def do_param_search():
z_list = arange(500, 1550, 50)
diff_list = arange(1, 5.5, 0.5)
cs = CalcSimWrapper()
ds = InputDatastore('../InputData', 'NiCu', 973)
ps = ParamSearchEngine(cs, ds)
pbar = ProgressBar(widgets=['Parameter search: ', Percentage(), ' ', Bar()],
maxval=len(z_list) * len(diff_list))
pbar.start()
def progress_update(curi):
pbar.update(curi)
#logstream = StringIO()
#logging.basicConfig(stream=logstream, level=logging.DEBUG)
logging.basicConfig(level=logging.INFO)
retim = ps.search(z_list, diff_list, 973, progress_update)
#print(logstream.getvalue())
extent = 1, 50, 0, 3000
immap = imshow(retim, cmap=cm.jet, interpolation='nearest', extent=extent)
colorbar(immap)
ylabel('z* (arb. units)')
xlabel('Cv/Cve (arb. units)')
gca().set_aspect('auto')
title('Search for minimum fit error')
savetxt('paramsearch.csv', retim)
savefig('paramsearch.png')
]
forwardfiles = [f for f in files if f.endswith("forward.csv")]
reversefiles = [f for f in files if f.endswith("reverse.csv")]
rx = r".*Searchmap_I([\-0-9\.]+)_.*.csv"
for f in forwardfiles:
print(str.format("Processing {}", f))
I = float(re.match(rx, f).groups()[0])
fresults[I] = np.genfromtxt(f, skip_header=0, delimiter=",")
for f in reversefiles:
print(str.format("Processing {}", f))
I = -float(re.match(rx, f).groups()[0])
rresults[I] = np.genfromtxt(f, skip_header=0, delimiter=",")
else:
# do search for forward/back
for direction, result_stash in [("forward", fresults), ("reverse", rresults)]:
search_engine = ParamSearchEngine(accelcs, dstore)
edict = dstore.edict_for_direction(direction)
for I in edict.keys():
print(str.format("{} bias, I = {}", direction, I))
pbar = ProgressBar(
widgets=["Parameter search: ", Percentage(), " ", Bar()], maxval=len(zrange) * len(cvfrange)
)
pbar.start()
search_map = search_engine.search(zrange, cvfrange, I, args.temperature, pbar.update, direction)
print("\n")
result_stash[I] = search_map
outpath = path.join(args.outputdir, str.format("Searchmap_I{}_{}.png", I, direction))
dmplots.plot_search_map(
search_map, (zrange[0], zrange[-1]), (cvfrange[0], cvfrange[-1]), I, direction, outpath
)
outpath = path.join(args.outputdir, str.format("Searchmap_I{}_{}.csv", I, direction))
