Warning

The following sections describe advanced features that are not intended for the average user.

## Installing Plotting Plug-Ins¶

CellBlender supports a variety of plotting plug-ins that may be installed in the "data_plotters" folder under the cellblender addon folder (typically something like: ~/.config/blender/2.70/scripts/addons/cellblender/data_plotters). Each plotting plug-in will have its own folder in that directory, and within that folder must (at least) be a file named __init__.py. As an example, the xmgrace plug-in will be found at ~/.config/blender/2.70/scripts/addons/cellblender/data_plotters/xmgrace. There may be other files required in that folder. For example, the Java Plotter requires the file PlotData.jar to be there, and the matplotlib plotter requires the files mpl_plot.py and mpl_defaults.py. The number and purposes of these additional files depends completely on the plotting plug-in.

Installing a new plotting plug-in only requires the creation of a new directory in the data_plotters directory (the name can be whatever you feel is appropriate), and the installation of the associated files (which must include an __init__.py file.

Here's an example of a simple plotting plug-in for xmgrace:

import os
import subprocess

def find_in_path(program_name):
for path in os.environ.get('PATH','').split(os.pathsep):
full_name = os.path.join(path,program_name)
if os.path.exists(full_name) and not os.path.isdir(full_name):
return full_name
return None

def get_name():
return ( "XmGrace Plotter" )

def requirements_met():
path = find_in_path ( "xmgrace" )
if path == None:
return False
else:
return True

def plot ( data_path, plot_spec ):
program_path = os.path.dirname(__file__)

# XmGrace expects plain file names so translate:

plot_cmd = find_in_path ( "xmgrace" )

for plot_param in plot_spec.split():
if plot_param[0:2] == "f=":
plot_cmd = plot_cmd + " " + plot_param[2:]

pid = subprocess.Popen ( plot_cmd.split(), cwd=data_path )


Warning

This plotting api is still being developed and changes are expected!

## Writing Plotting Plug-Ins¶

CellBlender's plotting plug-in API is still very immature, so drastic changes may be anticipated. But for those who need to write their own plotting plug-in, the current specification is as follows...

Each plotting plug-in must have an __init__.py file containing the following functions:

• get_name()
• requirements_met()
• plot ( data_path, plot_spec )

These are described in separate sections below.

## get_name()¶

The get_name() function simply returns the name of this plug-in in the form of a normal python string. This is used for the user interface.

## requirements_met()¶

The requirements_met() function is called to determine if the operating environment meets the requirements for this plug-in to work. For example, if the plug-in is written in Java, then the requirements_met function should check to see that a suitable Java Virtual Machine is installed. This function returns True if the requirements are met, and false otherwise.

## plot ( data_path, plot_spec )¶

The plot() function actually performs the plot. The plot function takes two parameters:

• data_path - a path to where the data files exist (added to each file)
• plot_spec - a list of files and modifiers that describe the plotting

The data_path is fairly self-explanatory, but the plot_spec requires a little bit of explanation.

The fundamental plot specification is just a list of file names immediately prefixed with "f=" and separated by spaces:

f=mol1v1.dat f=mol1v2.dat f=mol1s1.dat f=mol2s1.dat


Every plotting plug-in should recognize the "f=" prefix as specifying the name of a file where the file itself contains two columns of numbers (time and count) in ASCII text format. As a minimum, the plug-in should be able to plot all such files in a single plot.

At this point, all additional parameters are optional ... but certainly useful!

Among the optional parameters are the separators "page" and "plot". These are inserted between file names to produce either a new page or a new plot. For example, the previous specification could plot the volume and surface molecules in two separate plots within the same page using this command:

f=mol1v1.dat f=mol1v2.dat plot f=mol1s1.dat f=mol2s1.dat


Alternatively, the the following command will put each of those plots on their own pages:

f=mol1v1.dat f=mol1v2.dat page f=mol1s1.dat f=mol2s1.dat


This command creates two pages and creates 2 plots on each page:

f=mol1v1.dat plot f=mol1v2.dat page f=mol1s1.dat plot f=mol2s1.dat


Finally, here is the current plotting plug-in API (SUBJECT TO CHANGE)

• defs=filename ... Loads default parameters from a python file
• page ... Starts a new page (figure in matplotlib)
• plot ... Starts a new plot (subplot in matplotlib)
• color=#rrggbb ... Selects a color via Red,Green,Blue values
• color=color_name ... Selects a color via standard color names
• title=title_string ... Sets the title for each plot
• pagetitle=string ... Sets the title for each page
• xlabel=label_string ... Sets the label for the x axis
• ylabel=label_string ... Sets the label for the y axis
• legend=code ... Adds a legend with code = 0..10 (-1=none)
• n=name ... Name used to over-ride file name in legend
• f=filename ... Plots the file with current settings