#%% LOAD VACUUM DATA
vacuum_path = os.path.join(home, vacuum_folder)
vacuum_file = lambda f, s: os.path.join(vacuum_path, f, s)
vacuum_series = os.listdir(vacuum_path)
vacuum_series = vu.filter_by_string_must(vacuum_series, "SC")
vacuum_series = vu.sort_by_number(vacuum_series, 0)
vacuum_data = []
vacuum_params = []
for s in vacuum_series:
vacuum_data.append(np.loadtxt(vacuum_file(s, "Results.txt")))
vacuum_params.append(vs.retrieve_footer(vacuum_file(s, "Results.txt")))
vacuum_header = vs.retrieve_header(vacuum_file(s, "Results.txt"))
vacuum_params = [vu.fix_params_dict(p) for p in vacuum_params]
#%% LOAD WATER DATA
water_path = os.path.join(home, water_folder)
water_file = lambda f, s: os.path.join(water_path, f, s)
water_series = os.listdir(water_path)
water_series = vu.filter_by_string_must(water_series, "AllWater")
water_series = vu.sort_by_number(water_series, 0)
water_data = []
water_params = []
for s in water_series:
path.append(os.path.join(home, f))
file.append(lambda f, s: os.path.join(path[-1], f, s))
series.append(os.listdir(path[-1]))
series[-1] = vu.filter_to_only_directories(series[-1])
series[-1] = vu.filter_by_string_must(series[-1], sm)
if smn != "": series[-1] = vu.filter_by_string_must(series[-1], smn, False)
series[-1] = sf(series[-1])
data.append([])
params.append([])
for s in series[-1]:
data[-1].append(np.loadtxt(file[-1](s, "Results.txt")))
params[-1].append(vs.retrieve_footer(file[-1](s, "Results.txt")))
header.append(vs.retrieve_header(file[-1](s, "Results.txt")))
for i in range(len(params[-1])):
if not isinstance(params[-1][i], dict):
params[-1][i] = vu.fix_params_dict(params[-1][i])
r = []
from_um_factor = []
resolution = []
paper = []
index = []
for p in params:
r.append([pi["r"] for pi in p])
from_um_factor.append([pi["from_um_factor"] for pi in p])
resolution.append([pi["resolution"] for pi in p])
try:
path = os.path.join(home, folder)
file = lambda f, s: os.path.join(path, f, s)
series = os.listdir(path)
series = vu.filter_to_only_directories(series)
series = vu.filter_by_string_must(series, series_must)
if series_mustnt != "":
series = vu.filter_by_string_must(series, series_mustnt, False)
series = sorting_function(series)
data = []
params = []
for s in series:
data.append(np.loadtxt(file(s, "Results.txt")))
params.append(vs.retrieve_footer(file(s, "Results.txt")))
data_header = vs.retrieve_header(file(s, "Results.txt"))
for i, p in enumerate(params):
if not isinstance(p, dict):
params[i] = vu.fix_params_dict(p)
midflux = []
for s in series:
midflux.append(np.loadtxt(file(s, "MidFlux.txt")))
midflux_header = vs.retrieve_header(file(s, "MidFlux.txt"))
endflux = []
for s in series:
endflux.append(np.loadtxt(file(s, "BaseResults.txt")))
endflux_header = vs.retrieve_header(file(s, "BaseResults.txt"))
#%% LOAD DATA
path = os.path.join(home, folder)
file = lambda f, s: os.path.join(path, f, s)
series = os.listdir(path)
series = vu.filter_by_string_must(series, recognize_string)
series = sorting_function(series)
data = []
params = []
for s in series:
data.append(np.loadtxt(file(s, "Results.txt")))
params.append(vs.retrieve_footer(file(s, "Results.txt")))
header = vs.retrieve_header(file(s, "Results.txt"))
params = [vu.fix_params_dict(p) for p in params]
r = [p["r"] for p in params]
from_um_factor = [p["from_um_factor"] for p in params]
#%% GET MAX WAVELENGTH
max_wlen = [data[i][np.argmax(data[i][:, 1]), 0] for i in range(len(data))]
#%% PLOT
colors = plab.cm.Blues(np.linspace(0, 1, len(series) + 3))[3:]
plt.figure()
# Saving directories
series = ["2020111101", "2020111103"]
folder = "AuMieResults"
home = "/home/vall/Documents/Thesis/ThesisPython/"
#%% LOAD DATA
file = lambda f, s: os.path.join(home, folder, "{}Results".format(s), f)
data = []
params = []
for s in series:
data.append(np.loadtxt(file("MidFlux.txt", s)))
params.append(vs.retrieve_footer(file("MidFlux.txt", s)))
header = vs.retrieve_header(file("MidFlux.txt", s))
r = [p["r"] for p in params]
resolution = [p["resolution"] for p in params]
from_um_factor = [p["from_um_factor"] for p in params]
until_after_sources = [p["until_after_sources"] for p in params]
#%% PLOT
new_series = ["F8"] #["", "F1", "F2"]
def proposed_factor(series, r, resolution, from_um_factor,
until_after_sources):
if series == "":
return 1
