matplotlib.pyplot.contour — Matplotlib 3.10.1 documentation (original) (raw)
matplotlib.pyplot.contour(*args, data=None, **kwargs)[source]#
Plot contour lines.
Call signature:
contour([X, Y,] Z, /, [levels], **kwargs)
The arguments X, Y, Z are positional-only.
contour and contourf draw contour lines and filled contours, respectively. Except as noted, function signatures and return values are the same for both versions.
Parameters:
X, Yarray-like, optional
The coordinates of the values in Z.
X and Y must both be 2D with the same shape as Z (e.g. created via numpy.meshgrid), or they must both be 1-D such that len(X) == N is the number of columns in Z andlen(Y) == M is the number of rows in Z.
X and Y must both be ordered monotonically.
If not given, they are assumed to be integer indices, i.e.X = range(N), Y = range(M).
Z(M, N) array-like
The height values over which the contour is drawn. Color-mapping is controlled by cmap, norm, vmin, and vmax.
levelsint or array-like, optional
Determines the number and positions of the contour lines / regions.
If an int n, use MaxNLocator, which tries to automatically choose no more than n+1 "nice" contour levels between minimum and maximum numeric values of Z.
If array-like, draw contour lines at the specified levels. The values must be in increasing order.
Returns:
Other Parameters:
corner_maskbool, default: [rcParams["contour.corner_mask"]](../../users/explain/customizing.html?highlight=contour.corner%5Fmask#matplotlibrc-sample) (default: True)
Enable/disable corner masking, which only has an effect if Z is a masked array. If False, any quad touching a masked point is masked out. If True, only the triangular corners of quads nearest those points are always masked out, other triangular corners comprising three unmasked points are contoured as usual.
colorscolor or list of color, optional
The colors of the levels, i.e. the lines for contour and the areas for contourf.
The sequence is cycled for the levels in ascending order. If the sequence is shorter than the number of levels, it's repeated.
As a shortcut, a single color may be used in place of one-element lists, i.e.'red' instead of ['red'] to color all levels with the same color.
Changed in version 3.10: Previously a single color had to be expressed as a string, but now any valid color format may be passed.
By default (value None), the colormap specified by _cmap_will be used.
alphafloat, default: 1
The alpha blending value, between 0 (transparent) and 1 (opaque).
cmapstr or Colormap, default: [rcParams["image.cmap"]](../../users/explain/customizing.html?highlight=image.cmap#matplotlibrc-sample) (default: 'viridis')
The Colormap instance or registered colormap name used to map scalar data to colors.
This parameter is ignored if colors is set.
normstr or Normalize, optional
The normalization method used to scale scalar data to the [0, 1] range before mapping to colors using cmap. By default, a linear scaling is used, mapping the lowest value to 0 and the highest to 1.
If given, this can be one of the following:
- An instance of Normalize or one of its subclasses (see Colormap normalization).
- A scale name, i.e. one of "linear", "log", "symlog", "logit", etc. For a list of available scales, call matplotlib.scale.get_scale_names(). In that case, a suitable Normalize subclass is dynamically generated and instantiated.
This parameter is ignored if colors is set.
vmin, vmaxfloat, optional
When using scalar data and no explicit norm, vmin and vmax define the data range that the colormap covers. By default, the colormap covers the complete value range of the supplied data. It is an error to use_vmin_/vmax when a norm instance is given (but using a str _norm_name together with vmin/vmax is acceptable).
If vmin or vmax are not given, the default color scaling is based on_levels_.
This parameter is ignored if colors is set.
colorizerColorizer or None, default: None
The Colorizer object used to map color to data. If None, a Colorizer object is created from a norm and cmap.
This parameter is ignored if colors is set.
origin{None, 'upper', 'lower', 'image'}, default: None
Determines the orientation and exact position of Z by specifying the position of Z[0, 0]. This is only relevant, if X, _Y_are not given.
- None:
Z[0, 0]is at X=0, Y=0 in the lower left corner. - 'lower':
Z[0, 0]is at X=0.5, Y=0.5 in the lower left corner. - 'upper':
Z[0, 0]is at X=N+0.5, Y=0.5 in the upper left corner. - 'image': Use the value from
[rcParams["image.origin"]](../../users/explain/customizing.html?highlight=image.origin#matplotlibrc-sample)(default:'upper').
extent(x0, x1, y0, y1), optional
If origin is not None, then extent is interpreted as inimshow: it gives the outer pixel boundaries. In this case, the position of Z[0, 0] is the center of the pixel, not a corner. If_origin_ is None, then (x0, y0) is the position of Z[0, 0], and (x1, y1) is the position of Z[-1, -1].
