Added exponential distribution of seed photons for the ODE method (7907ceea) · Commits · polarization / slab

compute_stokes.c

+7 −7

Original line number	Diff line number	Diff line
		@@ -55,9 +55,9 @@ void compute_stokes(double ene, double* k_lab, double* polvect_cart, stokes_para
		exit(1);
		}

		ptr_stokes[ii].array_Is[jj] = ptr_stokes[ii].array_Is[jj] + 1;
		ptr_stokes[ii].array_Qs[jj] = ptr_stokes[ii].array_Qs[jj] + Qs;
		ptr_stokes[ii].array_Us[jj] = ptr_stokes[ii].array_Us[jj] + Us;
		ptr_stokes[ii].array_I[jj] = ptr_stokes[ii].array_I[jj] + 1;
		ptr_stokes[ii].array_Q[jj] = ptr_stokes[ii].array_Q[jj] + Qs;
		ptr_stokes[ii].array_U[jj] = ptr_stokes[ii].array_U[jj] + Us;
		ptr_stokes[ii].counter[jj]++;

		FlagFound = TRUE;
		@@ -103,11 +103,11 @@ void compute_stokes(double ene, double* k_lab, double* polvect_cart, stokes_para

		for (ii = 0; ii < POLAR_NBOUNDS - 1; ii++)
		{
		Itot_allbands = Itot_allbands + ptr_stokes[ii].array_Is[jj];
		Itot_allbands = Itot_allbands + ptr_stokes[ii].array_I[jj];

		Qtot = Qtot + ptr_stokes[ii].array_Qs[jj];
		Utot = Utot + ptr_stokes[ii].array_Us[jj];
		Itot = Itot + ptr_stokes[ii].array_Is[jj];
		Qtot = Qtot + ptr_stokes[ii].array_Q[jj];
		Utot = Utot + ptr_stokes[ii].array_U[jj];
		Itot = Itot + ptr_stokes[ii].array_I[jj];

		if (isnan(Qtot))
		{

main_program.c

+2 −1

Original line number	Diff line number	Diff line
		@@ -58,7 +58,8 @@ int main(int argc, char* argv[])
		printf("\nSeed photons distributions: three options are possible with parameter seed=N\n");
		printf("1: photons at the center of the slab\n");
		printf("2: photons uniform distribution\n");
		printf("3: photons at the base (valid only for ode and mc methods)\n\n");
		printf("3: photons at the base (valid only for ode and mc methods)\n");
		printf("4: photons with exponential distribution (valid only for ode and mc methods)\n\n");

		printf("Parameters for iteration algorithms\n");

mc_slab.c

+3 −3

Original line number	Diff line number	Diff line
		@@ -341,13 +341,13 @@ int slab_mc(int nphot, int seed)

		for (ii = 0; ii < POLAR_NBOUNDS - 1; ii++)
		{
		MPI_Reduce(struct_stokes[ii].array_Is, struct_stokes_average[ii].array_Is, nstepangles,
		MPI_Reduce(struct_stokes[ii].array_I, struct_stokes_average[ii].array_I, nstepangles,
		MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);

		MPI_Reduce(struct_stokes[ii].array_Qs, struct_stokes_average[ii].array_Qs, nstepangles,
		MPI_Reduce(struct_stokes[ii].array_Q, struct_stokes_average[ii].array_Q, nstepangles,
		MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);

		MPI_Reduce(struct_stokes[ii].array_Us, struct_stokes_average[ii].array_Us, nstepangles,
		MPI_Reduce(struct_stokes[ii].array_U, struct_stokes_average[ii].array_U, nstepangles,
		MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);

