#%% 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