def r_s_from_grid(grid,
grid_pts,
minimum_distance_between_speakers=1.2,
max_distance_from_wall=0.6):
ymax = np.amax(grid.nos[:, 1])
y_start = ymax * 0.7
y_end = ymax * 0.85
y_space = np.linspace(y_start, y_end, grid_pts[1])
y_height = 1.2
a = grid.nos
xmax = []
for i in y_space:
b = a[(a[:, 2] > y_height * .8) & (a[:, 2] < y_height * 1.2)]
b = b[(b[:, 1] > i * .8) & (b[:, 1] < i * 1.2)]
xmax.append(np.amax(b[:, 0]))
xmax = np.array(xmax)
x_end = xmax - max_distance_from_wall
x_start = np.ones_like(x_end) * (minimum_distance_between_speakers / 2)
x_space = []
for i in range(len(x_end)):
x_space.append(np.linspace(x_start[i], x_end[i], grid_pts[0]))
x_space = np.array(x_space)
s_coords_L = [] #np.zeros(grid_pts)
r_coords = []
# print(s_coords_L.shape)
# print(np.array([x_space[0],y_space[0],1.2]))
for i in range(grid_pts[0]):
x_spacei = x_space[:, i]
for ii in range(grid_pts[1]):
s_coords_L.append([x_spacei[i], y_space[ii], 1.2])
r_coords.append([
0, (y_space[ii]) - np.cos(np.deg2rad(30)) * x_spacei[i] * 2,
1.21
])
s_coords_L = np.array(s_coords_L)
s_coords_R = s_coords_L.copy()
s_coords_R[:, 0] = -s_coords_R[:, 0]
r_coords = np.array(r_coords)
Ro = []
So = []
for i in range(len(r_coords)):
R = fd.Receiver(coord=[r_coords[i]])
Ro.append(R)
S = fd.Source()
S.coord = np.array([[s_coords_L[i, :]], [s_coords_R[i, :]]])
S.q = np.array([[0.0001], [0.0001]])
So.append(S)
return So, Ro
def r_s_coord_pair(y_value, distance_s_r):
r_coord = np.array([0, y_value, 1.2])
hyp = distance_s_r
rad30 = np.deg2rad(30)
s_x = np.sin(rad30) * hyp
s_y = np.cos(rad30) * hyp + y_value
s_coord = np.array([[s_x, s_y, 1.2], [-s_x, s_y, 1.2]])
R = fd.Receiver()
R.star(r_coord, 0.15)
S = fd.Source()
S.coord = s_coord
S.q = np.array([[0.0001], [0.0001]])
return R, S
def r_s_positions(grid, grid_pts, bias):
xmax = np.amax(grid.nos[:, 0])
ymax = np.amax(grid.nos[:, 1])
x_start = xmax * 0.8 + bias[0]
x_end = xmax * 0.5 + bias[0]
y_start = ymax * 0.7 + bias[1]
y_end = ymax * 0.9 + bias[1]
y_space = np.linspace(y_start, y_end, grid_pts[1])
x_space = np.linspace(x_start, x_end, grid_pts[0])
s_coords_L = [] #np.zeros(grid_pts)
r_coords = []
# print(s_coords_L.shape)
# print(np.array([x_space[0],y_space[0],1.2]))
for i in range(grid_pts[0]):
for ii in range(grid_pts[1]):
s_coords_L.append([x_space[i], y_space[ii], 1.2])
r_coords.append([
0, (1 / y_space[ii]) * np.cos(np.deg2rad(30)) * x_space[i] * 2,
1.21
])
s_coords_L = np.array(s_coords_L)
s_coords_R = s_coords_L.copy()
s_coords_R[:, 0] = -s_coords_R[:, 0]
r_coords = np.array(r_coords)
Ro = []
So = []
for i in range(len(r_coords)):
R = fd.Receiver(coord=[r_coords[i]])
Ro.append(R)
S = fd.Source()
S.coord = np.array([[s_coords_L[i, :]], [s_coords_R[i, :]]])
S.q = np.array([[0.0001], [0.0001]])
So.append(S)
return So, Ro
# -*- coding: utf-8 -*-
"""
Created on Sat Nov 28 00:30:38 2020
@author: gutoa
"""
import femder as fd
import numpy as np
path_to_geo = "..\\Mshs\\FEM_3D\\cplx_room.geo"
AP = fd.AirProperties(c0=343)
AC = fd.AlgControls(AP, 20, 150, 1)
S = fd.Source("spherical")
S.coord = np.array([[-1, 2.25, 1.2], [1, 2.25, 1.2]])
S.q = np.array([[0.0001], [0.0001]])
R = fd.Receiver([0, 1, 1.2])
BC = fd.BC(AC, AP)
# BC.normalized_admittance(3,0.02)
tmm = fd.TMM(20, 200, 1)
tmm.porous_layer(sigma=10.9, t=150, model='db')
tmm.compute()
# BC.normalized_admittance(3,tmm.y_norm)
BC.mu[3] = (tmm.y)
# BC.delany(3,10900,0.15)
# BC.normalized_admittance(3,0.02+1j*0.5)