Image.contour#

ContourManager.contour(var: ndarray[tuple[Any, ...], dtype[generic]], check: bool = True, **kwargs: Any) → QuadContourSet[source]#

Plot a contour plot of a given variable.

The function uses the matplotlib.pyplot.contour function. The function returns None.

Parameters:

- alpha: float, default 1.0: Sets the transparency of the contour lines.
- aspect: {‘auto’, ‘equal’, float}, default ‘auto’: Sets the aspect ratio of the plot. The ‘auto’ keyword is the default option (most likely the plot will be squared). The ‘equal’ keyword will set the same scaling for x and y. A float will fix the ratio between the y-scale and the x-scale (1.0 is the same as ‘equal’).
- ax: {ax object, ‘old’, None}, default None: The axis where to plot the lines. If None, a new axis is created. If ‘old’, the last considered axis will be used.
- c: str, default self.color: Determines the contour lines plot. If not defined, the program will loop over an array of 6 color which are different for the most common vision deficiencies.
- cmap: str, default ‘hot’: Selects the colormap. If not defined, the colormap ‘hot’ will be adopted. Some useful colormaps are: plasma, magma, seismic. Please avoid using colorbars like jjet or rainbow, which are not perceptively uniform and not suited for people with vision deficiencies.
- cpos: {‘top’,’bottom’,’left’,’right’}, default None: Enables the colorbar (if defined), default position on the right.
- cscale: {‘linear’,’log’,’symlog’,’twoslope’}, default ‘linear’: Sets the colorbar scale. Default is the linear (‘norm’) scale.
- extend: {‘neither’,’both’,’min’,’max’}, default ‘neither’: Sets the extension of the triangular colorbar extension.
- extendrect: bool, default False: If True, the colorbar extension will be rectangular.
- fontsize: float, default 17.0: Sets the fontsize for all the axis components (only for the current axis).
- grid: bool, default False: Enables/disables the grid on the plot.
- labelsize: float, default fontsize: Sets the labels fontsize (which is the same for both labels). The default value corresponds to the value of the keyword ‘fontsize’.
- levels: np.ndarray: The levels of the contour lines.
- minorticks: str, default None: If not None enables the minor ticks on the plot (for both grid axes).
- sharex: Matplotlib axis | False, default False: Shares the x-axis with another axis.
- sharey: Matplotlib axis | False, default False: Shares the y-axis with another axis.
- ticksdir: {‘in’, ‘out’}, default ‘in’: Sets the ticks direction. The default option is ‘in’.
- tickssize: float | bool, default True: Sets the ticks fontsize (which is the same for both grid axes). The default value corresponds to the value of the keyword ‘fontsize’.
- title: str, default None: Places the title of the plot on top of it.
- titlepad: float, default 8.0: Sets the distance between the title and the top of the plot
- titlesize: float, default fontsize: Sets the title fontsize. The default value corresponds to the value of the keyword ‘fontsize’.
- transpose: True/False, default False: Transposes the variable matrix. Use is not recommended if not really necessary (e.g. in case of highly customized variables and plots).
- tresh: float, default max(abs(vmin),vmax)*0.01: Sets the threshold for the colormap. If not defined, the threshold will be set to 1% of the maximum absolute value of the variable. The default cases are the following: - twoslope colorscale: sets the limit between the two linear regimes. - symlog: sets the limit between the logaitrhmic and the linear regime.
- var (not optional): np.ndarray: The variable to be plotted.
- vmax: float: The maximum value of the colormap.
- vmin: float: The minimum value of the colormap.
- x1: 1D array, default ‘Default’: The ‘x’ array.
- x2: 1D array, default ‘Default’: The ‘y’ array.
- xrange: [float, float], default [0,1]: Sets the range in the x-direction. If not defined the code will compute the range while plotting the data.
- xscale: {‘linear’,’log’}, default ‘linear’: If enabled (and different from True), sets automatically the scale on the x-axis. Data in log scale should be used with the keyword ‘log’, while data in linear scale should be used with the keyword ‘linear’.
- xticks: {[float], None, True}, default True: If enabled (and different from True), sets manually ticks on x-axis. In order to completely remove the ticks the keyword should be used with None.
- xtickslabels: {[str], None, True}, default True: If enabled (and different from True), sets manually the ticks labels on the x-axis. In order to completely remove the ticks the keyword should be used with None. Note that fixed tickslabels should always correspond to fixed ticks.
- xtitle: str, default None: Sets and places the label of the x-axis.
- yrange: [float, float], default [0,1]: Sets the range in the y-direction. If not defined the code will compute the range while plotting the data.
- yscale: {‘linear’,’log’}, default ‘linear’: If enabled (and different from True), sets automatically the scale on the y-axis. Data in log scale should be used with the keyword ‘log’, while data in linear scale should be used with the keyword ‘linear’.
- yticks: {[float], None, True}, default True: If enabled (and different from True), sets manually ticks on y-axis. In order to completely remove the ticks the keyword should be used with None.
- ytickslabels: {[str], None, True}, default True: If enabled (and different from True), sets manually the ticks labels on the y-axis. In order to completely remove the ticks the keyword should be used with None. Note that fixed tickslabels should always correspond to fixed ticks.
- ytitle: str, default None: Sets and places the label of the y-axis.
—-

Returns:

cnt: LineCollection
The set of contour lines of the given variable.

Examples

Example #1: Plot a contour plot of a variable
```
>>> I.contour(D.rho, levels=10)
```