Wed 28 Aug 21:38:52 CEST 2024

src/SimNDT/gui/snapshots.py

@@ -0,0 +1,169 @@
+__author__ = 'Miguel Molero'
+
+import sys
+import numpy as np
+import matplotlib.pyplot as plt
+from  scipy.misc import imsave
+from scipy.io import savemat
+
+from SimNDT.gui.Warnings import WarningParms
+import math
+
+class SnapShots:
+    def __init__(self, Enable=False, Extension='.png', Step=200, Filename=None, dB=60, Color=0, 
+                       Field = 0,
+                       enableFields=False,
+                       enableSignals=False,
+                       enableImages=False,
+                       enableNumPy=False,
+                       enableVolume=False,
+                       enableView=False,
+                       sensorShape = [],
+                       sensorPlacement = [],
+                       sensorSize = 0):
+
+        self.IsEnable = Enable
+        self.Extension = Extension
+        self.Step = Step
+        self.Filename = Filename
+        self.DB = dB
+        self.Color = Color
+        self.Field = Field
+        self.enableFields   = enableFields
+        self.enableSignals  = enableSignals
+        self.enableImages   = enableImages
+        self.enableNumPy    = enableNumPy
+        self.enableVolume   = enableVolume
+        self.enableView     = enableView
+        self.sensorShape    = sensorShape
+        self.sensorPlacement = sensorPlacement
+        self.sensorSize      = sensorSize
+        self.volF = []
+        self.volS = []
+        self.volP = []
+
+    def save_fields(self, Fx, Fy, n):
+
+        if self.enableVolume:
+          self.volF.append(np.array([Fx,Fy]))
+        elif self.enableNumPy:
+          FILE = self.Filename + ("-fields-%05d" % (int(n / self.Step)))
+          np.save(FILE,np.array([Fx,Fy]))
+        else:  
+          dict = {}
+          dict['Vx'] = Fx
+          dict['Vy'] = Fy
+          FILE = self.Filename + ("-fields-%05d" % (int(n / self.Step))) + ".mat"
+          savemat(FILE, dict)
+
+    # @blab+
+    def save_signal(self, D , n, Label):
+        self.Label = Label       
+        xn = D.shape[1]
+        yn = D.shape[0]
+        dx = 1 # sensor delta
+        dy = 1
+        ox = 0 # offset
+        oy = 0
+        if len(self.sensorShape) > 0:
+          # size of sensor matrix
+          sx = self.sensorShape[0]
+          sy = self.sensorShape[1]
+          S = np.zeros([sy,sx])
+          if len(self.sensorPlacement):
+            p=self.sensorPlacement
+            ox=p[0]
+            dx=p[1]
+            oy=p[2]
+            dy=p[3]
+          else:
+            ox=dx=round(xn/(sx+1.0))
+            oy=dy=round(yn/(sy+1.0))
+          for x in range(0,sx):
+            for y in range(0,sy):
+              S[y,x]=D[oy+y*dy,ox+x*dx]
+        else:
+          S = D 
+
+        if self.enableVolume:
+          self.volS.append(np.copy(S))
+        elif self.enableNumPy:
+          FILE = self.Filename + ("-signal-"+Label+"-%05d" % (int(n / self.Step)))
+          np.save(FILE,S)
+        else:
+          FILE = self.Filename + ("-signal-"+Label+"-%05d" % (int(n / self.Step))) + ".mat"
+          savemat(FILE, S)
+
+    def save_power(self, Vx, Vy, n):
+        
+        S =  np.sqrt(Vx ** 2 + Vy ** 2)
+        
+        if self.enableVolume:
+          self.volP.append(np.copy(S))
+        elif self.enableNumPy:
+          FILE = self.Filename + ("-power-%05d" % (int(n / self.Step)))
+          np.save(FILE,S)
+        else:
+          FILE = self.Filename + ("-power-%05d" % (int(n / self.Step))) + ".mat"
+          savemat(FILE, S)
+
+    def save_fig(self, SV, n, idx=None):
+
+        SV += self.DB
+        ind = np.nonzero(SV < 0)
+        SV[ind] = 0
+        SV /= np.max(SV)
+
+        if self.Color == 0:
+            cmap = plt.get_cmap('jet')
+        elif self.Color == 1:
+            cmap = plt.get_cmap('gray')
+
+        try:
+            _resize = False
+            M, N = np.shape(SV)
+            if M >= 2000:
+                _resize = True
+            if N >= 2000:
+                _resize = True
+
+            if _resize:
+                SVV = SV[::3, ::3]
+                rgba_img = cmap(SVV)
+            else:
+                SVV = SV[::2, ::2]
+                rgba_img = cmap(SVV)
+
+            rgb_img = np.delete(rgba_img, 3, 2)
+
+            if idx is not None:
+                FILE = self.Filename + "_insp%d_" % idx + str(int(n / self.Step)) + self.Extension
+            else:
+                FILE = self.Filename + ("%05d" % (int(n / self.Step))) + self.Extension
+            imsave(FILE, rgb_img)
+
+        except:
+            msgBox = WarningParms("Too large Snapshots Size!!!!!!!!")
+            if msgBox.exec_():
+                sys.exit()
+
+    def save_vol(self):
+    
+        if len(self.volF) > 0:
+          if self.enableNumPy:
+            FILE = self.Filename + '-fields'
+            np.save(FILE,np.array(self.volF))
+            self.volF=[]
+            
+        if len(self.volS) > 0:
+          if self.enableNumPy:
+            FILE = self.Filename + '-signal-'+self.Label
+            np.save(FILE,np.array(self.volS))
+            self.volS=[]
+          
+        if len(self.volP) > 0:
+          if self.enableNumPy:
+            FILE = self.Filename + '-power'
+            np.save(FILE,np.array(self.volP))
+            self.volP=[]
+