Merge pull request #24 from VirtualPhotonics/feature/23-create-a-separate-function-for-heat-map-so-it-can-be-referenced-from-multiple-places

Author: lmalenfant

.gitignore

@@ -1 +1,3 @@
 **/.ipynb_checkpoints/
+**/__pycache__/
+libraries/

forward-solvers/fluence-of-rho-and-z-two-layer.py

@@ -11,11 +11,13 @@
 import clr
 # Import the Operating System so we can access the files for the VTS library
 import os
+import sys
+module_path = '../modules'
+sys.path.append(module_path)
 file = '../libraries/Vts.dll'
 clr.AddReference(os.path.abspath(file))
 import numpy as np
 import plotly.graph_objects as go
-import plotly.express as px
 from Vts import *
 from Vts.Common import *
 from Vts.Extensions import *
@@ -30,9 +32,8 @@
 from Vts.MonteCarlo.Factories import *
 from Vts.MonteCarlo.PhotonData import *
 from Vts.MonteCarlo.PostProcessing import *
-from System import Array, Double, Object, Func, Math
-clr.AddReference("System.Core")
-from System.Linq import Enumerable
+from System import Array, Double, Math
+from graph_tools import heatmap
 
 solver = TwoLayerSDAForwardSolver()
 solver.SourceConfiguration = SourceConfiguration.Distributed
@@ -75,26 +76,6 @@
 # reverse and concatenate
 allFluenceRowsToPlot = np.concatenate((fluenceRowsToPlot[::-1], fluenceRowsToPlot))
 
-# Heatmap function to convert the data into a heat map
-def heatmap(values, x, y, x_label="", y_label="", title=""):
-    """Create a heatmap chart."""
-    # values should be a 2D array-like (list of lists or 2D numpy array)
-    fig = go.Figure(data=go.Heatmap(
-        z=values,
-        x=x,
-        y=y,
-        transpose=True,
-        colorscale='Hot',
-        colorbar=dict(title=title)
-    ))
-    fig.update_layout(
-        title=title,
-        xaxis_title=x_label,
-        yaxis_title=y_label,
-        yaxis_autorange='reversed'
-    )
-    return fig
-
 fluenceChart = heatmap(allFluenceRowsToPlot.tolist(), allRhos.tolist(), list(zs), "ρ [mm]", "z [mm]", "log(Φ(ρ, z) [mm-2])")
 fluenceChart.add_hline(y=topLayerThickness, line_dash="dash", line_color="white", line_width=2)
 fluenceChart.show(renderer="browser")

forward-solvers/phd-of-rho-and-z-compute-fluence.py

@@ -9,11 +9,13 @@
 import clr
 # Import the Operating System so we can access the files for the VTS library
 import os
+import sys
+module_path = '../modules'
+sys.path.append(module_path)
 file = '../libraries/Vts.dll'
 clr.AddReference(os.path.abspath(file))
 import numpy as np
 import plotly.graph_objects as go
-import plotly.express as px
 from Vts import *
 from Vts.Common import *
 from Vts.Extensions import *
@@ -28,9 +30,8 @@
 from Vts.MonteCarlo.Factories import *
 from Vts.MonteCarlo.PhotonData import *
 from Vts.MonteCarlo.PostProcessing import *
-from System import Array, Double, Object, Func, Math
-clr.AddReference("System.Core")
-from System.Linq import Enumerable
+from System import Array, Double, Math
+from graph_tools import heatmap
 
 solver = DistributedPointSourceSDAForwardSolver()
 
@@ -83,25 +84,5 @@
 # split into rows
 phdRowsToPlot = np.array([log_phd[i:i+size] for i in range(0, len(log_phd), size)])
 
