From f6b1b22b0d797ae424ce645e1c9561c08f6c1d2e Mon Sep 17 00:00:00 2001
From: "Mads M. Pedersen" <mmpe@dtu.dk>
Date: Thu, 14 Jun 2018 10:22:29 +0200
Subject: [PATCH] implemented easy_drivers.py
---
tests/topfarm/__init__.py | 0
tests/topfarm/test_drivers.py | 73 ++++++++++++++++++++++++
tests/{ => topfarm}/test_topfarm.py | 0
topfarm/_topfarm.py | 17 +++---
topfarm/cost_models/dummy.py | 3 -
topfarm/easy_drivers.py | 88 +++++++++++++++++++++++++++++
6 files changed, 169 insertions(+), 12 deletions(-)
create mode 100644 tests/topfarm/__init__.py
create mode 100644 tests/topfarm/test_drivers.py
rename tests/{ => topfarm}/test_topfarm.py (100%)
create mode 100644 topfarm/easy_drivers.py
diff --git a/tests/topfarm/__init__.py b/tests/topfarm/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/tests/topfarm/test_drivers.py b/tests/topfarm/test_drivers.py
new file mode 100644
index 00000000..718db758
--- /dev/null
+++ b/tests/topfarm/test_drivers.py
@@ -0,0 +1,73 @@
+'''
+Created on 17. maj 2018
+
+@author: mmpe
+'''
+from topfarm import TopFarm
+
+import numpy as np
+import pytest
+from topfarm.cost_models.dummy import DummyCost, DummyCostPlotComp
+from topfarm.plotting import NoPlot
+from topfarm.easy_drivers import EasyScipyOptimizeDriver, EasySimpleGADriver
+
+
+initial = [[6, 0], [6, -8], [1, 1]] # initial turbine layouts
+optimal = np.array([[2.5, -3], [6, -7], [4.5, -3]]) # desired turbine layouts
+boundary = [(0, 0), (6, 0), (6, -10), (0, -10)] # turbine boundaries
+desired = [[3, -3], [7, -7], [4, -3]] # desired turbine layouts
+
+
+@pytest.fixture
+def topfarm_generator():
+ def _topfarm_obj(driver):
+ plot_comp = DummyCostPlotComp(desired)
+ #plot_comp = NoPlot()
+ return TopFarm(initial, DummyCost(desired), 2, plot_comp=plot_comp, boundary=boundary, driver=driver)
+ return _topfarm_obj
+
+
+
+
+# # CONMIN-specific Settings
+# self.driver.itmax = 30
+# self.driver.fdch = 0.00001
+# self.driver.fdchm = 0.000001
+# self.driver.ctlmin = 0.01
+# self.driver.delfun = 0.001
+#
+# # NEWSUMT-specific Settings
+# #self.driver.itmax = 10
+#
+# # COBYLA-specific Settings
+# #self.driver.rhobeg = 1.0
+# #self.driver.rhoend = 1.0e-4
+# #self.driver.maxfun = 1000
+#
+# # SLSQP-specific Settings
+# #self.driver.accuracy = 1.0e-6
+# #self.driver.maxiter = 50
+#
+# # Genetic-specific Settings
+# #self.driver.population_size = 90
+# #self.driver.crossover_rate = 0.9
+# #self.driver.mutation_rate = 0.02
+# #self.selection_method = 'rank'
+
+
+@pytest.mark.parametrize('driver,tol',[(EasyScipyOptimizeDriver(), 1e-4),
+ (EasyScipyOptimizeDriver(tol=1e-3), 1e-2),
+ (EasyScipyOptimizeDriver(maxiter=13), 1e-1),
+ (EasyScipyOptimizeDriver(optimizer='COBYLA', tol=1e-3), 1e-2),
+ #(EasyPyOptSparseSLSQP(),??),
+ (EasySimpleGADriver(), 1e-4)][-1:])
+def test_optimizers(driver, tol, topfarm_generator):
+ tf = topfarm_generator(driver)
+ tf.optimize()
+ tb_pos = tf.turbine_positions
+ #tf.plot_comp.show()
+
+ assert sum((tb_pos[2] - tb_pos[0])**2) > 2**2 - tol # check min spacing
+ assert tb_pos[1][0]< 6 + tol # check within border
+ np.testing.assert_array_almost_equal(tb_pos, optimal, -int(np.log10(tol)))
+ #print (tb_pos - optimal)
diff --git a/tests/test_topfarm.py b/tests/topfarm/test_topfarm.py
similarity index 100%
rename from tests/test_topfarm.py
rename to tests/topfarm/test_topfarm.py
diff --git a/topfarm/_topfarm.py b/topfarm/_topfarm.py
index 572c9efa..c145ea4a 100644
--- a/topfarm/_topfarm.py
+++ b/topfarm/_topfarm.py
@@ -19,7 +19,7 @@ class TopFarm(object):
"""
def __init__(self, turbines, cost_comp, min_spacing, boundary, boundary_type='convex_hull', plot_comp=None,
- driver_options={'optimizer': 'SLSQP'}):
+ driver=ScipyOptimizeDriver()):
self.initial_positions = turbines = np.array(turbines)
@@ -32,19 +32,18 @@ class TopFarm(object):
indeps = prob.model.add_subsystem('indeps', IndepVarComp(), promotes=['*'])
min_x, min_y = self.boundary_comp.vertices.min(0)
mean_x, mean_y = self.boundary_comp.vertices.mean(0)
- if driver_options['optimizer'] == 'SLSQP':
+ design_var_kwargs = {}
+
+ if 'optimizer' in driver.options and driver.options['optimizer'] == 'SLSQP':
min_x, min_y, mean_x, mean_y = 0, 0, 1, 1 # scaling disturbs SLSQP
+ # Default +/- sys.float_info.max does not work for SLSQP
+ design_var_kwargs = {'lower': np.nan, 'upper': np.nan}
indeps.add_output('turbineX', turbines[:, 0], units='m', ref0=min_x, ref=mean_x)
indeps.add_output('turbineY', turbines[:, 1], units='m', ref0=min_y, ref=mean_y)
