def load(self, rec_file):
"""Loads stored data to instantiate a surrogate model.
Parameters
----------
rec_file : str
Name of the file in `latom.data.smt` where the surrogate model is stored
"""
self.d = load(self.abs_path(rec_file))
self.limits = self.d['limits']
self.x_samp = self.d['x_samp']
self.m_prop = self.d['m_prop']
self.failures = self.d['failures']
def load(self, rec_file):
"""Loads stored data to instantiate a meta model.
Parameters
----------
rec_file : str
Name of the file in `latom.data.metamodels` where the meta model is stored
"""
self.d = load(self.abs_path(rec_file))
self.twr = self.d['twr']
self.Isp = self.d['Isp']
self.m_prop = self.d['m_prop']
self.failures = self.d['failures']
import numpy as np
from latom.utils.pickle_utils import load, save
from latom.data.metamodels.data_mm import dirname_metamodels
from latom.plots.response_surfaces import RespSurf
plot = 'mp' # 'mp' to plot the propellant fraction, 'en' to plot the spacecraft energy
fid = None # 'llo2apo_lin_19_12_390-500.pkl' # filename for adjusted solution
direction = 1 # stack Isp (columns, 1) or thrust/weight ratios (rows, 0)
# load raw solutions
fid1 = '/'.join([dirname_metamodels, 'llo2apo_lin_19_6_390-440.pkl'])
fid2 = '/'.join([dirname_metamodels, 'tests/llo2apo_mm_lin450-500.pkl'])
d1 = load(fid1)
d2 = load(fid2)
# stack solutions
if np.isclose(direction, 0): # same Isp bounds and step
m_prop = np.vstack((d1['m_prop'], d2['m_prop']))
energy = np.vstack((d1['energy'], d2['energy']))
failures = np.vstack((d1['failures'], d2['failures']))
twr = np.hstack((d1['twr'], d2['twr']))
isp = d1['Isp']
elif np.isclose(direction, 1): # same thrust/weight ratio bounds and step
m_prop = np.hstack((d1['m_prop'], d2['m_prop']))
energy = np.hstack((d1['energy'], d2['energy']))
failures = np.hstack((d1['failures'], d2['failures']))
extrapolate=extrapolate,
method=im_mm,
training_data_gradients=training_data_gradients,
vec_size=nb_points,
rec_file=fid_mm)
# SurrogateModel instance(s)
sm_lhs = SurrogateModel(tm_lhs, rec_file=fid_lhs)
if fid_full is not None:
sm_full = SurrogateModel(tm_full, rec_file=fid_full)
else:
sm_full = None
# benchmark points
if compute_err and (not solve):
d = load(fid_real)
isp = d['Isp']
twr = d['twr']
else:
if sm_full is not None:
isp = generate_benchmark_points(mm.limits[0],
nb_points,
mm.Isp,
sm_lhs.x_samp[:, 0],
sm_full.x_samp[:, 0],
atol=1e-6)
twr = generate_benchmark_points(mm.limits[1],
nb_points,
mm.twr,
sm_lhs.x_samp[:, 1],
sm_full.x_samp[:, 1],
from latom.utils.pickle_utils import load, save from latom.data.continuation.data_continuation import dirname_continuation from latom.data.metamodels.data_mm import dirname_metamodels from latom.plots.response_surfaces import RespSurf plot = 'mp' # 'mp' to plot the propellant fraction, 'en' to plot the spacecraft energy fid = None # 'llo2apo_lin_005-05_250-330.pkl' # filename for adjusted solution en_threshold = -6e4 # spacecraft energy threshold isp_lim = (0, None) # new specific impulse limits twr_lim = (2, None) # new thrust/weight ratio limits # load raw solution fid_raw = '/'.join([dirname_metamodels, 'tests/llo2apo_mm_lin159.pkl']) d = load(fid_raw) # extract data from dictionary isp_raw = np.reshape(d['Isp'], (1, np.size(d['Isp']))) twr_raw = np.reshape(d['twr'], (np.size(d['twr']), 1)) m_prop_raw = d['m_prop'] energy_raw = d['energy'] # Isp and thrust/weight ratio matrices isp_mat = np.ones(np.shape(energy_raw)) * isp_raw twr_mat = np.ones(np.shape(energy_raw)) * twr_raw # Isp and thrust/weight ratios for which the solution degenerated into a parabola twr_fail = twr_mat[energy_raw > en_threshold] isp_fail = isp_mat[energy_raw > -en_threshold]