Wed 28 Aug 21:38:52 CEST 2024

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sbosse 2024-08-28 21:38:59 +02:00
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#!/usr/bin/env python
# encoding: utf-8
"""
inspection.py
Created by Miguel Molero on 2013-09-26.
Copyright (c) 2013 MMolero. All rights reserved.
"""
import numpy as np
def setEmisor(Theta, Size, x2, y2, X0, Y0):
Ntheta = np.size(Theta, 0)
NXL = int(2.0 * Size)
xL = np.zeros((NXL,), dtype=np.float32)
yL = np.zeros((NXL,), dtype=np.float32)
for m in range(0, Ntheta):
if np.abs(np.cos(Theta[m])) < 1e-5:
yL = np.arange(y2[m] - Size, y2[m] + Size)
xL[:] = x2[m] * np.ones((NXL,), dtype=np.float32)
elif np.abs(np.cos(Theta[m])) == 1:
xL[:] = np.arange(x2[m] - Size, x2[m] + Size)
yL[:] = y2[m] - ((x2[m] - X0) / (y2[m] - Y0)) * (xL[:] - x2[m])
else:
xL[:] = np.linspace(x2[m] - (Size * np.abs(np.cos(Theta[m]))), x2[m] + (Size * np.abs(np.cos(Theta[m]))),
num=NXL, endpoint=True)
yL = y2[m] - ((x2[m] - X0) / (y2[m] - Y0)) * (xL[0:NXL] - x2[m])
if m == 0:
XL = np.zeros((np.size(xL, 0), Ntheta), dtype=np.float32)
YL = np.zeros((np.size(xL, 0), Ntheta), dtype=np.float32)
XL[:, m] = np.int32((xL[0:np.size(xL, 0)]))
YL[:, m] = np.int32((yL[0:np.size(xL, 0)]))
return XL, YL
def centerOffset(XL, YL, Theta, Scenario, transducer, Ratio):
Ntheta = np.size(Theta, 0)
if transducer.Location == "Top":
YL += np.int32(transducer.CenterOffset * Scenario.Pixel_mm * Ratio)
elif transducer.Location == "Left":
XL += np.int32(transducer.CenterOffset * Scenario.Pixel_mm * Ratio)
IR = np.zeros((Ntheta, Ntheta), dtype=np.float32)
B = range(0, Ntheta)
IR[:, 0] = np.int32(B[:])
for i in range(1, Ntheta):
B = np.roll(B, -1)
IR[:, i] = np.int32(B)
return XL, YL, IR
def borderOffset(XL, YL, Scenario, transducer, Ratio):
if transducer.Location == "Top":
XL[:, 0] += (np.int32(transducer.BorderOffset * Scenario.Pixel_mm * Ratio))
XL[:, 1] -= (np.int32(transducer.BorderOffset * Scenario.Pixel_mm * Ratio))
elif transducer.Location == "Left":
YL[:, 0] += (np.int32(transducer.BorderOffset * Scenario.Pixel_mm * Ratio))
YL[:, 1] -= (np.int32(transducer.BorderOffset * Scenario.Pixel_mm * Ratio))
return XL, YL
def flip(XL):
return np.fliplr(XL)
def getReceivers(XL, YL, IR, T, Field):
ReceptorX = (XL)
ReceptorY = (YL)
M, N = np.shape(ReceptorX)
temp = np.zeros((M, N - 1), dtype=np.float32)
for mm in range(0, M):
for ir in range(0, N - 1):
temp[mm, ir] = T[int(ReceptorX[mm, int(IR[0, ir + 1])]), int(ReceptorY[mm, int(IR[0, ir + 1])])]
if Field:
return temp.transpose()
else:
return np.mean(temp, 0)