplotlib implementation
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in matplot_dep.controllers.
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the plot_function returns a pair (X, annotation) to plot, when called with
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a new input X (which would be the grid, which is visible on the plot
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right now)
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:param canvas: the canvas to plot on
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:param array-like annotation: the annotation labels for the heatmap
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:param [horizontal_min,horizontal_max,vertical_min,vertical_max] extent: the extent of where to place the heatmap
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:param str label: the label for the heatmap
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:return: a list of both the heatmap and annotation plots [heatmap, annotation], or the interactive update object (alone)
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:param plot_function: the function, which generates new data for given input locations X
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:param int resolution: the resolution of the interactive plot redraw - this is only needed when giving a plot_function
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"""
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raise NotImplementedError("Implement all plot functions in AbstractPlottingLibrary in order to use your own plotting library")
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def contour(self, canvas, X, Y, C, Z=None, color=None, label=None, **kwargs):
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"""
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Make a contour plot at (X, Y) with heights/colors stored in C on the canvas.
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if Z is not None: make 3d contour plot at (X, Y, Z) with heights/colors stored in C on the canvas.
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the kwargs are plotting library specific kwargs!
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"""
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raise NotImplementedError("Implement all plot functions in AbstractPlottingLibrary in order to use your own plotting library")
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def fill_between(self, canvas, X, lower, upper, color=None, label=None, **kwargs):
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"""
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Fill along the xaxis between lower and upper.
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the kwargs are plotting library specific kwargs!
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"""
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raise NotImplementedError("Implement all plot functions in AbstractPlottingLibrary in order to use your own plotting library")
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def fill_gradient(self, canvas, X, percentiles, color=None, label=None, **kwargs):
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"""
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Plot a gradient (in alpha values) for the given percentiles.
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the kwargs are plotting library specific kwargs!
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"""
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print("fill_gradient not implemented in this backend.")
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