diff --git a/topfarm/_topfarm.py b/topfarm/_topfarm.py
index 1344dc02e0bafa9e3bc155fa5bb451ad1770346b..c210f2fb057927648120dae2789e9d8d945640d6 100644
--- a/topfarm/_topfarm.py
+++ b/topfarm/_topfarm.py
@@ -10,7 +10,7 @@ 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
+from topfarm.utils import pos_from_case, latest_id
class TopFarm(object):
diff --git a/topfarm/constraint_components/spacing_component.py b/topfarm/constraint_components/spacing_component.py
index 318948d9a75fa8a03b96718bb0a4db37125525e9..7d05698157636ec8121f3d903aa72ba924e07159 100644
--- a/topfarm/constraint_components/spacing_component.py
+++ b/topfarm/constraint_components/spacing_component.py
@@ -33,34 +33,39 @@ class SpacingComp(ExplicitComponent):
self.declare_partials('wtSeparationSquared', ['turbineX', 'turbineY'])
def compute(self, inputs, outputs):
- # print 'in dist const'
-
turbineX = inputs['turbineX']
turbineY = inputs['turbineY']
+ separation_squared = self._compute(turbineX, turbineY)
+ outputs['wtSeparationSquared'] = separation_squared
+
+
+ def _compute(self, turbineX, turbineY):
nTurbines = self.nTurbines
separation_squared = np.zeros(int((nTurbines - 1) * nTurbines / 2))
-
k = 0
for i in range(0, nTurbines):
for j in range(i + 1, nTurbines):
separation_squared[k] = (turbineX[j] - turbineX[i])**2 + (turbineY[j] - turbineY[i])**2
k += 1
- outputs['wtSeparationSquared'] = separation_squared
-# print("wt sep")
-# print(separation_squared)
-# print()
-
+ return separation_squared
+
+
def compute_partials(self, inputs, J):
-
# obtain necessary inputs
turbineX = inputs['turbineX']
turbineY = inputs['turbineY']
+ dSdx, dSdy = self._compute_partials(turbineX, turbineY)
+ # populate Jacobian dict
+ J['wtSeparationSquared', 'turbineX'] = dSdx
+ J['wtSeparationSquared', 'turbineY'] = dSdy
+
+
+ def _compute_partials(self, turbineX, turbineY):
# get number of turbines
nTurbines = self.nTurbines
# initialize gradient calculation array
- dS = np.zeros((int((nTurbines - 1.) * nTurbines / 2.), 2 * nTurbines))
dSdx = np.zeros((int((nTurbines - 1.) * nTurbines / 2.), nTurbines)) #col: dx_1-dx_n, row: d12, d13,..,d1n, d23..d2n,..
dSdy = np.zeros((int((nTurbines - 1.) * nTurbines / 2.), nTurbines))
@@ -71,20 +76,13 @@ class SpacingComp(ExplicitComponent):
for i in range(0, nTurbines):
for j in range(i + 1, nTurbines):
# separation wrt Xj
- dS[k, j] = 2 * (turbineX[j] - turbineX[i])
dSdx[k,j]= 2 * (turbineX[j] - turbineX[i])
# separation wrt Xi
- dS[k, i] = -2 * (turbineX[j] - turbineX[i])
dSdx[k, i] = -2 * (turbineX[j] - turbineX[i])
# separation wrt Yj
- dS[k, j + nTurbines] = 2 * (turbineY[j] - turbineY[i])
dSdy[k, j] = 2 * (turbineY[j] - turbineY[i])
# separation wrt Yi
- dS[k, i + nTurbines] = -2 * (turbineY[j] - turbineY[i])
dSdy[k, i] = -2 * (turbineY[j] - turbineY[i])
# increment turbine pair counter
k += 1
-
- # populate Jacobian dict
- J['wtSeparationSquared', 'turbineX'] = dS[:, :nTurbines]
- J['wtSeparationSquared', 'turbineY'] = dS[:, nTurbines:]
+ return dSdx, dSdy
diff --git a/topfarm/recording.py b/topfarm/recording.py
deleted file mode 100644
index 3b3672767db07552b4fafccdbbfebb36ba2255d1..0000000000000000000000000000000000000000
--- a/topfarm/recording.py
+++ /dev/null
@@ -1,39 +0,0 @@
-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)
diff --git a/topfarm/utils.py b/topfarm/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..df16d39da6460122fe00afe2927a734509e3e396
--- /dev/null
+++ b/topfarm/utils.py
@@ -0,0 +1,147 @@
+from topfarm.constraint_components.boundary_component import \
+ PolygonBoundaryComp
+from topfarm.constraint_components.spacing_component import SpacingComp
