Changes bayes plots to use mean reflectivity and SLD

Author: DrPaulSharp

RATapi/utils/plotting.py

@@ -1,5 +1,6 @@
 """Plots using the matplotlib library"""
 
+import copy
 from functools import partial, wraps
 from math import ceil, floor, sqrt
 from statistics import stdev
@@ -241,10 +242,11 @@ def plot_ref_sld(
     """
     data = PlotEventData()
 
+    # We need to take a copy of results and SLD in case the data to plot is modified later
     data.modelType = project.model
-    data.reflectivity = results.reflectivity
+    data.reflectivity = copy.deepcopy(results.reflectivity)
     data.shiftedData = results.shiftedData
-    data.sldProfiles = results.sldProfiles
+    data.sldProfiles = copy.deepcopy(results.sldProfiles)
     data.resampledLayers = results.resampledLayers
     data.dataPresent = RATapi.inputs.make_data_present(project)
     data.subRoughs = results.contrastParams.subRoughs
@@ -275,6 +277,12 @@ def plot_ref_sld(
                     for sld in results.predictionIntervals.sld
                 ],
             }
+            # For a shaded plot, use the mean values from predictionIntervals
+            for reflectivity, mean_reflectivity in zip(data.reflectivity, results.predictionIntervals.reflectivity):
+                reflectivity[:, 1] = mean_reflectivity[2]
+            for sldProfile, mean_sld_profile in zip(data.sldProfiles, results.predictionIntervals.sld):
+                for sld, mean_sld in zip(sldProfile, mean_sld_profile):
+                    sld[:, 1] = mean_sld[2]
         else:
             raise ValueError(
                 "Shaded confidence intervals are only available for the results of Bayesian analysis (NS or DREAM)"

cpp/rat.cpp

@@ -995,6 +995,18 @@ py::list pyList1DFromRatCellWrap2D(const T& values)
     return result;
 }
 
+template <typename T>
+py::list pyList1DFromRatCellWrap1D(const T& values)
+{
+    py::list result;
+
+    for (int32_T idx0{0}; idx0 < values.size(0); idx0++) {
+        result.append(pyArrayFromRatArray2d(values[idx0].f1));
+    }
+
+    return result;
+}
+
 template <typename T> 
 py::list pyList2dFromRatCellWrap(const T& values)
 {
@@ -1234,7 +1246,7 @@ BayesResults bayesResultsFromStruct9T(const RAT::struct9_T results)
 
     bayesResults.chain = pyArrayFromRatArray2d(results.chain);
 
-    bayesResults.predictionIntervals.reflectivity = pyList1DFromRatCellWrap2D<coder::array<RAT::cell_wrap_11, 1U>>(results.predictionIntervals.reflectivity);
+    bayesResults.predictionIntervals.reflectivity = pyList1DFromRatCellWrap1D<coder::array<RAT::cell_wrap_11, 1U>>(results.predictionIntervals.reflectivity);
     bayesResults.predictionIntervals.sld = pyList2dFromRatCellWrap<coder::array<RAT::cell_wrap_11, 2U>>(results.predictionIntervals.sld);
     bayesResults.predictionIntervals.sampleChi = pyArray1dFromBoundedArray<coder::bounded_array<real_T, 1000U, 1U>>(results.predictionIntervals.sampleChi);