		MPI_Reduce(struct_stokes[ii].counter, struct_stokes_average[ii].counter, nstepangles, MPI_INT,

plot_data.py

0 → 100755

+53 −0

Original line number	Diff line number	Diff line
		import numpy as np
		import matplotlib.pyplot as plt
		from mpl_toolkits.mplot3d import Axes3D

		def read_data(file_path):
		"""
		Read the data from the input file and extract X, Y, and Z values.
		Assumes the data format is X Y Z in each line.
		"""
		X, Y, Z = np.loadtxt(file_path, unpack=True)
		return X, Y, Z

		def plot_3d_histogram(X, Y, Z, bins_x, bins_y):
		"""
		Plot a 3D histogram using bar3d with square bins.
		"""
		H, xedges, yedges = np.histogram2d(X, Y, bins=[bins_x, bins_y])
		X, Y = np.meshgrid(xedges[:-1], yedges[:-1])

		# Set the widths and depths of the bars to make them square
		dx = (xedges[1] - xedges[0])
		dy = (yedges[1] - yedges[0])

		fig = plt.figure()
		ax = fig.add_subplot(111, projection='3d')

		# Flatten the arrays
		X = X.ravel()
		Y = Y.ravel()
		Z = np.zeros_like(X)
		dx = np.full_like(X, dx)
		dy = np.full_like(X, dy)

		ax.bar3d(X, Y, Z, dx, dy, H.ravel(), shade=True)
		ax.set_xlabel('X')
		ax.set_ylabel('Y')
		ax.set_zlabel('Frequency')
		ax.set_title('3D Histogram of Z(x, y)')
		plt.show()

		if __name__ == "__main__":
		# Path to the input file (replace with your file path)
		file_path = 'data.txt'

		# Read data from the input file
		X, Y, Z = read_data(file_path)

		# Number of bins for X and Y axes
		bins_x = 40 # Adjust as needed
		bins_y = 40 # Adjust as needed

		# Plot the 3D histogram
		plot_3d_histogram(X, Y, Z, bins_x, bins_y)

solve_rte.c

+48 −0

Original line number	Diff line number	Diff line
		@@ -4,6 +4,9 @@
		double I0_center_updown(double tau, double u);
		double I0_upward(double tau, double u);
		double I0_uniform_updown(double tau, double u);
		double I0_exp_upward(double tau, double u);
		double I0_exp_downward(double tau, double u);


		void set_spline2d_obj(gsl_spline2d* Spline_I2d, double* za, double** I_funct);
		int set_array_idx(double tau_prev, double tau, double* array, int nstep);
		@@ -117,6 +120,19 @@ int solve_rte(int k_iter, int seed_distribution, int Nstep_tau)
		ptr_Iklr[0].Il_matrix_downstream[ii][jj] = 0;
		ptr_Iklr[0].Ir_matrix_downstream[ii][jj] = 0;
		}

		else if (seed_distribution == SEED_EXP)
		{
		ptr_Iklr[0].Il_matrix_upstream[ii][jj] = I0_exp_upward(array_tau[ii], array_mu[jj]);
		ptr_Iklr[0].Ir_matrix_upstream[ii][jj] = I0_exp_upward(array_tau[ii], array_mu[jj]);

		ptr_Iklr[0].Il_matrix_downstream[ii][jj] = I0_exp_downward(array_tau[ii], array_mu[jj]);
		ptr_Iklr[0].Ir_matrix_downstream[ii][jj] = I0_exp_downward(array_tau[ii], array_mu[jj]);


		}


		else
		{
		printf(
		@@ -361,6 +377,38 @@ int RTE_Equations(double s, const double y[], double f[], void* params)
		return GSL_SUCCESS;
		}


		/====================================================================/
		/Value of the I^k(tau,u) function for k=0 and seed photons/
		/with exponential distribution for u > 0 and u < 0/
		/====================================================================/

		double I0_exp_upward(double tau, double u)
		{
		double value;

		value= ((-1 + exp(((-1 + u) * tau) / u))) /
		(2.0 * exp(tau) * (-1 + u));

		return value;

		}


		double I0_exp_downward(double tau, double u)
		{
		double value;

		value=(exp(-2 * tau0) * (exp(tau) - exp(-tau / u))) /
		(2.0 * (1 + u));


		return value;

		}



		/====================================================================/
		/Value of the I^k(tau,u) function for k=0 and seed photons/
		/at the base of the slab (tau=0)/