results = self.extract_results()
n_level_satisfied = sum(1 for x in results['storage.HQ.H']
if _min <= x <= _max)
q_pump_integral = sum(results['Q_pump'])
q_pump_sum_changes = np.sum(np.diff(results['Q_pump'])**2)
self.intermediate_results.append(
(priority, n_level_satisfied, q_pump_integral, q_pump_sum_changes))
def post(self):
# Call super() class to not overwrite default behaviour
super().post()
for priority, n_level_satisfied, q_pump_integral, q_pump_sum_changes \
in self.intermediate_results:
print('\nAfter finishing goals of priority {}:'.format(priority))
print('Level goal satisfied at {} of {} time steps'.format(
n_level_satisfied, len(self.times())))
print('Integral of Q_pump = {:.2f}'.format(q_pump_integral))
print('Sum of squares of changes in Q_pump: {:.2f}'.format(
q_pump_sum_changes))
# Any solver options can be set here
def solver_options(self):
options = super().solver_options()
solver = options['solver']
options[solver]['print_level'] = 1
return options
# Run
run_optimization_problem(Example)
label='Slootvaart Pump 2',
linewidth=2,
color='r')
ymin, ymax = axarr[4].get_ylim()
axarr[4].set_ylim(-0.05 * (ymax - ymin), ymax * 1.1)
axarr[4].xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))
f.autofmt_xdate()
# Shrink each axis by 20% and put a legend to the right of the axis
for i in range(len(axarr)):
box = axarr[i].get_position()
axarr[i].set_position(
[box.x0, box.y0, box.width * 0.8, box.height])
axarr[i].legend(loc='center left',
bbox_to_anchor=(1, 0.5),
frameon=False)
# Output Plot
f.set_size_inches(8, 9)
plt.savefig(os.path.join(self._output_folder, 'overall_results.png'),
bbox_inches='tight',
pad_inches=0.1)
# Plot the working area with the operating points of the pump.
plot_operating_points(self, self._output_folder)
# Run
run_optimization_problem(Wieringermeer_afd1_afd2, base_folder='..')