-# Heatmap function to convert the data into a heat map
-def heatmap(values, x, y, x_label="", y_label="", title=""):
-    """Create a heatmap chart."""
-    # values should be a 2D array-like (list of lists or 2D numpy array)
-    fig = go.Figure(data=go.Heatmap(
-        z=values,
-        x=x,
-        y=y,
-        transpose=True,
-        colorscale='Hot',
-        colorbar=dict(title=title)
-    ))
-    fig.update_layout(
-        title=title,
-        xaxis_title=x_label,
-        yaxis_title=y_label,
-        yaxis_autorange='reversed'
-    )
-    return fig
-
 fluenceChart = heatmap(phdRowsToPlot.tolist(), allRhos.tolist(), list(zs), "ρ [mm]", "z [mm]", "log(phd(ρ, z) [mm-2])")
 fluenceChart.show(renderer="browser")

forward-solvers/phd-of-rho-and-z-two-layer.py

@@ -9,11 +9,13 @@
 import clr
 # Import the Operating System so we can access the files for the VTS library
 import os
+import sys
+module_path = '../modules'
+sys.path.append(module_path)
 file = '../libraries/Vts.dll'
 clr.AddReference(os.path.abspath(file))
 import numpy as np
 import plotly.graph_objects as go
-import plotly.express as px
 from Vts import *
 from Vts.Common import *
 from Vts.Extensions import *
@@ -28,9 +30,8 @@
 from Vts.MonteCarlo.Factories import *
 from Vts.MonteCarlo.PhotonData import *
 from Vts.MonteCarlo.PostProcessing import *
-from System import Array, Double, Object, Func, Math
-clr.AddReference("System.Core")
-from System.Linq import Enumerable
+from System import Array, Double, Math
+from graph_tools import heatmap
 
 solver = TwoLayerSDAForwardSolver()
 solver.SourceConfiguration = SourceConfiguration.Distributed
@@ -77,26 +78,6 @@
 # split into rows
 fluenceRowsToPlot = np.array([log_fluence[i:i+size] for i in range(0, len(log_fluence), size)])
 
-# Heatmap function to convert the data into a heat map
-def heatmap(values, x, y, x_label="", y_label="", title=""):
-    """Create a heatmap chart."""
-    # values should be a 2D array-like (list of lists or 2D numpy array)
-    fig = go.Figure(data=go.Heatmap(
-        z=values,
-        x=x,
-        y=y,
-        transpose=True,
-        colorscale='Hot',
-        colorbar=dict(title=title)
-    ))
-    fig.update_layout(
-        title=title,
-        xaxis_title=x_label,
-        yaxis_title=y_label,
-        yaxis_autorange='reversed'
-    )
-    return fig
-
 fluenceChart = heatmap(fluenceRowsToPlot.tolist(), allRhos.tolist(), list(zs), "ρ [mm]", "z [mm]", "log(phd(ρ, z) [mm-2])")
 fluenceChart.add_hline(y=topLayerThickness, line_dash="dash", line_color="white", line_width=2)
 fluenceChart.show(renderer="browser")

forward-solvers/readme.txt

@@ -1,6 +1,6 @@
 ## The MIT License (MIT)
 
-#### Copyright (c) 2023 Virtual Photonics Technology Initiative
+#### Copyright (c) 2025 Virtual Photonics Technology Initiative
 
 ### Acknowledgement
 Use the following acknowledgement in publications or applications that make use of this open source software or underlying technology and research:

inverse-solutions/readme.txt

@@ -0,0 +1,21 @@
+import plotly.graph_objects as go
+
+# Heatmap function to convert the data into a heat map
+def heatmap(values, x, y, x_label="", y_label="", title=""):
+    """Create a heatmap chart."""
+    # values should be a 2D array-like (list of lists or 2D numpy array)
+    fig = go.Figure(data=go.Heatmap(
+        z=values,
+        x=x,
+        y=y,
+        transpose=True,
+        colorscale='Hot',
+        colorbar=dict(title=title)
+    ))
+    fig.update_layout(
+        title=title,
+        xaxis_title=x_label,
+        yaxis_title=y_label,
+        yaxis_autorange='reversed'
+    )
+    return fig

license.md

@@ -1,9 +1,9 @@
 {
     "runtimeOptions": {
-      "tfm": "net6.0",
+      "tfm": "net8.0",
       "framework": {
         "name": "Microsoft.NETCore.App",
-        "version": "6.0.0"
+        "version": "8.0.0"
       },
       "configProperties": {
         "System.GC.Server": true