import matplotlib.pyplot as plt import numpy as np from matplotlib.colors import LogNorm import csv from matplotlib import cbook import matplotlib.ticker as mticker #import hole data with open('700-1000_direct.csv', newline='') as f: #with open('400-700_holes_direct.csv', newline='') as f: reader = csv.reader(f) hole_list = list(reader) maxw=len(hole_list) #find indices of different fluence percent index10=[] index50=[] index90=[] index1=[] index01=[] index37=[] for k in range(maxw): #loop through each wavelength v10=min(range(len(hole_list[k])), key=lambda i: abs(float(hole_list[k][i])- 0.1)) #find 10% v50=min(range(len(hole_list[k])), key=lambda i: abs(float(hole_list[k][i])- 0.5)) #find 50% v90=min(range(len(hole_list[k])), key=lambda i: abs(float(hole_list[k][i])- 0.9)) #find 90% v1=min(range(len(hole_list[k])), key=lambda i: abs(float(hole_list[k][i])- 0.01)) #find 50% v01=min(range(len(hole_list[k])), key=lambda i: abs(float(hole_list[k][i])- 0.001)) #find 0.1% v37=min(range(len(hole_list[k])), key=lambda i: abs(float(hole_list[k][i])- 0.37)) #find 37% index10.append(v10) index50.append(v50) index90.append(v90) index1.append(v1) index01.append(v01) index37.append(v37) #create arrays of different fluence percentage values #10% left ten=[] for i in range(maxw): ten.append(hole_list[i][index10[i]]) #50% left fiftey=[] for i in range(maxw): fiftey.append(hole_list[i][index50[i]]) #90% left ninety=[] for i in range(maxw): ninety.append(hole_list[i][index90[i]]) #1% left one=[] for i in range(maxw): one.append(hole_list[i][index1[i]]) #37% left thirsev=[] for i in range(maxw): thirsev.append(hole_list[i][index37[i]]) #0.1% left pone=[] for i in range(maxw): pone.append(hole_list[i][index01[i]]) #print(ten, fiftey, ninety) xmax=0.05 ymax=0.05 zlength=0.5 #cm znumber=800 zvoxel_length=zlength/znumber #cm xlength=0.1 #cm xnumber=100 xvoxel_length=(xlength/xnumber)*10 #mm wavelength=np.arange(400,701) xdepth=[] depth=[] for i in range(xnumber): idepth=(i*xvoxel_length) #cm xdepth.append(idepth) zmax=0.25 sc_width=0.002 e_width=0.0053 m_width=0.0032 b_width=0.0032 d_width=0.1970 h_width=0.3 sc_z_vox=200 e_z_vox=100 m_z_vox=100 b_z_vox=100 d_z_vox=150 h_z_vox=150 sc_nzg= (2.*zmax)/(sc_width/sc_z_vox) e_nzg= (2.*zmax)/(e_width/e_z_vox) m_nzg=(2.*zmax)/(m_width/m_z_vox) b_nzg= (2.*zmax)/(b_width/b_z_vox) d_nzg= (2.*zmax)/(d_width/d_z_vox) h_nzg= (2.*zmax)/(h_width/h_z_vox) dep=0. for i in range(0,200): dep=dep + ((2*zmax)/sc_nzg) # 10 converts to mm depth.append(dep) for i in range(200,300): dep=dep + ((2*zmax)/e_nzg) depth.append(dep) for i in range(300,400): dep=dep + ((2*zmax)/m_nzg) depth.append(dep) for i in range(400,500): dep=dep + ((2*zmax)/b_nzg) depth.append(dep) for i in range(500,650): dep=dep + ((2*zmax)/d_nzg) depth.append(dep) for i in range(650,800): dep=dep + ((2*zmax)/h_nzg) depth.append(dep) for i in range(800): depth[i]=depth[i]*10 #create arrays of different depth values at percentages #10% left dten=[] for i in range(maxw): dten.append(depth[index10[i]]) #50% left dfiftey=[] for i in