This argument is ignored if X and Y are specified in the call to contour.
locatorticker.Locator subclass, optional
The locator is used to determine the contour levels if they are not given explicitly via levels. Defaults to MaxNLocator.
extend{'neither', 'both', 'min', 'max'}, default: 'neither'
Determines the contourf-coloring of values that are outside the_levels_ range.
If 'neither', values outside the levels range are not colored. If 'min', 'max' or 'both', color the values below, above or below and above the levels range.
Values below min(levels) and above max(levels) are mapped to the under/over values of the Colormap. Note that most colormaps do not have dedicated colors for these by default, so that the over and under values are the edge values of the colormap. You may want to set these values explicitly usingColormap.set_under and Colormap.set_over.
Note
An existing QuadContourSet does not get notified if properties of its colormap are changed. Therefore, an explicit call changed() is needed after modifying the colormap. The explicit call can be left out, if a colorbar is assigned to the QuadContourSet because it internally callschanged().
Example:
x = np.arange(1, 10) y = x.reshape(-1, 1) h = x * y
cs = plt.contourf(h, levels=[10, 30, 50], colors=['#808080', '#A0A0A0', '#C0C0C0'], extend='both') cs.cmap.set_over('red') cs.cmap.set_under('blue') cs.changed()
xunits, yunitsregistered units, optional
Override axis units by specifying an instance of amatplotlib.units.ConversionInterface.
antialiasedbool, optional
Enable antialiasing, overriding the defaults. For filled contours, the default is False. For line contours, it is taken from [rcParams["lines.antialiased"]](../../users/explain/customizing.html?highlight=lines.antialiased#matplotlibrc-sample) (default: True).
nchunkint >= 0, optional
If 0, no subdivision of the domain. Specify a positive integer to divide the domain into subdomains of nchunk by nchunk quads. Chunking reduces the maximum length of polygons generated by the contouring algorithm which reduces the rendering workload passed on to the backend and also requires slightly less RAM. It can however introduce rendering artifacts at chunk boundaries depending on the backend, the antialiased flag and value of alpha.
linewidthsfloat or array-like, default: [rcParams["contour.linewidth"]](../../users/explain/customizing.html?highlight=contour.linewidth#matplotlibrc-sample) (default: None)
Only applies to contour.
The line width of the contour lines.
If a number, all levels will be plotted with this linewidth.
If a sequence, the levels in ascending order will be plotted with the linewidths in the order specified.
If None, this falls back to [rcParams["lines.linewidth"]](../../users/explain/customizing.html?highlight=lines.linewidth#matplotlibrc-sample) (default: 1.5).
linestyles{None, 'solid', 'dashed', 'dashdot', 'dotted'}, optional
Only applies to contour.
If linestyles is None, the default is 'solid' unless the lines are monochrome. In that case, negative contours will instead take their linestyle from the negative_linestyles argument.
linestyles can also be an iterable of the above strings specifying a set of linestyles to be used. If this iterable is shorter than the number of contour levels it will be repeated as necessary.
negative_linestyles{None, 'solid', 'dashed', 'dashdot', 'dotted'}, optional
Only applies to contour.
If linestyles is None and the lines are monochrome, this argument specifies the line style for negative contours.
If negative_linestyles is None, the default is taken from[rcParams["contour.negative_linestyle"]](../../users/explain/customizing.html?highlight=contour.negative%5Flinestyle#matplotlibrc-sample) (default: 'dashed').
negative_linestyles can also be an iterable of the above strings specifying a set of linestyles to be used. If this iterable is shorter than the number of contour levels it will be repeated as necessary.
hatcheslist[str], optional
Only applies to contourf.
A list of cross hatch patterns to use on the filled areas. If None, no hatching will be added to the contour.
algorithm{'mpl2005', 'mpl2014', 'serial', 'threaded'}, optional
Which contouring algorithm to use to calculate the contour lines and polygons. The algorithms are implemented inContourPy, consult theContourPy documentation for further information.
The default is taken from [rcParams["contour.algorithm"]](../../users/explain/customizing.html?highlight=contour.algorithm#matplotlibrc-sample) (default: 'mpl2014').
clip_pathPatch or Path or TransformedPath
Set the clip path. See set_clip_path.
Added in version 3.8.
dataindexable object, optional
If given, all parameters also accept a string s, which is interpreted as data[s] if s is a key in data.
Notes
- contourf differs from the MATLAB version in that it does not draw the polygon edges. To draw edges, add line contours with calls tocontour.
- contourf fills intervals that are closed at the top; that is, for boundaries z1 and z2, the filled region is:
except for the lowest interval, which is closed on both sides (i.e. it includes the lowest value). - contour and contourf use a marching squares algorithm to compute contour locations. More information can be found inContourPy documentation.