Moved the heatmap function into a separate file, added the libraries and the pycache folders to the .gitignore

Author: lmalenfant

.gitignore

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

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

@@ -15,7 +15,6 @@
 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 +29,8 @@
 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 +73,6 @@
 # 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/graph_tools.py

@@ -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

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

@@ -13,7 +13,6 @@
 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 +27,8 @@
 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 +81,5 @@
 # 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

@@ -13,7 +13,6 @@
 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 +27,8 @@
 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 +75,6 @@
 # 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 +1 @@
-This folder will contain the Forward Solver demos.
+This folder contains the Forward Solver demos.