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some polishing

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This commit is contained in:
stahn
2024-04-25 12:34:36 +02:00
parent 7336848424
commit ca81d4134b
1 changed files with 20 additions and 16 deletions
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life_histogrammer.py
+20 -16
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@@ -233,9 +233,14 @@ class PlotSelection:
# grids
def y_grid(self):
y_grid = np.arange(yMin, yMax+1, 1)
return y_grid
def lamda_grid(self):
dldl = 0.005 # Delta lambda / lambda
lamda_grid = lamdaMin*(1+dldl)**np.arange(int(np.log(lamdaMax/lamdaMin)/np.log(1+dldl)+1))
lMin = max(2, lamdaMin)
lamda_grid = lMin*(1+dldl)**np.arange(int(np.log(lamdaMax/lMin)/np.log(1+dldl)+1))
return lamda_grid
def theta_grid(self):
@@ -273,8 +278,7 @@ class PlotSelection:
cmap = mpl.cm.gnuplot(np.arange(256))
cmap[:1, :] = np.array([256/256, 255/256, 236/256, 1])
cmap = mpl.colors.ListedColormap(cmap, name='myColorMap', N=cmap.shape[0])
y_grid = np.arange(64)
I_yt, bins_y, bins_t = np.histogram2d(data_e[:,4], data_e[:,8], bins = (y_grid, self.theta_grid()))
I_yt, bins_y, bins_t = np.histogram2d(data_e[:,4], data_e[:,8], bins = (self.y_grid(), self.theta_grid()))
I_lt, bins_l, bins_t = np.histogram2d(data_e[:,7], data_e[:,8], bins = (self.lamda_grid(), self.theta_grid()))
I_q, bins_q = np.histogram(data_e[:,9], bins = self.q_grid())
q_lim = 4*np.pi*np.array([ max( np.sin(self.theta_grid()[0]*np.pi/180.)/self.lamda_grid()[-1] , 1e-4 ),
@@ -335,9 +339,8 @@ class PlotSelection:
cmap = mpl.cm.gnuplot(np.arange(256))
cmap[:1, :] = np.array([256/256, 255/256, 236/256, 1])
cmap = mpl.colors.ListedColormap(cmap, name='myColorMap', N=cmap.shape[0])
y_grid = np.arange(64)
z_grid = np.arange(det.nBlades*32)
I_yz, bins_y, bins_z = np.histogram2d(data_e[:,4], (det.nBlades-data_e[:,2])*32-data_e[:,3], bins = (y_grid, z_grid))
I_yz, bins_y, bins_z = np.histogram2d(data_e[:,4], (det.nBlades-data_e[:,2])*32-data_e[:,3], bins = (self.y_grid(), z_grid))
if arg == 'log':
vmin = 0
vmax = max(1, np.log(np.max(I_yt)+.1)/np.log(10)*1.05)
@@ -363,14 +366,16 @@ class PlotSelection:
vmax = max(np.max(I_lt), 5)
plt.pcolormesh(bins_l, bins_t, I_lt.T, cmap=cmap, vmin=0, vmax=vmax)
plt.xlim(0,)
if np.min(bins_t) > 0.01 :
plt.ylim(bottom=0)
else:
plt.ylim(bottom=np.min(bins_t))
if np.max(bins_t) < -0.01:
plt.ylim(top=0)
else:
plt.ylim(top=np.max(bins_t))
#if np.min(bins_t) > 0.01 :
# plt.ylim(bottom=0)
#else:
# plt.ylim(bottom=np.min(bins_t))
#if np.max(bins_t) < -0.01:
# plt.ylim(top=0)
#else:
# plt.ylim(top=np.max(bins_t))
plt.xlim(lamdaMin, lamdaMax)
plt.ylim(thetaMin, thetaMax)
plt.xlabel('$\\lambda ~/~ \\mathrm{\\AA}$')
plt.ylabel('$\\theta ~/~ \\mathrm{deg}$')
headline = self.headline(fileNumber, np.shape(data_e)[0])
@@ -471,7 +476,7 @@ def process(dataPath, ident, clas):
#================================
# instrument specific parameters
#================================
global lamdaMin, lamdaMax, qMin, qMax, thetaMin, thetaMax
global lamdaMin, lamdaMax, qMin, qMax, thetaMin, thetaMax, yMin, yMax
# defaults
lamdaCut = 2.5 # Aa used to reshuffle tof
# data filtering and folding
@@ -500,11 +505,10 @@ def process(dataPath, ident, clas):
sumTime = 0
number = resolveNumber(dataPath, ident)
print(ident, number)
fileName, fileNumber = fileNameCreator(dataPath, str(number))
if verbous:
logging.info('events2histogram processing file ->\033[1m {} \033[0m<-'.format(fileNumber))
logging.info('life_histogrammer processing file ->\033[1m {} \033[0m<-'.format(fileNumber))
for i in range(6):
ev = h5py.File(fileName, 'r', swmr=True)