Density plots¶
- class sage.plot.density_plot.DensityPlot(xy_data_array, xrange, yrange, options)[source]¶
Bases:
GraphicPrimitive
Primitive class for the density plot graphics type. See
density_plot?
for help actually doing density plots.INPUT:
xy_data_array
– list of lists giving evaluated values of the function on the gridxrange
– tuple of 2 floats indicating range for horizontal directionyrange
– tuple of 2 floats indicating range for vertical directionoptions
– dictionary of valid plot options to pass to constructor
EXAMPLES:
Note this should normally be used indirectly via
density_plot
:sage: from sage.plot.density_plot import DensityPlot sage: D = DensityPlot([[1,3],[2,4]], (1,2), (2,3),options={}) sage: D DensityPlot defined by a 2 x 2 data grid sage: D.yrange (2, 3) sage: D.options() {}
>>> from sage.all import * >>> from sage.plot.density_plot import DensityPlot >>> D = DensityPlot([[Integer(1),Integer(3)],[Integer(2),Integer(4)]], (Integer(1),Integer(2)), (Integer(2),Integer(3)),options={}) >>> D DensityPlot defined by a 2 x 2 data grid >>> D.yrange (2, 3) >>> D.options() {}
- get_minmax_data()[source]¶
Return a dictionary with the bounding box data.
EXAMPLES:
sage: x,y = var('x,y') sage: f(x, y) = x^2 + y^2 sage: d = density_plot(f, (3,6), (3,6))[0].get_minmax_data() sage: d['xmin'] 3.0 sage: d['ymin'] 3.0
>>> from sage.all import * >>> x,y = var('x,y') >>> __tmp__=var("x,y"); f = symbolic_expression(x**Integer(2) + y**Integer(2)).function(x,y) >>> d = density_plot(f, (Integer(3),Integer(6)), (Integer(3),Integer(6)))[Integer(0)].get_minmax_data() >>> d['xmin'] 3.0 >>> d['ymin'] 3.0
- sage.plot.density_plot.density_plot(f, xrange, yrange, plot_points=25, cmap='gray', interpolation='catrom', **options)[source]¶
density_plot
takes a function of two variables, \(f(x,y)\) and plots the height of the function over the specifiedxrange
andyrange
as demonstrated below.density_plot(f, (xmin,xmax), (ymin,ymax), ...)
INPUT:
f
– a function of two variables(xmin, xmax)
– 2-tuple, the range ofx
values OR 3-tuple(x,xmin,xmax)
(ymin, ymax)
– 2-tuple, the range ofy
values OR 3-tuple(y,ymin,ymax)
The following inputs must all be passed in as named parameters:
plot_points
– integer (default: 25); number of points to plot in each direction of the gridcmap
– a colormap (default:'gray'
), the name of a predefined colormap, a list of colors or an instance of a matplotlib Colormap. Type:import matplotlib.cm; matplotlib.cm.datad.keys()
for available colormap names.interpolation
– string (default:'catrom'
); the interpolation method to use:'bilinear'
,'bicubic'
,'spline16'
,'spline36'
,'quadric'
,'gaussian'
,'sinc'
,'bessel'
,'mitchell'
,'lanczos'
,'catrom'
,'hermite'
,'hanning'
,'hamming'
,'kaiser'
EXAMPLES:
Here we plot a simple function of two variables. Note that since the input function is an expression, we need to explicitly declare the variables in 3-tuples for the range:
sage: x,y = var('x,y') sage: density_plot(sin(x) * sin(y), (x,-2,2), (y,-2,2)) Graphics object consisting of 1 graphics primitive
>>> from sage.all import * >>> x,y = var('x,y') >>> density_plot(sin(x) * sin(y), (x,-Integer(2),Integer(2)), (y,-Integer(2),Integer(2))) Graphics object consisting of 1 graphics primitive
Here we change the ranges and add some options; note that here
f
is callable (has variables declared), so we can use 2-tuple ranges:sage: x,y = var('x,y') sage: f(x,y) = x^2 * cos(x*y) sage: density_plot(f, (x,-10,5), (y,-5,5), interpolation='sinc', plot_points=100) Graphics object consisting of 1 graphics primitive
>>> from sage.all import * >>> x,y = var('x,y') >>> __tmp__=var("x,y"); f = symbolic_expression(x**Integer(2) * cos(x*y)).function(x,y) >>> density_plot(f, (x,-Integer(10),Integer(5)), (y,-Integer(5),Integer(5)), interpolation='sinc', plot_points=Integer(100)) Graphics object consisting of 1 graphics primitive
An even more complicated plot:
sage: x,y = var('x,y') sage: density_plot(sin(x^2+y^2) * cos(x) * sin(y), (x,-4,4), (y,-4,4), cmap='jet', plot_points=100) Graphics object consisting of 1 graphics primitive
>>> from sage.all import * >>> x,y = var('x,y') >>> density_plot(sin(x**Integer(2)+y**Integer(2)) * cos(x) * sin(y), (x,-Integer(4),Integer(4)), (y,-Integer(4),Integer(4)), cmap='jet', plot_points=Integer(100)) Graphics object consisting of 1 graphics primitive
This should show a “spotlight” right on the origin:
sage: x,y = var('x,y') sage: density_plot(1/(x^10 + y^10), (x,-10,10), (y,-10,10)) Graphics object consisting of 1 graphics primitive
>>> from sage.all import * >>> x,y = var('x,y') >>> density_plot(Integer(1)/(x**Integer(10) + y**Integer(10)), (x,-Integer(10),Integer(10)), (y,-Integer(10),Integer(10))) Graphics object consisting of 1 graphics primitive
Some elliptic curves, but with symbolic endpoints. In the first example, the plot is rotated 90 degrees because we switch the variables \(x\), \(y\):
sage: density_plot(y^2 + 1 - x^3 - x, (y,-pi,pi), (x,-pi,pi)) Graphics object consisting of 1 graphics primitive
>>> from sage.all import * >>> density_plot(y**Integer(2) + Integer(1) - x**Integer(3) - x, (y,-pi,pi), (x,-pi,pi)) Graphics object consisting of 1 graphics primitive
sage: density_plot(y^2 + 1 - x^3 - x, (x,-pi,pi), (y,-pi,pi)) Graphics object consisting of 1 graphics primitive
>>> from sage.all import * >>> density_plot(y**Integer(2) + Integer(1) - x**Integer(3) - x, (x,-pi,pi), (y,-pi,pi)) Graphics object consisting of 1 graphics primitive
Extra options will get passed on to show(), as long as they are valid:
sage: density_plot(log(x) + log(y), (x,1,10), (y,1,10), aspect_ratio=1) Graphics object consisting of 1 graphics primitive
>>> from sage.all import * >>> density_plot(log(x) + log(y), (x,Integer(1),Integer(10)), (y,Integer(1),Integer(10)), aspect_ratio=Integer(1)) Graphics object consisting of 1 graphics primitive
sage: density_plot(log(x) + log(y), (x,1,10), (y,1,10)).show(aspect_ratio=1) # These are equivalent
>>> from sage.all import * >>> density_plot(log(x) + log(y), (x,Integer(1),Integer(10)), (y,Integer(1),Integer(10))).show(aspect_ratio=Integer(1)) # These are equivalent