Fluence¶

Fluence detector is used to obtain the spatial distribution of the energy (packet weights) deposited into the sample through the process of absorption or optionally the fluence rate. Three different implementations of the fluence detector are available in the xopto.mcbase.mcfluence module:

FluenceRz - Radially symmetric implementation $(r, z)$ .
FluenceCyl - Implementation in cylindrical coordinates $(r, \varphi, z)$ .
Fluence - Implementation in Cartesian coordinates $(x, y, z)$ .

The following are time-resolved variants of the above fluence detectors:

FluenceRzt - Implementation in Cartesian coordinates wit additional temporal axis $(x, y, z, t)$ .
FluenceCylt - Implementation in Cartesian coordinates wit additional temporal axis $(x, y, z, t)$ .
Fluencet - Implementation in Cartesian coordinates wit additional temporal axis $(x, y, z, t)$ .

The observed volume voxelization is axis-aligned and allows independent adjustment of the voxel size along the x, y and z axis for Fluence, along r, φ and z axis for . FluenceCyl and along the r and z axis for FluenceRz. The time-resolved variants of the fluence detectors have an additional temporal (t) axis. The time along the temporal axis is measured in seconds.

The fluence accumulators utilize NumPy arrays and follow C-indexing order, where the last index represents the most rapidly changing memory location:

FluenceRz - [z, r]
FluenceCyl - [z, φ, r]
Fluence - [z, y, x]
FluenceRzt - [z, r, t]
FluenceCylt - [z, φ, r, t]
Fluencet - [z, y, x, t]

The Fluence, Fluencet, FluenceCyl, FluenceCylt, FluenceRz and FluenceRzt classes are also conveniently imported into the xopto.mcml.mcfluence, xopto.mccyl.mcfluence xopto.mcvox.mcfluence modules.

The fluence detector allows collection of unscaled deposited / absorbed packet weights or of the fluence rate where the deposited packet weights are scaled by the inverse of the absorption coefficient. The collection method can be selected through the mode argument that should be set to ‘deposition’ (default) for the raw weights and ‘fluence’ for the fluence rate.

In the following example we voxelize a volume that extends along the x axis from -5 to 5 mm, along the y axis from -5 to 5 mm and along the z axis from 0 to 10 mm. The voxel size along all the three axis is set to 0.1 mm.

from xopto.mcml import mc

fluence = mc.mcfluence.Fluence(
    xaxis=mc.mcfluence.Axis(-5.0e-3, 5.0e-3, 100),
    yaxis=mc.mcfluence.Axis(-5.0e-3, 5.0e-3, 100),
    zaxis=mc.mcfluence.Axis(0.0, 10.0e-3, 100)
)

The Axis instances along the x, y and z axis can be accessed through the xaxis, yaxis and zaxis properties. Likewise, the centers of the voxels along the x, y and z axis can be accessed through the x, y and z properties.

xaxis = fluence.xaxis
yaxis = fluence.yaxis
zaxis = fluence.zaxis

x_centers = fluence.x    # or as xaxis.centers
y_centers = fluence.y    # or as yaxis.centers
z_centers = fluence.z    # or as zaxis.centers

The fluence data are stored in a 3D numpy array that can be accessed through the raw or data properties. The individual voxels are addressed / sliced as data[z_slice, y_slice, x_slice].

Note

The values returned by the raw property are the unscaled sums of deposited / absorbed photon packet weights while the values returned by the data property are scaled by the inverse of the product between the voxel volume and the number of launched packets. The time-resolved variants of fluence detectors scale the values returned by data with the inverse of the product between the voxel volume, the number of launched packets and the corresponding time interval. Also note that the voxel size is constant for the Fluence but changes with location for the FluenceRz and FluenceCyl.

After completing the Monte Carlo simulation, the fluence accumulator can be viewed using the plot() method. The method allows slicing across the voxelized volume along one of the main coordinate axis. Use the axis parameter to set the coordinate axis:

axis=’x’ slice along the x axis,
axis=’y’ slice along the y axis,
axis=’z’ slice along the z axis.

To show integral projections along one of the main coordinate axis call with:

axis=’xproj’ for an integral projection along the x axis,
axis=yproj for an integral projection along the y axis,
axis=’zproj’ for an integral projection along the z axis.

The slices can be viewed in a linear or logarithmic scale. Call with scale=’lin’ to show the slices in a linear intensity scale. By default the color coding of each slice is automatically scaled to the range of weights (autoscale=True).

fluence.plot(axis='z')    # slice along the z axis
fluence.plot(axis='y')    # slice along the y axis
fluence.plot(axis='x')    # slice along the x axis

fluence.plot(axis='zproj')    # integral projection / sum along the z axis
fluence.plot(axis='yproj')    # integral projection / sum along the y axis
fluence.plot(axis='xproj')    # integral projection / sum along the x axis