Sympy plot aspect ratio

Documentation Help Center. The axis command works by setting various axes object properties. You can set these properties directly to achieve precisely the effect you want. Sets the relative scaling of the individual axis data values. Set DataAspectRatio to [1 1 1] to display real-world objects in correct proportions.

Specifying a value for DataAspectRatio overrides stretch-to-fill behavior. Sets the proportions of the axes plot box set box to on to see the box.

Specifying a value for PlotBoxAspectRatio overrides stretch-to-fill behavior. Defines the location and size of the axes with a four-element vector: [ left offsetbottom offsetwidthheight ]. Sets the minimum and maximum limits of the respective axes. When the mode properties are set to autoMATLAB automatically determines values for all of these properties and then stretches the axes to fit the figure shape.

You can override any property's automatic operation by specifying a value for the property or setting its mode property to manual. The value you select for a particular property depends primarily on what type of data you want to display. Representations of real-world objects e. In the first case, it is generally desirable to select axis limits that provide good resolution in each axis direction and to fill the available space. Real-world objects, on the other hand, need to be represented accurately in proportion, regardless of the angle of view.

Provide the highest resolution in the available space by setting the scale of each axis independently when DataAspectRatioMode and the PlotBoxAspectRatioMode are set to auto.

Draw axes that fit the position rectangle by adjusting the CameraViewAngle and then stretch-to-fill the axes if necessary. The axes Position property specifies the location and dimensions of the axes within the figure.

The default value for the axes Units property is normalized to the parent figure dimensions. This means the shape of the figure window determines the shape of the position rectangle.

Changing the size and shape of the figure causes a change in the size and shape of the axes.If not Nonethis defines which parameter will be adjusted to meet the required aspect. If not Nonethis defines where the Axes will be drawn if there is extra space due to aspect constraints. The most common way to to specify the anchor are abbreviations of cardinal directions:. If Trueapply the settings to all shared Axes. Default is False. Bar chart with gradients.

Tricontour Demo. Tricontour Smooth Delaunay. Tricontour Smooth User. Trigradient Demo. Tripcolor Demo. Triplot Demo. Zooming in and out using Axes. Mmh Donuts!!! Inset Locator Demo2. Scatter Hist.

Cartesian coordinates with fixed "aspect ratio"

Simple Anchored Artists. Anchored Artists. Demo Agg Filter. Rasterization Demo. Loglog Aspect. Annotate Text Arrow. DivergingNorm colormap normalization. Colormap Normalization. Version 3. Table of Contents matplotlib. Show Page Source.

The most common way to to specify the anchor are abbreviations of cardinal directions: value description 'C' centered 'SW' lower left corner 'S' middle of bottom edge 'SE' lower right corner etc. See also matplotlib. Examples using matplotlib.

Last updated on Feb 09, Created using Sphinx 1. Doc version v3.The plotting module allows you to make 2-dimensional and 3-dimensional plots. Presently the plots are rendered using matplotlib as a backend. The above functions are only for convenience and ease of use. It is possible to plot any plot by passing the corresponding Series class to Plot as argument.

For interactive work the function plot is better suited. This class permits the plotting of sympy expressions using numerous backends matplotlib, textplot, the old pyglet module for sympy, Google charts api, etc. The figure can contain an arbitrary number of plots of sympy expressions, lists of coordinates of points, etc.

The customization of the figure is on two levels. Global options that concern the figure as a whole eg title, xlabel, scale, etc and per-data series options eg name and aesthetics eg. The difference between options and aesthetics is that an aesthetic can be a function of the coordinates or parameters in a parametric plot. The supported values for an aesthetic are: - None the backend uses default values - a constant - a function of one variable the first coordinate or parameter - a function of two variables the first and second coordinate or parameters - a function of three variables only in nonparametric 3D plots Their implementation depends on the backend so they may not work in some backends.

