From 329639e0645b57cf2203f6045da899dac696bd60 Mon Sep 17 00:00:00 2001 From: brahim Date: Wed, 5 Mar 2025 13:40:22 +0100 Subject: [PATCH] granulo loader program is cleaned from useless commented lines and useless print --- Model/granulo_loader.py | 149 +--------------------------------------- 1 file changed, 1 insertion(+), 148 deletions(-) diff --git a/Model/granulo_loader.py b/Model/granulo_loader.py index 8870afc..95a3ed0 100644 --- a/Model/granulo_loader.py +++ b/Model/granulo_loader.py @@ -1,7 +1,5 @@ -import matplotlib.pyplot as plt import numpy as np import pandas as pd -from Model.GrainSizeTools import demodul_granulo, mix_gaussian_model class GranuloLoader: @@ -16,8 +14,7 @@ class GranuloLoader: self._y = self._data.iloc[:, 1].tolist() # distance from left bank (m) self._z = self._data.iloc[:, 2].tolist() # depth (m) - self._r_grain = 1e-6 * np.array(self._data.columns.values)[5:].astype(float) / 2 - # self._r_grain = 1e-6 * np.array(self._data.columns.values)[5:].astype(float) / 2 # grain radius (m) + self._r_grain = 1e-6 * np.array(self._data.columns.values)[5:].astype(float) / 2 # grain radius (m) self._Ctot = self._data.iloc[:, 3].tolist() # Total concentration (g/L) self._D50 = self._data.iloc[:, 4].tolist() # median diameter (um) @@ -25,147 +22,3 @@ class GranuloLoader: self._frac_vol_cumul = np.cumsum(self._frac_vol, axis=1) # Cumulated volume fraction (%) - # print(type(self._frac_vol_cumul), self._frac_vol_cumul.shape, self._frac_vol_cumul) - - # # --- Load sand sediments data file --- - # self.path_sand = path_sand - # self._data_sand = pd.read_excel(self.path_sand, engine="odf", header=0) - # - # self._Ctot_sand = np.array(self._data_sand.iloc[:, 2]) # Total concentration (g/L) - # self._D50_sand = np.array(self._data_sand.iloc[:, 3]) # median diameter (um) - # self._frac_vol_sand = np.array(self._data_sand.iloc[:, 4:]) # Volume fraction (%) - # - # self._frac_vol_sand_cumul = np.cumsum(self._frac_vol_sand, axis=1) # Cumulated volume fraction (%) - # - # # --- Compute % of fine and % of sand sediment in total concentration --- - # - # self._Ctot_fine_per_cent = 100 * self._Ctot_fine / (self._Ctot_fine + self._Ctot_sand) - # self._Ctot_sand_per_cent = 100 * self._Ctot_sand / (self._Ctot_fine + self._Ctot_sand) - - # ============================================================================================================== - # ============================================================================================================== - -# N_sample = 0 -# # -# fig, ax = plt.subplots(1, 2) -# ax[0].plot(self._r_grain, self._frac_vol[N_sample, :], color="k", marker='.') -# ax[0].set_xscale('log') -# ax[0].set_xlabel('Radius ($\mu m$)') -# ax[0].set_ylabel('Class size volume fraction') -# -# ax[1].plot([self._r_grain[i+1]-self._r_grain[i] for i in range(self._r_grain.shape[0]-1)], list(range(self._r_grain.shape[0]-1)), color="k", marker="x") -# ax[1].set_xlabel('Ecart inter-class') -# ax[1].set_ylabel('n° échantillon') -# -# plt.show() -# -# print(f"self._r_grain.shape : {self._r_grain.shape}") -# print(f"self._r_grain : {self._r_grain}") -# print(f"self._frac_vol_cumul.shape : {self._frac_vol_cumul[N_sample, :].shape}") -# print(f"self._frac_vol_cumul[N_sample, :] : {self._frac_vol_cumul[N_sample, :]}") -# print(np.where(self._frac_vol_cumul[N_sample, :] > 0)) -# # -# min_demodul = 1e-6 -# max_demodul = 500e-6 -# sample_demodul = demodul_granulo(self._r_grain[:], -# self._frac_vol_cumul[N_sample, :], -# min_demodul, max_demodul) -# -# print(f"sample_demodul : {sample_demodul.demodul_data_list}") - -# N_modes = 3 -# sample_demodul.print_mode_data(N_modes) -# sample_demodul.plot_interpolation() -# sample_demodul.plot_modes(N_modes) -# -# print(f"mu_list : {sample_demodul.demodul_data_list[3 - 1].mu_list}") -# print(f"sigma_list : {sample_demodul.demodul_data_list[3 - 1].sigma_list}") -# print(f"w_list : {sample_demodul.demodul_data_list[3 - 1].w_list}") -# -# resampled_log_array = np.log(np.logspace(-10, -2, 3000)) -# proba_vol_demodul = mix_gaussian_model(resampled_log_array, -# sample_demodul.demodul_data_list[2].mu_list, -# sample_demodul.demodul_data_list[2].sigma_list, -# sample_demodul.demodul_data_list[2].w_list) -# -# -# -# proba_vol_demodul = proba_vol_demodul / np.sum(proba_vol_demodul) -# ss = np.sum(proba_vol_demodul / np.exp(resampled_log_array) ** 3) -# proba_num = proba_vol_demodul / np.exp(resampled_log_array) ** 3 / ss -# -# print(f"proba_num : {proba_num}") -# freq = 5e6 -# -# a2f2pdf = 0 -# a3pdf = 0 -# for i in range(len(resampled_log_array)): -# a = np.exp(resampled_log_array)[i] -# a2f2pdf += a**2 * form_factor_function_MoateThorne2012(a, freq)**2 * proba_num[i] -# a3pdf += a**3 * proba_num[i] -# -# print(f"a2f2pdf = {a2f2pdf}") -# print(f"a3pdf = {a3pdf}") -# -# ks = (a2f2pdf / a3pdf) -# -# print(f"ks = {ks}") -# -# -# def form_factor_function_MoateThorne2012(a_s, freq, C=1500): -# """This function computes the form factor based on the equation of -# Moate and Thorne (2012)""" -# # computing the wave number -# k = 2 * np.pi * freq / C -# x = k * a_s -# f = (x ** 2 * (1 - 0.25 * np.exp(-((x - 1.5) / 0.35) ** 2)) * ( -# 1 + 0.6 * np.exp(-((x - 2.9) / 1.15) ** 2))) / ( -# 42 + 28 * x ** 2) -# return f - - -# if __name__ == "__main__": -# GranuloLoader("/home/bmoudjed/Documents/2 Data/Confluence_Rhône_Isere_2018/Granulo_data/fine_sample_file.ods") - # GranuloLoader("/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/Granulo_data/" - # "sand_sample_file.ods") - # GranuloLoader("/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/" - # "pt_acoused_cnr_7nov2023/echantil/fine_new_file_acoused_101RDS 3.ods") - # GranuloLoader("/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/" - # "pt_acoused_cnr_7nov2023/echantil/sand_new_file_acoused_101RDS 3.ods") - - - - - - - - - - -# # form_factor = form_factor_function_MoateThorne2012(GranuloLoader.) -# -# def ks(a_s, rho_s, freq, pdf): -# # --- Calcul de la fonction de form --- -# form_factor = form_factor_function_MoateThorne2012(a_s, freq) -# print(f"form_factor shape = {len(form_factor)}") -# # print(f"form_factor = {form_factor}") -# -# # --- Gaussian mixture --- -# # sample_demodul = demodul_granulo(a_s.astype(float), pdf, 0.17e-6, 200e-6) -# # sample_demodul.plot_interpolation() -# -# # ss = np.sum(pdf / a_s ** 3) -# # proba_num = (pdf / a_s ** 3) / ss -# -# # --- Compute k_s by dividing two integrals --- -# a2f2pdf = 0 -# a3pdf = 0 -# for i in range(len(pdf)): -# a2f2pdf += a_s[i] ** 2 * form_factor[i] * proba_num[i] -# a3pdf += a_s[i] ** 3 * proba_num[i] -# -# ks = np.sqrt(a2f2pdf / (rho_s * a3pdf)) -# -# # ks = np.array([0.04452077, 0.11415143, 0.35533713, 2.47960051]) -# # ks = ks0[ind] -# return ks \ No newline at end of file