added option to record/resume optimizaton.

record optimization by setting: record = True
chose directory of recording by setting: case_recorder_dir = [your dir]
resume optimization by setting: rerun_case_id = [your case_id] or 'latest' for resuming most recent run

topfarm/_topfarm.py

+import os
 import time
 import numpy as np
 import warnings
 with warnings.catch_warnings():
     warnings.simplefilter('ignore', FutureWarning)
-    from openmdao.api import Problem, ScipyOptimizeDriver, IndepVarComp
+    from openmdao.api import Problem, ScipyOptimizeDriver, IndepVarComp, \
+    SqliteRecorder
 from topfarm.constraint_components.boundary_component import BoundaryComp,\
     PolygonBoundaryComp
 from topfarm.constraint_components.spacing_component import SpacingComp
 from topfarm.plotting import PlotComp
+from topfarm.recording import pos_from_case, latest_id
 
 
 class TopFarm(object):
@@ -19,10 +22,18 @@ class TopFarm(object):
     """
 
     def __init__(self, turbines, cost_comp, min_spacing, boundary, boundary_type='convex_hull', plot_comp=None,
-                 driver=ScipyOptimizeDriver()):
-
-        self.initial_positions = turbines = np.array(turbines)
-
+                 driver=ScipyOptimizeDriver(), record = False, case_recorder_dir = os.getcwd(),
+                 rerun_case_id = None):
+        if rerun_case_id is None:
+            self.initial_positions = turbines = np.array(turbines)
+        elif rerun_case_id is 'latest':
+            rerun_case_id = latest_id(case_recorder_dir)
+            self.initial_positions = turbines = pos_from_case(rerun_case_id) 
+            print('*Initial positions loaded from file: {}\n'.format(
+                    rerun_case_id))
+        else:
+            self.initial_positions = turbines = pos_from_case(rerun_case_id) 
+        print(turbines)
         n_wt = turbines.shape[0]
         if boundary_type == 'polygon':
             self.boundary_comp = PolygonBoundaryComp(boundary, n_wt)
@@ -44,6 +55,17 @@ class TopFarm(object):
         prob.model.add_subsystem('cost_comp', cost_comp, promotes=['*'])
         prob.driver = driver
 
+        if record:
+            timestr = time.strftime("%Y%m%d_%H%M%S")
+            filename = 'cases_{}.sql'.format(timestr)
+            case_recorder_filename = os.path.join(case_recorder_dir, filename)
+            recorder = SqliteRecorder(case_recorder_filename)
+            prob.driver.add_recorder(recorder)
+            prob.driver.recording_options['record_desvars'] = True
+            prob.driver.recording_options['record_responses'] = True
+            prob.driver.recording_options['record_objectives'] = True
+            prob.driver.recording_options['record_constraints'] = True
+
         prob.model.add_design_var('turbineX', **design_var_kwargs)
         prob.model.add_design_var('turbineY', **design_var_kwargs)
         prob.model.add_objective('cost')
@@ -63,6 +85,9 @@ class TopFarm(object):
 
         prob.setup(check=True, mode='fwd')
 
+
+        
+        
     def check(self, all=False, tol=1e-3):
         """Check gradient computations"""
         comp_name_lst = [comp.pathname for comp in self.problem.model.system_iter()

topfarm/recording.py

+import os
+import numpy as np
+from openmdao.api import CaseReader
+
+
+def pos_from_case(case_recorder_filename):
+    cr = CaseReader(case_recorder_filename)
+    case_list = cr.driver_cases.list_cases()
+    case_len = len(case_list)
+    case_arg = 'rank0:SLSQP|{:d}'.format(case_len-1)
+    case = cr.driver_cases.get_case(case_arg)
+    x = np.array(case.desvars['turbineX'])
+    y = np.array(case.desvars['turbineY'])
+    turbines = np.column_stack((x, y))
+    return turbines
+
+
+def latest_id(case_recorder_dir):
+    files = os.listdir(case_recorder_dir)
+    files = [x for x in files if x.startswith('cases_') and x.endswith('.sql')]
+    if len(files) == 0:
+        string = 'No recorded files found in the specified directory: '
+        string += case_recorder_dir + '\n' + 9*' '
+        string += 'Start a new optimization or specify another directory '
+        string += 'for resumed optimization'
+        raise Warning(string)
+    latest = max(files)
+    latest = os.path.join(case_recorder_dir,latest)
+    return latest
+    
+if __name__ == '__main__':
+    crf = r"C:\Sandbox\Git\TopFarm2\topfarm\cases_20180621_104446.sql"
+    case_recorder_filename = crf
+    turbines = pos_from_case(case_recorder_filename)
+    print(turbines)
+
+    case_recorder_dir = r'C:\Sandbox\Git\TopFarm2\topfarm'
+    latest_id = latest_id(case_recorder_dir)
+    print(latest_id)