If the plot is parametric and the arity of the aesthetic function permits it the aesthetic is calculated over parameters and not over coordinates. If the arity does not permit calculation over parameters the calculation is done over coordinates. Only cartesian coordinates are supported for the moment, but you can use the parametric plots to plot in polar, spherical and cylindrical coordinates.

The per data series options and aesthetics are: There are none in the base series. See below for options for subclasses. Consider two Plot objects, p1 and p2. To add the second plot to the first, use the extend method, like so:. Plots a function of a single variable and returns an instance of the Plot class also, see the description of the show keyword argument below. The plotting uses an adaptive algorithm which samples recursively to accurately plot the plot.

The adaptive algorithm uses a random point near the midpoint of two points that has to be further sampled. Hence the same plots can appear slightly different. Default range may change in the future if a more advanced default range detection algorithm is implemented. The default value is set to True. Set show to False and the function will not display the plot. The returned instance of the Plot class can then be used to save or display the plot by calling the save and show methods respectively.

Used when the adaptive is set to False. Specifies the color for the plot.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service.

The dark mode beta is finally here. Change your preferences any time. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. I'm using Spyder's Ipython console to try to get some quick parametric plots of functions. I ran the command.

sympy plot aspect ratio

After looking at this answer In sympy plotting, how can I get a plot with a fixed aspect ratio? I tried following their instructions to try to leverage matplotlib and I get no errors. But when I enter. You need to use fig. The following example produces a graph with equal aspect ratio:.

Learn more. Sympy: Set aspect ratio Ask Question. Asked 3 years ago. Active 3 years ago. Viewed times. I ran the command import sympy as sp sp. If I enter p. I try other aspect ratios and still nothing changes. But when I enter plt. Addem Addem 2, 2 2 gold badges 14 14 silver badges 42 42 bronze badges. Active Oldest Votes.

The following example produces a graph with equal aspect ratio: import sympy as sp sp. Craig Craig 3, 1 1 gold badge 12 12 silver badges 21 21 bronze badges. The corresponding Sympy issue is github.Documentation Help Center. You can control the relative lengths of the x -axis, y -axis, and z -axis plot box aspect ratio.

You also can control the relative lengths of one data unit along each axis data aspect ratio. The plot box aspect ratio is the relative lengths of the x -axis, y -axis, and z -axis.

By default, the plot box aspect ratio is based on the size of the figure. You can change the aspect ratio using the pbaspect function.

Set the ratio as a three-element vector of positive values that represent the relative axis lengths. For example, plot an elongated circle. Then set the plot box aspect ratio so that the x-axis is twice the length of the y -axis and z -axis not shown.

For square axes, use [1 1 1]. This value is similar to using the axis square command. The data aspect ratio is the relative length of the data units along the x -axis, y -axis, and z -axis. You can change the aspect ratio using the daspect function. Set the ratio as a three-element vector of positive values that represent the relative lengths of data units along each axis. For example, set the ratio so that the length from 0 to 1 along the x -axis is equal to the length from 0 to 0.

For equal data units in all directions, use [1 1 1]. This value is similar to using the axis equal command. One data unit in the x direction is the same length as one data unit in the y and z directions.

Change the data aspect ratio. Then revert back to the default plot box and data aspect ratios using the axis normal command. A modified version of this example exists on your system.The plotting module allows you to make 2-dimensional and 3-dimensional plots. Presently the plots are rendered using matplotlib as a backend. The above functions are only for convenience and ease of use.

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It is possible to plot any plot by passing the corresponding Series class to Plot as argument. For interactive work the function plot is better suited. This class permits the plotting of sympy expressions using numerous backends matplotlib, textplot, the old pyglet module for sympy, Google charts api, etc.

The figure can contain an arbitrary number of plots of sympy expressions, lists of coordinates of points, etc. The customization of the figure is on two levels. Global options that concern the figure as a whole eg title, xlabel, scale, etc and per-data series options eg name and aesthetics eg. The difference between options and aesthetics is that an aesthetic can be a function of the coordinates or parameters in a parametric plot.

