diff --git a/topfarm/constraint_components/spacing_component.py b/topfarm/constraint_components/spacing_component.py
index ec97351d85f0706322a4874abbcb631996184596..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'] = dSdx
- J['wtSeparationSquared', 'turbineY'] = dSdy
+ return dSdx, dSdy
diff --git a/topfarm/utils.py b/topfarm/utils.py
index 16cdaaf76a3f39cc1eba6099b6be60400d5c87eb..f5256c7e1e4e62b6c0ffccfceab6859c34ba12a1 100644
--- a/topfarm/utils.py
+++ b/topfarm/utils.py
@@ -1,14 +1,18 @@
+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
-from topfarm.constraint_components.boundary_component import \
- PolygonBoundaryComp
-from topfarm.constraint_components.spacing_component import SpacingComp
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
@@ -25,6 +29,10 @@ def pos_from_case(case_recorder_filename):
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:
@@ -40,32 +48,33 @@ def latest_id(case_recorder_dir):
def random_positions(boundary, n_wt, n_iter, step_size, min_space,
plot=False, verbose=True):
- ba = np.array(boundary).T
- x_max = max(ba[0])
- x_min = min(ba[0])
- y_max = max(ba[1])
- y_min = min(ba[1])
- x = np.random.rand(n_wt)
- y = np.random.rand(n_wt)
- xm = (x_max+x_min)/2
- ym = (y_max+y_min)/2
- xa = (x_max-xm)
- ya = (y_max-ym)
- x *= 2*xa
- y *= 2*ya
- x += xm-xa
- y += ym-ya
+ '''
+ 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 gradient that the turbines are moved
+ in each step
+ min_space: the minimum spacing between turbines
+ 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, plot, verbose)
+ return turbines
+
+def _random_positions(x, y, boundary, n_wt, n_iter, step_size, min_space,
+ plot, verbose):
boundary_comp = PolygonBoundaryComp(boundary, n_wt)
spacing_comp = SpacingComp(nTurbines=n_wt)
turbineX = copy(x)
turbineY = copy(y)
- inputs = {}
- outputs = {}
- J = {}
- inputs['turbineX'] = turbineX
- inputs['turbineY'] = turbineY
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:
@@ -73,11 +82,8 @@ def random_positions(boundary, n_wt, n_iter, step_size, min_space,
plt.plot(bx, by)
plt.plot(x, y, '.')
for j in range(n_iter):
- spacing_comp.compute(inputs, outputs)
- spacing_comp.compute_partials(inputs, J)
- dx = J['wtSeparationSquared', 'turbineX']
- dy = J['wtSeparationSquared', 'turbineY']
- dist = outputs['wtSeparationSquared']
+ 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
@@ -91,8 +97,7 @@ def random_positions(boundary, n_wt, n_iter, step_size, min_space,
break
if plot:
plt.plot(turbineX, turbineY, 'o')
- spacing_comp.compute(inputs, outputs)
- dist = outputs['wtSeparationSquared']
+ dist = spacing_comp._compute(turbineX, turbineY)
index = np.argmin(dist)
if verbose:
print('Spacing obtained: {}'.format(dist[index]**0.5))
@@ -101,6 +106,10 @@ def random_positions(boundary, n_wt, n_iter, step_size, min_space,
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):
for i in range(0, n_wt):
dng = boundary_comp.calc_distance_and_gradients(turbineX,
@@ -111,21 +120,19 @@ def _contain(n_wt, turbineX, turbineY, boundary_comp):
dy = dng[2][i]
turbineX[i] -= dx*dist*1.1
turbineY[i] -= dy*dist*1.1
- dng = boundary_comp.calc_distance_and_gradients(turbineX,
- turbineY)
- dist = dng[0][i]
return turbineX, turbineY
if __name__ == '__main__':
- 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)
+# 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