Adding and managing extra fields for visualization purposes¶

Quite often in your simulation you will want to label cells using scalar field, vector fields or simply create your own scalar or vector fields which are fully managed by you from the Python level. CC3D allows you to create four kinds of fields:

1. Scalar Field – to display scalar quantities associated with single pixels
2. Cell Level Scalar Field – to display scalar quantities associated with cells
3. Vector Field - to display vector quantities associated with single pixels
4. Cell Level Vector Field - to display vector quantities associated with cells

You can take look at CompuCellPythonTutorial/ExtraFields to see an example of a simulation that uses all four kinds of fields. The Python syntax used to create and manipulate custom fields is relatively simple but quite hard to memorize. Fortunately Twedit++ has CC3DPython->Extra Fields menu that inserts code snippets to create/manage fields.

Scalar Field – pixel based¶

Let’s look at the steppable that creates and manipulates scalar cell field. This field is implemented as Numpy float array and you can use Numpy functions to manipulate this field.

from math import *

class ExtraFieldVisualizationSteppable(SteppableBasePy):
def __init__(self, _simulator, _frequency=10):
SteppableBasePy.__init__(self, _simulator, _frequency)
self.scalarField = CompuCellSetup.createScalarFieldPy(self.dim, "ExtraField")

def step(self, mcs):

self.scalarField[:, :, :] = 0.0  # clear field

for x in xrange(self.dim.x):
for y in xrange(self.dim.y):
for z in xrange(self.dim.z):

if (not mcs % 20):
self.scalarField[x, y, z] = x * y

else:
self.scalarField[x, y, z] = sin(x * y)


The scalar field (we called it ExtraField) is created in the __init__ function of the steppable using

self.createScalarFieldPy(self.dim,"ExtraField").


Important: Make sure that all calls to functions creating fields are in the __init__ functions so that the Player can display them correctly.

In the step function we initialize self.scalarField using slicing operation:

self.scalarField[:, :, :]


In Python slicing convention, a single colon means all indices – here we put three colons for each axis which is equivalent to selecting all pixels.

Following lines in the step functions iterate over every pixel in the simulation and if MCS is divisible by 20 then self.scalarField is initialized with x*y value if MCS is not divisible by 20 than we initialize scalar field with sin(x*y) function. Notice, that we imported all functions from the math Python module so that we can get sin function to work.

SteppableBasePy has convenience function called self.everyPixel (CC3D Python->Visit->All Lattice Pixels) which allows us to compact triple loop to just one line:

for x,y,z in self.everyPixel():
if (not mcs%20):
self.scalarField[x,y,z]=x*y
else:
self.scalarField[x,y,z]=sin(x*y)


If we would like to iterate over x axis indices with step 5, over y indices with step 10 and over z axis indices with step 4 we would replace first line in the above snippet with.

for x,y,z in self.everyPixel(5,10,4):


You can still use triple loops if you like but shorter syntax leads to a cleaner code.

Vector Field – pixel based¶

By analogy to pixel based scalar field we can create vector field. Let’s look at the example code:

class VectorFieldVisualizationSteppable(SteppableBasePy):
def __init__(self, _simulator, _frequency=10):
SteppableBasePy.__init__(self, _simulator, _frequency)
self.vectorField = self.createVectorFieldPy("VectorField")

def step(self, mcs):
self.vectorField[:, :, :, :] = 0.0  # clear vector field

for x, y, z in self.everyPixel(10, 10, 5):
self.vectorField[x, y, z] = [x * random(), y * random(), z * random()]


Th code is very similar to the previous steppable. In the __init__ function we create pixel based vector field , in the step function we initialize it first to with zero vectors and later we iterate over pixels using steps 10, 10, 5 for x, y, z axes respectively and to these select lattice pixels we assign [x*random(), y*random(), z*random()] vector. Internally, self.vectorField is implemented as Numpy array:

np.zeros(shape=(_dim.x, _dim.y, _dim.z,3), dtype=np.float32)


Scalar Field – cell level¶

Pixel based fields are appropriate for situations where we want to assign scalar of vector to particular lattice locations. If, on the other hand, we want to label cells with a scalar or a vector we need to use cell level field (scalar or vector). It is still possible to use pixel-based fields but we assure you that the code you would write would be ver ugly at best.

Internally cell-based scalar field is implemented as a map or a dictionary indexed by cell id (although in Python instead of passing cell id we pass cell object to make syntax cleaner). Let us look at an example code:

class IdFieldVisualizationSteppable(SteppableBasePy):
def __init__(self,_simulator,_frequency=10):
SteppableBasePy.__init__(self,_simulator,_frequency)
self.scalarCLField=self.createScalarFieldCellLevelPy("IdField")

def step(self,mcs):
self.scalarCLField.clear()
for cell in self.cellList:
self.scalarCLField[cell]=cell.id*random()


As it was the case with other fields we create cell level scalar field in the __init__ function using self.createScalarFieldCellLevelPy. In the step function we first clear the field – this simply removes all entries from the dictionary. If you forget to clean dictionary before putting new values you may end up with stray values from the previous step. Inside the loop over all cells we assign random value to each cell. When we plot IdField in the player we will see that cells have different color labels. If we used pixel-based field to accomplish same task we would have to manually assign same value to all pixels belonging to a given cell. Using cell level fields we save ourselves a lot of work and make code more readable.

Vector Field – cell level¶

We can also associate vectors with cells. The code below is analogous to the previous example:

Inside __init__ function we create cell-level vector field using self.createVectorFieldCellLevelPy function. In the step function we clear field and then iterate over all cells and assign random vector to each cell. When we plot this field on top cell borders you will see that vectors are anchored in “cells’ corners” and not at the COM. This is because such rendering is faster.

You should remember that all those 4 kinds of field discussed here are for display purposes only. They do not participate in any calculations done by C++ core code and there is no easy way to pass values of those fields to the CC3D computational core.