The supported values for an aesthetic are: - None the backend uses default values - a constant - a function of one variable the first coordinate or parameter - a function of two variables the first and second coordinate or parameters - a function of three variables only in nonparametric 3D plots Their implementation depends on the backend so they may not work in some backends.

AspectRatio

If the plot is parametric and the arity of the aesthetic function permits it the aesthetic is calculated over parameters and not over coordinates. If the arity does not permit calculation over parameters the calculation is done over coordinates. Only cartesian coordinates are supported for the moment, but you can use the parametric plots to plot in polar, spherical and cylindrical coordinates.

The per data series options and aesthetics are: There are none in the base series. See below for options for subclasses. Consider two Plot objects, p1 and p2. To add the second plot to the first, use the extend method, like so:.

Plots a function of a single variable and returns an instance of the Plot class also, see the description of the show keyword argument below. The plotting uses an adaptive algorithm which samples recursively to accurately plot the plot. The adaptive algorithm uses a random point near the midpoint of two points that has to be further sampled. Hence the same plots can appear slightly different. Default range may change in the future if a more advanced default range detection algorithm is implemented.

Arguments for plot function:. The default value is set to True. Set show to False and the function will not display the plot. The returned instance of the Plot class can then be used to save or display the plot by calling the save and show methods respectively.

Used when the adaptive is set to False. Specifies the color for the plot.

SymPy Gamma and SymPy Live: Python and Mathematics Online; SciPy 2013 Presentation

See Plot to see how to set color for the plots. If there are multiple plots, then the same series series are applied to all the plots. If you want to set these options separately, you can index the Plot object returned and set it. Arguments for Plot class:.GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together.

Skip to content. Permalink Dismiss Join GitHub today GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together.

Sign up. Branch: master. Find file Copy path. Raw Blame History. The data series are instances of classes meant to simplify getting points and meshes from sympy expressions. This module gives only the essential. For all the fancy stuff use directly the backend. Simplicity of code takes much greater importance than performance. Don't use it if you care at all about performance. For use in the tests. This class permits the plotting of sympy expressions using numerous backends matplotlib, textplot, the old pyglet module for sympy, Google charts api, etc.

The figure can contain an arbitrary number of plots of sympy expressions, lists of coordinates of points, etc. The customization of the figure is on two levels. Global options that concern the figure as a whole eg title, xlabel, scale, etc and per-data series options eg name and aesthetics eg. The difference between options and aesthetics is that an aesthetic can be a function of the coordinates or parameters in a parametric plot.

sympy plot aspect ratio

The supported values for an aesthetic are: - None the backend uses default values - a constant - a function of one variable the first coordinate or parameter - a function of two variables the first and second coordinate or parameters - a function of three variables only in nonparametric 3D plots Their implementation depends on the backend so they may not work in some backends.

If the plot is parametric and the arity of the aesthetic function permits it the aesthetic is calculated over parameters and not over coordinates. If the arity does not permit calculation over parameters the calculation is done over coordinates. Only cartesian coordinates are supported for the moment, but you can use the parametric plots to plot in polar, spherical and cylindrical coordinates. The arguments for the constructor Plot must be subclasses of BaseSeries.

Any global option can be specified as a keyword argument. See below for options for subclasses. The possible values for each option are described in the docstring of Plot. They are based purely on convention, no checking is done. The backend should be smart enough to iterate over this list. On every show a new backend instance is created in self.

The backend should check if it supports the data series that it's given. It's the backend responsibility to know how to use the class of data series that it's given.

The backend is not obliged to use that api eg.

sympy plot aspect ratio

The rationale for using flags instead of checking base classes is that setting multiple flags is simpler than multiple inheritance. The adaptive sampling is done by recursively checking if three points are almost collinear. If they are not collinear, then more points are added between those points. The maximum depth allowed is We are not using linspace to avoid aliasing. If there is a real value in between, then sample those points further.

Most of the stuff is derived from Line2DBaseSeries.


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