Merge pull request #3 from WISDEM/dev

Dev

.gitignore

@@ -129,4 +129,8 @@ dmypy.json
 .pyre/
 *.csv
 *.fem
-*.ans
+*.ans
+
+# Outputs
+*.xlsx
+*.sql

LICENSE

@@ -1,4 +1,4 @@
-                                 Apache License
+                                Apache License
                            Version 2.0, January 2004
                         http://www.apache.org/licenses/
 

README.md

@@ -7,4 +7,6 @@ To run the code, follow these steps
 2. In an anaconda environment, type 
 
         pip install pyfemm
-        conda install openmdao
+        conda install openmdao
+
+The technical support of David Meeker, Ph.D., author of the Femm library is gratefully acknowledged

examples/convergence_plots.py

@@ -0,0 +1,79 @@
+import openmdao.api as om
+import os
+import matplotlib.pyplot as plt
+
+
+class Convergence_Trends_Opt(om.ExplicitComponent):
+    """
+    Deprecating this for now and using OptView from PyOptSparse instead.
+    """
+
+    def initialize(self):
+
+        self.options.declare("opt_options")
+
+    def compute(self, inputs, outputs):
+
+        folder_output = self.options["opt_options"]["general"]["folder_output"]
+        print("Figures saved here: ", folder_output)
+        optimization_log = os.path.join(folder_output, self.options["opt_options"]["recorder"]["file_name"])
+
+        if os.path.exists(optimization_log):
+            cr = om.CaseReader(optimization_log)
+            cases = cr.get_cases()
+            rec_data = {}
+            design_vars = {}
+            responses = {}
+            iterations = []
+            for i, it_data in enumerate(cases):
+                iterations.append(i)
+
+                # Collect DVs and responses separately for DOE
+                for design_var in [it_data.get_design_vars()]:
+                    for dv in design_var:
+                        if i == 0:
+                            design_vars[dv] = []
+                        design_vars[dv].append(design_var[dv])
+
+                for response in [it_data.get_responses()]:
+                    for resp in response:
+                        if i == 0:
+                            responses[resp] = []
+                        responses[resp].append(response[resp])
+
+                # parameters = it_data.get_responses()
+                for parameters in [it_data.get_responses(), it_data.get_design_vars()]:
+                    for j, param in enumerate(parameters.keys()):
+                        if i == 0:
+                            rec_data[param] = []
+                        rec_data[param].append(parameters[param])
+
+            for param in rec_data.keys():
+                fig, ax = plt.subplots(1, 1, figsize=(5.3, 4))
+                ax.plot(iterations, rec_data[param])
+                ax.set(xlabel="Number of Iterations", ylabel=param)
+                fig_name = "Convergence_trend_" + param + ".png"
+                fig.savefig(os.path.join(folder_output, fig_name))
+                plt.close(fig)
+
+
+class PlotRecorder(om.Group):
+    def initialize(self):
+        self.options.declare("opt_options")
+
+    def setup(self):
+        self.add_subsystem("conv_plots", Convergence_Trends_Opt(opt_options=self.options["opt_options"]))
+
+
+mydir = os.path.dirname(os.path.realpath(__file__))  # get path to this file
+output_folder_name = "test5"
+
+opt_options = {}
+opt_options["general"] = {}
+opt_options["general"]["folder_output"] = os.path.join(mydir, "outputs", output_folder_name)
+opt_options["recorder"] = {}
+opt_options["recorder"]["file_name"] = "log.sql"
+
+wt_opt = om.Problem(model=PlotRecorder(opt_options=opt_options))
+wt_opt.setup(derivatives=False)
+wt_opt.run_model()