Plotting#
The loaded data should be visualized in a complete yet efficient way. The Image class is a quick tool in order to obtain simple plots suitable for scientific articles.
For the sake of simplicity, every Image class corresponds to one single figure. The reason behind such choice is that an Image including multiple figures would not be efficient in order to effectively remember where all the potential subplots are located.
Subplots creation and customization#
The first step of the plotting procedure is to create a list of axes (where each element of the axes list corresponds to a subplot). Two functions are built in order to give a good compromise between simplicity and customization:
The create_axes method creates a simple figure and set of axes, given a specific number of rows and columns. The subplots are automatically spaced evenly and the ratio between the different subplots sizes is 1. The aspect of the single subplots is automatically determined from the image size.
The create_axes method allows for a better customization, since both the size ratios of the plots and the horizontal and vertical spacing are customizable. Moreover, this function is designed to be called multiple times for the same figure (e.g. in case of plots which span over a different number of columns).
Once the figure and the axes are created, they are customizable through the set_axis method.
Parameters as the axes range or scale should be defined here. However, in case of simple plots all the parameters in this function can be defined in the specific plotting functions.
The plotting procedure#
At the moment only 1D and 2D plots are available, for both fluid and particles.
Note
Full 3D plotting is under active development.
The standard 1D and 2D fluid plots can be produced through the functions plot and display. Both functions are highly customizable and call the set_axis method. The particles can be plotted through the scatter method, which is also very customizable due to the call to the set_axis method.
Field and contour lines#
The Image class contains a contour and a streamplot methods, which can be used for a quick visualization of contour and field lines. Such methods are based on the contour and streamplot maptlotlib methods. Note that field and contour lines can be also produced in the Load class for a more accurate computation. Nonetheless, these methods require a limited computational time, favoring a quick visualization in absence of complex structures.
Interactive plots#
A quick interactive visualization is possible due to the interactive methods, which is available for both 1D and 2D fluid output files.
Note
In the future a better customization will be possible (e.g. displays with field lines through callable functions).
Figures plotted interactively can be visualized through the entire temporal evolution, with a high parameters customization provided by the plot and display methods (called be the interactive method). Interactive plots can be saved through the animate method, which can create or save a video, showing the output with a selected temporal interval. If no file name is provided, the animate will show a video.
Useful plotting tools#
Although features such as the legend or colorbar can be easily included during the plotting procedure, sometimes the best choice (especially for non-trivial figures) is to add them during a later step. However, multiple legends and colorbars are possible within the same figure.
The PyPLUTO module allows for easy inset zooms through the zoom for both 1D and 2D plots with the same level of customization of the functions plot and display. Note that, for the zoom of 2D variables, an additional customization level is possible; in fact, the zoom of a different quantities can be easily plotted in order to see two variables of a selected region at the same time with minimum effort.
Image figures can be saved through the savefig method, which is a simple wrapper of the matplotlib savefig method.
Text can be written within a figure through the text method. Depending on the user’s choice, the text can be placed in different font size, color and position (relative to the figure, axes points or fraction).
AMR blocks#
AMR blocks can be visualized through the oplotbox method, although, due to the ongoing upgrades to the AMR in gPLUTO and its output, such method may change in the future.