Clarified how to test example cycles & made fixes to some related test scripts

.github/PULL_REQUEST_TEMPLATE.md

@@ -0,0 +1,15 @@
+### Summary
+
+Summary of PR.
+
+### Related Issues
+
+- Resolves #
+
+### Backwards incompatibilities
+
+None
+
+### New Dependencies
+
+None

README.md

@@ -27,7 +27,7 @@ Here is the OpenMDAO version you need for the specific versions of pyCycle
 | 4.2.0            | 3.10.0 or greater |
 
 ## Version 4.2 --- PyPI release
-No significant code changes, but minor adjustments to the package name in `setup.py` to enable publishing to PyPI. 
+No significant code changes, but minor adjustments to the package name in `setup.py` to enable publishing to PyPI.
 
 ## Citation
 
@@ -59,9 +59,9 @@ If you use pyCycle, please cite this paper:
 
     pip install 'om-pycycle[all]'
 
-Why is it `om-pycycle` on PyPI? 
-Because another package already claimed `pyCycle`! 
-Note that the import does not change though. 
+Why is it `om-pycycle` on PyPI?
+Because another package already claimed `pyCycle`!
+Note that the import does not change though.
 You still use `import pycycle` regardless.
 
 
@@ -90,7 +90,7 @@ or for pyCycle V4.0.0:
 
 Use pip to install:
 
-    pip install -e .
+    pip install -e .[all]
 
 
 ## Testing
@@ -100,10 +100,10 @@ After installation if you wat to run the unit test suite you can do so via the `
     testflo pycycle
 
 This will run all the unit tests within the pycycle repository, but note that it will NOT run the longer regression tests from the
-`example_cycles` folder.
-If you want to run the regression tests, then you need to clone the repository, CD into the `example_cycles` folder and call
+`example_cycles` folder.  These tests are written as 'benchmark' tests.
+If you want to run these tests, then you need to clone the repository, CD into the `example_cycles` folder and call
 
-    testflo .
+    testflo -b .
 
 
 ## Version 4.0 Announcements

example_cycles/N+3ref/N3_SPD.py

@@ -4,20 +4,27 @@
 from pprint import pprint
 
 import openmdao.api as om
+from openmdao.utils.general_utils import set_pyoptsparse_opt
 
 import pycycle.api as pyc
 
 from N3ref import N3, viewer, MPN3
 
+# check that pyoptsparse is installed
+OPT, OPTIMIZER = set_pyoptsparse_opt('SNOPT')
+if OPTIMIZER:
+    from openmdao.drivers.pyoptsparse_driver import pyOptSparseDriver
+
+
 def N3_SPD_model():
 
     prob = om.Problem()
 
-    prob.model = MPN3()    
+    prob.model = MPN3()
 
     # setup the optimization
     prob.driver = om.pyOptSparseDriver()
-    prob.driver.options['optimizer'] = 'SNOPT'
+    prob.driver.options['optimizer'] = OPTIMIZER
     prob.driver.options['debug_print'] = ['desvars', 'nl_cons', 'objs']
     prob.driver.opt_settings={'Major step limit': 0.05}
 
@@ -53,15 +60,15 @@ def N3_SPD_model():
     # Define the design point
     prob.set_val('TOC.splitter.BPR', 23.94514401),
     prob.set_val('TOC.balance.rhs:hpc_PR', 53.6332)
-    prob.set_val('TOC.fc.W', 820.44097898, units='lbm/s') 
+    prob.set_val('TOC.fc.W', 820.44097898, units='lbm/s')
 
     # Set specific cycle parameters
     prob.set_val('fan:PRdes', 1.300),
     prob.set_val('lpc:PRdes', 3.000),
     prob.set_val('T4_ratio.TR', 0.926470588)
     prob.set_val('RTO_T4', 3400.0, units='degR')
     prob.set_val('SLS.balance.rhs:FAR', 28620.84, units='lbf')
-    prob.set_val('CRZ.balance.rhs:FAR', 5510.72833567, units='lbf') 
+    prob.set_val('CRZ.balance.rhs:FAR', 5510.72833567, units='lbf')
     prob.set_val('RTO.hpt_cooling.x_factor', 0.9)
 
     # Set initial guesses for balances
@@ -116,4 +123,4 @@ def N3_SPD_model():
     for pt in ['TOC']+prob.model.od_pts:
         viewer(prob, pt)
 
-    print("time", time.time() - st)
+    print("time", time.time() - st)

example_cycles/N+3ref/benchmark_N3_SPD.py

@@ -1,16 +1,22 @@
-import numpy as np 
+import numpy as np
 import unittest
 import os
 
 import openmdao.api as om
 from openmdao.utils.assert_utils import assert_near_equal
+from openmdao.utils.general_utils import set_pyoptsparse_opt
 
 import pycycle.api as pyc
 
 from N3_SPD import N3_SPD_model
 
+# check that pyoptsparse is installed
+OPT, OPTIMIZER = set_pyoptsparse_opt('SNOPT')
+
+
 class N3MDPOptTestCase(unittest.TestCase):
 
