added some python script examples

examples/cluster_example.py

@@ -17,7 +17,7 @@ emax=30
 ecutmin=8
 ecutmax=12
 etabins=251
-csize=2
+csize=3
 gain=150
 nbins=100
 indmin=1
@@ -78,6 +78,7 @@ for i in range(indmin,indmax):
 
 fig, ax = plt.subplots()
 ax.plot(ebins[:-1],sp)
+ax.plot(ebins[:-1],spff)
 #ax.set_yscale('log')
 fig.show()
 """

examples/clustersFunctions.py

@@ -49,6 +49,21 @@ for i in range(1,21):
     print(ff)
     r = cr.ClusterFileReader(ff)
 """
+def color_images(r, emin, emax, ebins, xmin, xmax, ymin, ymax,  images=None, csize=3,gain=150):
+    n=0
+    while (cl:=r.read(100000,None)).size:
+        v=cr.clusterize(csize,cl['data'])
+        vv=[cl['x'],cl['y'],v['tot']/gain]
+        image,bins=np.histogramdd(vv, bins=[xmax-xmin,yxmax-ymin,ebins], range=[[xmin,xmax-1],[ymin,ymax-1],[emin,emax]])
+
+        if images is None:
+            images = image.copy()  
+        else:
+            images=images+image
+        n+=v.shape[0]
+        #print(v.shape)
+        print("Read ",n," clusters",np.sum(images))
+    return images, bins
 
 
 def analyze_clusters(r, emin, emax, ecutmin, ecutmax, xmin, xmax, ymin, ymax,   ietax=None, ietay=None, im=None, sp=None, etas=None, intim=None, csize=3,gain=150, nbins=100, etabins=250, subpix=5):

examples/color_imaging.py

@@ -0,0 +1,47 @@
+import os, sys
+from pathlib import Path
+import matplotlib.pyplot as plt
+import numpy as np
+#from creader import ClusterFileReader
+import creader as cr
+import clustersFunctions as cf
+
+fname = "/mnt/myData/230914_30s_star_100um_nofi/star_"
+xmin=0
+xmax=400
+ymin=0
+ymax=400
+emin=0
+emax=30
+
+csize=3
+gain=150
+nbins=100
+indmin=1
+indmax=20
+
+
+
+im=None
+
+
+
+for i in range(indmin,indmax+1):
+    #ff=fname
+    ff=fname+str(i)+".clust"
+    print(ff)
+    r = cr.ClusterFileReader(ff)
+    im, bins=cf.color_images(r, emin, emax, nbins, xmin, xmax, ymin, ymax,   im, csize, gain)
+
+sp=np.sum(im,axis=(0,1))
+
+fig, ax = plt.subplots()
+ax.plot(bins[2][:-1],sp)
+##ax.set_yscale('log')
+fig.show()
+
+cu=np.sum(im[:,:,10:35],axis=2)
+cf.plot_colz(cu)
+
+mo=np.sum(im[:,:,50:70],axis=2)
+cf.plot_colz(mo)

examples/readClusters.py

@@ -0,0 +1,89 @@
+import numpy as np
+from numpy.lib import recfunctions as rfn
+import matplotlib.pyplot as plt
+import sys
+
+#energyStep=100
+energyMax=40000
+energyBins=400
+clusterSize=3
+
+dtypeCluster = [('frameNr', np.int32),('coord', (np.int16,2)),('data',(np.int32,clusterSize*clusterSize))]
+
+def read_cluster_file(filename):
+    fd = open(filename,'rb')
+    clusters = np.fromfile(fd,dtype=dtypeCluster)
+    fd.close
+    #rfn.drop_fields(clusters, 'frameNr')
+    uCl = rfn.structured_to_unstructured(clusters)
+    return uCl
+
+def getEnergyArray(data):
+    off=3
+    enArray = np.sum(data[:,off:], axis=-1)
+    print(data.shape)
+    Q = np.empty((4,data.shape[0]))
+    print(Q.shape, data.shape)
+    Q[0,:]=data[:,off+0]+data[:,off+1]+data[:,off+3]+data[:,off+4]
+    Q[1,:]=data[:,off+1]+data[:,off+2]+data[:,off+4]+data[:,off+5]
+    Q[2,:]=data[:,off+3]+data[:,off+4]+data[:,off+6]+data[:,off+7]
+    Q[3,:]=data[:,off+4]+data[:,off+5]+data[:,off+7]+data[:,off+8]
+    print(Q)
+    quadArray = np.max(Q,axis=0)
+    return enArray,quadArray
+
+def spectrum_roi(x,y,en,xmin,xmax,ymin,ymax):
+    global energyBins
+    global energymax
+    roi=np.where(np.logical_and(np.logical_and(np.logical_and(x>=xmin,x<=xmax),y>=ymin),y<=ymax))
+    spectrum3,xedges2=np.histogram(en[roi],bins=energyBins,range=(0,energyMax))
+    return spectrum3,xedges2[1:]
+
+def image_cut(x,y,en,emin,emax):
+    energyCut=np.where(np.logical_and(en>=emin,en<=emax))
+    print(x[energyCut].shape,y[energyCut].shape)
+    image,xedges,yedges=np.histogram2d(x[energyCut],y[energyCut],bins=400)
+    return image
+
+
+fname="/mnt/moench_data/tomcat_fluorescence_24022020/clusters_tomo/cu_fibers_27keV_17.clust"
+if len(sys.argv)>1:
+    fname=sys.argv[1]
+
+cl=read_cluster_file(fname)
+print("file read")
+
+enADC,quadADC=getEnergyArray(cl)
+print("energy array done",enADC,quadADC)
+
+en=enADC*1000./150.
+quad=quadADC*1000./150.
+print("energy conversion done:",en,quad)
+
+x=cl[:,1]
+y=cl[:,2]
+
+#him=get_hyperimage(x,y,cl)
+#print("hyperimage done")
+xmin=0
+xmax=400
+ymin=00
+ymax=400
+
+
+spectrum2,xedges1= spectrum_roi(x,y,quad,xmin,xmax,ymin,ymax)
+fig2, axs2 = plt.subplots()
+axs2.plot(xedges1,spectrum2,"b-")
+fig2.show()
+print("sp plotted")
+
+emin=0
+emax=40000
+image=image_cut(x,y,quad,emin,emax)
+fig, axs = plt.subplots()
+v=axs.imshow(image,vmax=np.mean(image)*5*np.sqrt(np.var(image)),origin='upper',cmap=plt.cm.jet)
+fig.colorbar(v, ax=axs)
+fig.show()
+
+print("To get the spectrum for a certain ROI use: sp,x=spectrum_roi(x,y,en,xmin,xmax,ymin,ymax)")
+print("To the get the image with a certain energy cut use im=image_cut(x,y,en,emin,emax)")