# Set x limits for each variable based on target:
x_limits = []
for i in range(target._dim):
limits = [np.min(samples[:, i]), np.max(samples[:, i])]
x_limits.append(limits)
# Build up srom_size-to-SROM object map for plotting routine.
sroms = OrderedDict()
for srom_size in srom_sizes:
# Generate SROM from file:
srom = SROM(srom_size, target._dim)
srom_filename = "srom_m" + str(srom_size) + ".txt"
srom_filename = os.path.join(srom_dir, srom_filename)
srom.load_params(srom_filename)
sroms[srom_size] = srom
# Font size specs & plotting.
axis_font_size = 25
legend_font_size = 20
Postprocessor.compare_srom_cdfs(sroms,
target,
plot_dir="plots",
plot_suffix=plot_suffix,
variable_names=variables,
x_limits=x_limits,
x_ticks=x_ticks,
cdf_y_label=cdf_y_label,
axis_font_size=axis_font_size,
legend_font_size=legend_font_size)
sromsize = 20 #Data files for EOL samples, EOL finite difference samples, and SROM inputs srom_eol_file = "srom_data/srom_eol_m" + str(sromsize) + ".txt" srom_fd_eol_file = "srom_data/srom_fd_eol_m" + str(sromsize) + ".txt" srom_input_file = "srom_data/srom_m" + str(sromsize) + ".txt" #Get MC input/EOL samples MC_inputs = np.genfromtxt(mc_input_file) MC_eols = np.genfromtxt(mc_eol_file) #Get SROM EOL samples, FD samples and input SROM from file srom_eols = np.genfromtxt(srom_eol_file) srom_fd_eols = np.genfromtxt(srom_fd_eol_file) input_srom = SROM(sromsize, dim) input_srom.load_params(srom_input_file) #Get FD step sizes from file (the same for all samples, just pull the first) #Step sizes chosen as approximately 2% of the median sample value of inputs stepsizes = [0.0065, 0.083, 0.025] #Calculate gradient from FiniteDifference class: gradient = FD.compute_gradient(srom_eols, srom_fd_eols, stepsizes) #Create SROM surrogate, sample, and create random variable solution surrogate_PWL = SROMSurrogate(input_srom, srom_eols, gradient) srom_eol_samples = surrogate_PWL.sample(MC_inputs) solution_PWL = SampleRandomVector(srom_eol_samples) #Store EOL samples for plotting later: eolfile = "srom_data/srom_eol_samples_m" + str(sromsize) + ".txt"
#Set x limits for each variable based on target:
xlimits = []
for i in range(target._dim):
lims = [np.min(samples[:, i]), np.max(samples[:, i])]
xlimits.append(lims)
#Build up sromsize-to-SROM object map for plotting routine
sroms = OrderedDict()
for sromsize in sromsizes:
#Generate SROM from file:
srom = SROM(sromsize, target._dim)
sromfile = "srom_m" + str(sromsize) + ".txt"
sromfile = os.path.join(srom_dir, sromfile)
srom.load_params(sromfile)
sroms[sromsize] = srom
#Font size specs & plotting
axisfontsize = 25
legendfontsize = 20
Postprocessor.compare_srom_CDFs(sroms,
target,
plotdir="plots",
plotsuffix=plot_suffix,
variablenames=varz,
xlimits=xlimits,
xticks=xticks,
cdfylabel=cdfylabel,
axisfontsize=axisfontsize,
legendfontsize=legendfontsize)