range(maxw): dfiftey.append(depth[index50[i]]) #90% left dninety=[] for i in range(maxw): dninety.append(depth[index90[i]]) #1% left done=[] for i in range(maxw): done.append(depth[index1[i]]) #0.1% left dpone=[] for i in range(maxw): dpone.append(depth[index01[i]]) #37% left dpthirsev=[] for i in range(maxw): dpthirsev.append(depth[index37[i]]) #print(dten) print(max(dpone)) #tells us the max depth to create layer image print(dpthirsev[100]) CB_color_cycle = ['#377eb8', '#ff7f00', '#4daf4a', '#f781bf', '#a65628', '#984ea3', '#999999', '#e41a1c', '#dede00'] #image = plt.imread('layerimage-200-400nm.png') #plt.imshow(image) #cutimage=dslice[:799,:100] #plt.pcolormesh(xdepth[:100],depth[:799],cutimage)#, cmap='OrRd') plt.plot(wavelength[:maxw], dninety,color='#f781bf',linestyle='-', linewidth=4)#, label=('90%')) plt.plot(wavelength[:maxw], dfiftey,color='#4daf4a',linestyle='--',linewidth=4)#, label=('50%')) plt.plot(wavelength[:maxw], dten,color='#ff7f00',linestyle=':',linewidth=4.0)#, label=('10%')) plt.plot(wavelength[:maxw], done,color='#e41a1c',linestyle='-.',linewidth=4.0)#, label=('1%')) plt.plot(wavelength[:maxw], dpone,color='k',linestyle=(0,(3,1,1,1,1,1)),linewidth=4)#, label=('0.1%')) #plt.plot((300,300),(0.015,0.03),color='k',marker='_',label='in vivo') #plt.plot((340,340),(0.04,0.06),color='k',marker='_',label='in vivo') #plt.plot((300),(0.015),color='r',marker='x',label='in vivo') #plt.plot((340),(0.054),color='r',marker='x',label='in vivo') plt.plot((532,532),(0,5.1),color='r')#,label='KTP') plt.plot((595,595),(0,5.1),color='r')#,label='PDL') #plt.plot((400),(1),color='k',marker='X',markersize=10)#,label='in vivo') #plt.plot((450),(1.6),color='k',marker='X',markersize=10)#,label='in vivo') #plt.plot((550),(3),color='k',marker='X',markersize=10,label='Ash et al. Data') #upload layer image #im = plt.imread('layerimage-200-400nm.png'); #ext=[200, 400, 0, max(dpone)] #plt.imshow(im, zorder=0, extent=ext) im = plt.imread('layerimage-400-700nm.png'); ext=[400, 700, 0, max(dpone)] plt.imshow(im, zorder=0, extent=ext) aspect=im.shape[0]/float(im.shape[1])*((ext[1]-ext[0])/(ext[3]-ext[2])) plt.gca().set_aspect(aspect) ax=plt.gca() #ax.set_yscale('log') ax.yaxis.set_major_formatter(mticker.ScalarFormatter()) ax.yaxis.get_major_formatter().set_scientific(False) ax.yaxis.get_major_formatter().set_useOffset(False) ax.yaxis.set_major_formatter(mticker.FormatStrFormatter('%.f')) #plt.legend() #plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0.,fontsize=20) #plt.title('Percentage of Incident Light at depth') #plt.xlabel('Wavelength (nm)') #plt.xscale('log') #plt.yscale('log') plt.gca().invert_yaxis() #plt.ylabel('Depth (mm)') plt.xticks(fontsize=17) plt.yticks(fontsize=17) plt.savefig('percen_400-700_dir_ash_depth_mark.png',format='png', dpi=1200,bbox_inches='tight') plt.show() #cutimage=dslice[:605,:100] #plt.pcolormesh(xdepth[:100],depth[:605],cutimage, cmap='OrRd') #plt.xlabel('x (mm)') #plt.ylabel('z (mm)') #plt.gca().invert_yaxis() #plt.title('Fluence through a Cut Irradiated by Direct 400nm') #plt.colorbar() #plt.show()