map images with z-axis scaled by k

PI/20153006/parse_data_kscaled.py

+import h5py
+import numpy as np
+import pickle
+import os.path
+import pylab
+import matplotlib
+from scipy.interpolate import griddata
+from pykat.optics.maps import surfacemap
+              
+xi = np.linspace(-0.17, 0.17, 200)
+yi = np.linspace(-0.17, 0.17, 200)
+
+mode = 0
+####rescaling to [m]/[N] units
+E = 72.6e9#Pa = kg/m/s**2
+r1 = 0.17#m
+r2 = 0.16325#m
+A1 = np.pi*r1**2
+A2 = r2**2
+A = 0.5*(A1 + A2)
+d = 0.2#m
+kval = E*A/d
+####
+
+files = ["./raw/aLIGO_0-47kHz_surface.txt", "./raw/aLIGO_47-60kHz_surface.txt"] 
+eigenfreqs = np.loadtxt("./raw/aLIGO_eigenmodes.txt", dtype=np.float64)
+
+for f in files:
+    
+    D = np.loadtxt(f, comments="%")
+    
+    x,y,z = (D[:, 0], D[:, 1], D[:, 2]) # get x,y,z
+    
+    U = D[:, 3::3]
+    
+    for i in range(U.shape[1]):
+        zi = griddata((y, z), U[:, i],(xi[None,:], xi[:,None]), method='cubic')
+        zi = np.ma.array (zi, mask=np.isnan(zi))
+        cmap = matplotlib.cm.jet
+        cmap.set_bad('w',0.)
+
+        fig = pylab.figure(figsize=(7,6))
+
+        l = pylab.pcolormesh(xi/1e-2,yi/1e-2,zi/(kval/1e12))
+        l.set_zorder(100)
+        l.set_rasterized(True)
+        
+        pylab.grid(zorder=-100)
+        pylab.axes().set_aspect('equal', 'datalim')
+
+        pylab.xlabel("x [cm]")
+        pylab.ylabel("y [cm]")
+        pylab.title("Eigenmode=%i, f=%g [Hz]" % (mode, eigenfreqs[mode]))
+        
+        cb = pylab.colorbar()
+        cb.set_label("Surface displacement [pm/N]")
+        cb.solids.set_rasterized(True)
+        
+        pylab.tight_layout()
+        pylab.savefig("./images_kscaled/aligo_mode_%i.pdf" % mode, bbox_inches='tight', dpi=300)
+        pylab.close()
+        
+        mode += 1
+        
+        print(mode)
+    
+    
+    
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