+import os
+from copy import copy
+import numpy as np
+from openmdao.api import CaseReader
+import matplotlib.pyplot as plt
+
+
+def pos_from_case(case_recorder_filename):
+ '''
+ Input: a recorded optimization case
+ Returns the positions at the last step of that optimization
+ '''
+ if not os.path.exists(case_recorder_filename):
+ string = 'The specified optimization recording does not exists: '
+ string += case_recorder_filename
+ raise Warning(string)
+ 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):
+ '''
+ Input: path to the directory of recorded optimizations
+ Returns the absolute path to the most recent recording in that directory
+ '''
+ 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
+
+
+def random_positions(boundary, n_wt, n_iter, step_size, min_space,
+ pad = 1.1, plot=False, verbose=True):
+ '''
+ Input:
+ boundary: list of tuples, e.g.: [(0, 0), (6, 1), (7, -11), (-1, -10)]
+ n_wt: number of wind turbines
+ n_iter: number of iterations allowed to try and satisfy the minimum
+ spacing constraint
+ step_size: the multiplier on the spacing gradient that the turbines
+ are moved in each step
+ min_space: the minimum spacing between turbines
+ pad: the multiplier on the boundary gradient
+ plot: plot the generated random layout
+ verbose: print helpful text to the console
+ Returns an array of xy coordinates of the wind turbines
+ '''
+ x, y = map(_random, np.array(boundary).T)
+ turbines = _random_positions(x, y, boundary, n_wt, n_iter, step_size,
+ min_space, pad, plot, verbose)
+ return turbines
+
+
+def _random_positions(x, y, boundary, n_wt, n_iter, step_size, min_space,
+ pad, plot, verbose):
+ boundary_comp = PolygonBoundaryComp(boundary, n_wt)
+ spacing_comp = SpacingComp(nTurbines=n_wt)
+ turbineX = copy(x)
+ turbineY = copy(y)
+ min_space2 = min_space**2
+ ba = np.array(boundary).T
+ bx = np.append(ba[0], ba[0][0])
+ by = np.append(ba[1], ba[1][0])
+ if plot:
+ plt.cla()
+ plt.plot(bx, by)
+ plt.plot(x, y, '.')
+ for j in range(n_iter):
+ dist = spacing_comp._compute(turbineX, turbineY)
+ dx, dy = spacing_comp._compute_partials(turbineX, turbineY)
+ index = np.argmin(dist)
+ if dist[index] < min_space2:
+ turbineX += dx[index]*step_size
+ turbineY += dy[index]*step_size
+ turbineX, turbineY = _contain(n_wt, turbineX, turbineY,
+ boundary_comp, pad)
+ else:
+ if verbose:
+ print('Obtained required spacing after {} iterations'.format(
+ j))
+ break
+ if plot:
+ plt.plot(turbineX, turbineY, 'o')
+ dist = spacing_comp._compute(turbineX, turbineY)
+ index = np.argmin(dist)
+ if verbose:
+ print('Spacing obtained: {}'.format(dist[index]**0.5))
+ print('Spacing required: {}'.format(min_space))
+ turbines = np.array([turbineX, turbineY]).T
+ return turbines
+
+
+def _random(b):
+ return np.random.rand(n_wt) * (max(b) - min(b)) + min(b)
+
+
+def _contain(n_wt, turbineX, turbineY, boundary_comp, pad):
+ for i in range(0, n_wt):
+ dng = boundary_comp.calc_distance_and_gradients(turbineX,
+ turbineY)
+ dist = dng[0][i]
+ if dist < 0:
+ dx = dng[1][i]
+ dy = dng[2][i]
+ turbineX[i] -= dx*dist*pad
+ turbineY[i] -= dy*dist*pad
+ return turbineX, turbineY
+
+
+if __name__ == '__main__':
+# this_dir = os.path.dirname(os.path.abspath(__file__))
+# crf = r"C:\Sandbox\Git\TopFarm2\topfarm\cases_20180621_111710.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)
+
+ boundary = [(0, 0), (6, 1), (7, -11), (-1, -10)]
+ n_wt = 20
+ n_iter = 1000
+ step_size = 0.1
+ min_space = 2.1
+ plot = True
+ verbose = True
+ turbines = random_positions(boundary, n_wt, n_iter, step_size, min_space,
+ plot, verbose)
+ print(turbines)