dielectrics bulk loss corrected

Examples/startHREELS_Browser.py

@@ -3,7 +3,7 @@ import sys
 import matplotlib.pyplot as plt
 import numpy as np
 
-datapath = "./data"
-# datapath = "./Examples/data"
+# datapath = "./data"
+datapath = "./Examples/data"
 
 ViewHREELS.runViewer(datapath=datapath, startWithFile='c1a03')
\ No newline at end of file

libhreels/__init__.py

-__version__ = "1.0.8"
+__version__ = "1.1.0"

libhreels/analysizeData.py

+import numpy as np
+from matplotlib import pyplot as plt
+
+def findPeriod(list, period):
+    '''For a list of times (relative to a sync pulse) calculate the average time deviation squared.  
+    '''
+    residuum = []
+    sum_residuum = 0
+    for each in list:
+        r = each % period
+        residuum.append(r)
+        sum_residuum += r
+    av_res = sum_residuum / len(list)
+    deviation = 0
+    for res in residuum:
+        deviation += (res - av_res)**2
+    deviation /= (len(residuum)*period**2)
+    return deviation, av_res
+
+def makeTimeRelative(times, durations):
+    list = []
+    synced = False
+    t_zero = 0
+    for each in pulses:
+        if synced:
+            list.append(pulses[each][0]-t_zero)
+        if 9000 < pulses[each][2] < 9800:
+            print("synced")
+            t_zero = pulses[each][0]
+            synced = True
+    return list
+
+data = []       # read dat from file [[time in microsec, low duration, high duration], [...], ...]
+with open("data433_Signal2.txt", 'r') as f:
+    for line in f:
+        data.append([int(each) for each in line.split(',')])
+
+sumOn = 0; sumOff = 0
+for pulse in data[1:]:
+    sumOn += pulse[2]
+    sumOff += pulse[1]
+sumOn /= len(data)
+sumOff /= len(data)
+
+print("Average on and off times:", sumOn, sumOff)

libhreels/calcHREELS.py

@@ -46,7 +46,7 @@ except:
 
 class lambin:
     def __init__(self, film, setup=setup, instrument=instrument):
-        if not sys.version.startswith('3.6'):
+        if not (sys.version.startswith('3.6') or sys.version.startswith('3.8')):
             print('''Make sure the Fortran routines 'myEels2' and 'myBoson' 
             have been complied with the proper f2py3 for the right 
             python version!!''') 
@@ -124,7 +124,8 @@ class lambin:
             emin,emax,wmin,wmax,loss_array,self.debug,len(loss_array))
         if normalized:
             norm = max(spectrum[:n])
-        return xOut[:n], spectrum[:n]/norm
+        # return xOut[:n], spectrum[:n]/norm
+        return xOut[:len(x)], spectrum[:len(x)]/norm
 
     def calcEps(self, x):
         epsArray = []

libhreels/dielectrics.py

@@ -18,7 +18,7 @@ def doping2surfacePlasma(doping,epsInfinity=1.):
     return np.sqrt(doping)*1.8817885780819758e-06/np.sqrt(1+epsInfinity)
 
 def loss(eps):
-    return -np.imag(eps)
+    return np.imag(1/eps)
 
 def surfaceLoss(eps):
     return np.imag(1/(1+eps))
@@ -28,14 +28,13 @@ def reflectivity(eps):  # IR reflectivity
     a =np.abs((sq-1)/(sq+1))
     return a*a
 
-def sigma(eps,w):       # Complex conductivity (ignored factor eps_0)
-    return (eps-1)*w/1j
+def sigma(eps,w,eps_Infinity=1):       # Complex conductivity 
+    return np.imag((eps-eps_Infinity)*w)
 
 def plotDielectrics(x,eps):
-    fig, axs = plt.subplots(3, 1, sharex=True)
-    axs[0].plot(x, loss(eps), label='Loss function')
-    axs[0].plot(x, np.real(eps), label='Re( $\epsilon (\omega )$ )')
-    axs[0].legend()
+    fig, axs = plt.subplots(3, 1, sharex=True, figsize=(6,6))
+    axs[0].plot(x, -np.imag(eps), label='-Im $\epsilon (\omega )$')
+    axs[0].plot(x, np.real(eps), label='Re $\epsilon (\omega )$')    axs[0].legend()
     axs[0].set_ylabel('Dielectric Function')
 
     axs[1].plot(x, surfaceLoss(eps), lineStyle='-')    
@@ -49,7 +48,6 @@ def plotDielectrics(x,eps):
     axs[0].set_xlim(left=0, right=max(x))
 
     plt.show()
-
 class oscillator:
     def __init__(self, wTO, wLO, gammaTO=20, gammaLO=20):
         self.wTO = wTO

pyproject.toml

 [tool.poetry]
 name = "libhreels"
-version = "1.0.8"
+version = "1.1.1"
 description = "Handling, simulating, and plotting HREELS and Auger spectroscopy data"
 authors = ["Wolf Widdra <wolf.widdra@physik.uni-halle.de>"]
 include = ["*./libhreels/*"]