+    @unittest.skipUnless(OPT, "This test requires pyOptSparse.")
     def benchmark_case1(self):
 
         prob = N3_SPD_model()
@@ -20,15 +26,15 @@ def benchmark_case1(self):
         # Define the design point
         prob.set_val('TOC.splitter.BPR', 23.94514401),
         prob.set_val('TOC.balance.rhs:hpc_PR', 53.6332)
-        prob.set_val('TOC.fc.W', 820.44097898, units='lbm/s') 
+        prob.set_val('TOC.fc.W', 820.44097898, units='lbm/s')
 
         # Set specific cycle parameters
         prob.set_val('fan:PRdes', 1.300),
         prob.set_val('lpc:PRdes', 3.000),
         prob.set_val('T4_ratio.TR', 0.926470588)
         prob.set_val('RTO_T4', 3400.0, units='degR')
         prob.set_val('SLS.balance.rhs:FAR', 28620.84, units='lbf')
-        prob.set_val('CRZ.balance.rhs:FAR', 5510.72833567, units='lbf') 
+        prob.set_val('CRZ.balance.rhs:FAR', 5510.72833567, units='lbf')
         prob.set_val('RTO.hpt_cooling.x_factor', 0.9)
 
         # Set initial guesses for balances
@@ -126,7 +132,7 @@ def benchmark_case1(self):
         assert_near_equal(prob['CRZ.balance.fan_Nmech'], 2118.62554023, tol)#
         assert_near_equal(prob['CRZ.balance.lp_Nmech'], 6567.78766693, tol)#
         assert_near_equal(prob['CRZ.balance.hp_Nmech'], 20574.43651756, tol)#
-        assert_near_equal(prob['CRZ.hpc.Fl_O:tot:T'], 1481.9756247, tol)#   
+        assert_near_equal(prob['CRZ.hpc.Fl_O:tot:T'], 1481.9756247, tol)#
 
 
 if __name__ == "__main__":

example_cycles/electric_propulsor.py

@@ -2,6 +2,13 @@
 
 import pycycle.api as pyc
 
+# protection incase env doesn't have matplotlib installed, since its not strictly required
+try:
+    import matplotlib
+    import matplotlib.pyplot as plt
+except ImportError:
+  plt = None
+
 
 class Propulsor(pyc.Cycle):
 
@@ -10,10 +17,10 @@ def setup(self):
         design = self.options['design']
 
         USE_TABULAR = True
-        if USE_TABULAR: 
+        if USE_TABULAR:
             self.options['thermo_method'] = 'TABULAR'
             self.options['thermo_data'] = pyc.AIR_JETA_TAB_SPEC
-        else: 
+        else:
             self.options['thermo_method'] = 'CEA'
             self.options['thermo_data'] = pyc.species_data.janaf
             FUEL_TYPE = 'JP-7'
@@ -24,7 +31,7 @@ def setup(self):
         self.add_subsystem('inlet', pyc.Inlet())
         self.add_subsystem('fan', pyc.Compressor(map_data=pyc.FanMap, map_extrap=True))
         self.add_subsystem('nozz', pyc.Nozzle())
-        
+
         self.add_subsystem('perf', pyc.Performance(num_nozzles=1, num_burners=0))
 
 
@@ -125,15 +132,14 @@ def setup(self):
             self.pyc_add_pnt(pt, Propulsor(design=False, thermo_method='CEA'))
 
             self.set_input_defaults(pt+'.fc.MN', val=self.od_MNs[i])
-            self.set_input_defaults(pt+'.fc.alt', val=self.od_alts, units='m') 
-            self.set_input_defaults(pt+'.fan.map.RlineMap', val=self.od_Rlines[i])        
+            self.set_input_defaults(pt+'.fc.alt', val=self.od_alts, units='m')
+            self.set_input_defaults(pt+'.fan.map.RlineMap', val=self.od_Rlines[i])
 
         self.pyc_use_default_des_od_conns()
 
         self.pyc_connect_des_od('nozz.Throat:stat:area', 'balance.rhs:W')
 
         super().setup()
-
 
 
 if __name__ == "__main__":
@@ -158,13 +164,13 @@ def setup(self):
 
     # Set initial guesses for balances
     prob['design.balance.W'] = 200.
-    
+
     for i, pt in enumerate(mp_propulsor.od_pts):
-    
+
         # initial guesses
-        prob['off_design.fan.PR'] = 1.2
-        prob['off_design.balance.W'] = 406.790
-        prob['off_design.balance.Nmech'] = 1. # normalized value
+        prob[pt+'.fan.PR'] = 1.2
+        prob[pt+'.balance.W'] = 406.790
+        prob[pt+'.balance.Nmech'] = 1. # normalized value
 
     st = time.time()
 
@@ -184,7 +190,7 @@ def setup(self):
         print('\n', '#'*10, pt, '#'*10)
         viewer(prob, pt)
 
-    map_plots(prob,'design')
-
+    if plt:
+        map_plots(prob,'design')
 
     print("Run time", run_time)