indeps.add_output('boundary', self.boundary_comp.vertices, units='m')
prob.model.add_subsystem('cost_comp', cost_comp, promotes=['*'])
- prob.driver = ScipyOptimizeDriver()
-
- prob.driver.options.update(driver_options)
- design_var_kwargs = {}
- if driver_options['optimizer'] == 'SLSQP':
- # Default +/- sys.float_info.max does not work for SLSQP
- design_var_kwargs = {'lower': np.nan, 'upper': np.nan}
+ prob.driver = driver
+
prob.model.add_design_var('turbineX', **design_var_kwargs)
prob.model.add_design_var('turbineY', **design_var_kwargs)
prob.model.add_objective('cost')
diff --git a/topfarm/cost_models/dummy.py b/topfarm/cost_models/dummy.py
index 777b77f8..77a99f00 100644
--- a/topfarm/cost_models/dummy.py
+++ b/topfarm/cost_models/dummy.py
@@ -19,9 +19,6 @@ class DummyCost(ExplicitComponent):
self.optimal = np.array(optimal_positions)
self.N = self.optimal.shape[0]
- def cost(self, x, y):
- """Evaluate cost function"""
-
def setup(self):
self.add_input('turbineX', val=np.zeros(self.N), units='m')
self.add_input('turbineY', val=np.zeros(self.N), units='m')
diff --git a/topfarm/easy_drivers.py b/topfarm/easy_drivers.py
new file mode 100644
index 00000000..3f63aa71
--- /dev/null
+++ b/topfarm/easy_drivers.py
@@ -0,0 +1,88 @@
+from openmdao.drivers.scipy_optimizer import ScipyOptimizeDriver
+#from openmdao.drivers.pyoptsparse_driver import pyOptSparseDriver
+from openmdao.drivers.genetic_algorithm_driver import SimpleGADriver
+
+
+class EasyScipyOptimizeDriver(ScipyOptimizeDriver):
+
+ def __init__(self, optimizer='SLSQP', maxiter=200, tol=1e-6, disp=True):
+ """
+ Parameters
+ ----------
+ optimizer : {'Nelder-Mead', 'Powell', 'CG', 'BFGS', 'Newton-CG', 'L-BFGS-B',
+ 'TNC', 'COBYLA', 'SLSQP'}
+ Inequality constraints are supported by COBYLA and SLSQP,
+ but equality constraints are only supported by SLSQP. None of the other
+ optimizers support constraints.
+ maxiter : int
+ Maximum number of iterations.
+ tol : float
+ Tolerance for termination. For detailed control, use solver-specific options.
+ disp : bool
+ Set to False to prevent printing of Scipy convergence messages
+ """
+ ScipyOptimizeDriver.__init__(self)
+ self.options.update({'optimizer': optimizer, 'maxiter': maxiter, 'tol': tol, 'disp': disp})
+
+
+# class EasyPyOptSparseSLSQP(pyOptSparseDriver):
+# def __init__(self, maxit=200, acc=1e-6):
+# pyOptSparseDriver.__init__(self)
+# raise NotImplementedError
+
+
+class EasySimpleGADriver(SimpleGADriver):
+ def __init__(self, elitism=True, max_gen=100):
+ """Simple Genetic Algorithm Driver with argument
+
+ Parameters
+ ----------
+ bits : dict
+ Number of bits of resolution. Default is an empty dict, where every unspecified variable is assumed to be integer, and the number of bits is calculated automatically. If you have a continuous var, you should set a bits value as a key in this dictionary.
+ NotImplemented
+ debug_print : list
+ List of what type of Driver variables to print at each iteration. Valid items in list are ‘desvars’, ‘ln_cons’, ‘nl_cons’, ‘objs’, ‘totals’
+ NotImplemented
+ elitism : bool
+ If True, replace worst performing point with best from previous generation each iteration.
+ max_gen : int
+ Number of generations before termination.
+ pop_size :
+ Number of points in the GA. Set to 0 and it will be computed as four times the number of bits.
+ NotImplemented
+ procs_per_model : int
+ Number of processors to give each model under MPI.
+ NotImplemented
+ run_parallel : bool
+ Set to True to execute the points in a generation in parallel.
+ NotImplemented
+ """
+ SimpleGADriver.__init__(self)
+ self.options.update({'elitism': elitism, 'max_gen': max_gen})
+
+#
+# class COBYLADriverWrapper(CONMINdriver):
+# # CONMIN-specific Settings
+# self.driver.itmax = 30
+# self.driver.fdch = 0.00001
+# self.driver.fdchm = 0.000001
+# self.driver.ctlmin = 0.01
+# self.driver.delfun = 0.001
+#
+# # NEWSUMT-specific Settings
+# #self.driver.itmax = 10
+#
+# # COBYLA-specific Settings
+# #self.driver.rhobeg = 1.0
+# #self.driver.rhoend = 1.0e-4
+# #self.driver.maxfun = 1000
+#
+# # SLSQP-specific Settings
+# #self.driver.accuracy = 1.0e-6
+# #self.driver.maxiter = 50
+#
+# # Genetic-specific Settings
+# #self.driver.population_size = 90
+# #self.driver.crossover_rate = 0.9
+# #self.driver.mutation_rate = 0.02
+# #self.selection_method = 'rank'
--
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