Index: /fact/tools/pyscripts/sandbox/dneise/SlowDataPlotting/plot_DRScal_gain_RMS.py =================================================================== --- /fact/tools/pyscripts/sandbox/dneise/SlowDataPlotting/plot_DRScal_gain_RMS.py (revision 14430) +++ /fact/tools/pyscripts/sandbox/dneise/SlowDataPlotting/plot_DRScal_gain_RMS.py (revision 14430) @@ -0,0 +1,27 @@ +#!/usr/bin/python -tt + +import sys +from pyfact import SlowData +from plotters import CamPlotter +import matplotlib.pyplot as plt + +cp = CamPlotter('Mean GainRMS ' + sys.argv[1]) + +f = SlowData(sys.argv[1]) +f.register('all') +f.next() + +GainRms = f.GainRms.reshape(1440,1024) + +cp(GainRms.mean(axis=1)) + +cp.ax.text(-25,25,f.date[0]) +plt.draw() + +png = sys.argv[1]+'_gainRMS.png' +plt.savefig(png) + +import os +cmd = 'convert ' + png + ' ' + png[:-4] + '.pdf' +print cmd +os.system(cmd) Index: /fact/tools/pyscripts/sandbox/dneise/SlowDataPlotting/plot_currs.py =================================================================== --- /fact/tools/pyscripts/sandbox/dneise/SlowDataPlotting/plot_currs.py (revision 14430) +++ /fact/tools/pyscripts/sandbox/dneise/SlowDataPlotting/plot_currs.py (revision 14430) @@ -0,0 +1,93 @@ +#!/usr/bin/python -tti + +############################################## +# based on plot_trigger_rate.py by QW and TPK +############################################## + +from array import array +import os +import re +import sys +import numpy as np +import time + +from pyfact import SlowData + +#from ROOT import TCanvas, TGraph, TGraphErrors, TH2F +from ROOT import gROOT +#from ROOT import gStyle + +import matplotlib.pyplot as plt +import matplotlib.dates + +gROOT.SetStyle("Plain") +plt.ion() + +filelist = [] +if len(sys.argv) > 1: + base_path = sys.argv[1] +else: + print 'Usage:', sys.argv[0], '/your/search/path' + +for base,subdirs,files in os.walk(base_path): + for filename in files: + #include only run files + regex = re.search(r'\d\d\d\d\d\d\d\d\.FSC_CONTROL_CURRENT.fits',filename) + #include run files and also the nightly file + #regex = re.search(r'FTM_CONTROL_TRIGGER_RATES',filename) + if regex: + filelist.append(os.path.join(base,filename)) + + +plotlist = ['FAD_Id', 'FAD_In', 'FAD_Ip', 'FPA_Id', 'FPA_In', 'FPA_Ip', 'FTM_I', 'FFC_I'] +plotfmts = ['+:r', '+:b', '+:g' , '.:m' , '.:y', '.:k' , 'o:c' ,'*:k'] +per_name = [] + +for filename in filelist: + + print filename + + f = SlowData(filename) + + f.register("all") + + f.stack() + for row in f: + pass + + + for name in plotlist: + per_name.append(f.columns[name][0]) + + fig = plt.figure() + ax = fig.add_subplot(111) + plt.hold(True) + for i,name in enumerate(plotlist): + for number in range(per_name[i]): + print name, number + Time = f.stacked_cols['Time'] + data = f.stacked_cols[name][:,number] + med = np.median(Time) + # get rid of Times of the previous day. + Time_today = Time[np.where( Time>med-0.25 )[0]] + data_today = data[np.where( Time>med-0.25)[0]] + if number == 0: + ax.plot_date( Time_today, data_today, fmt=plotfmts[i], label=name) + else: + ax.plot_date( Time_today, data_today, fmt=plotfmts[i]) + today_str = time.strftime('%d.%m.' ,time.gmtime(Time_today[0]*24*3600)) + print today_str + plt.title('Currents \n'+today_str) + ax.xaxis.set_major_locator( +# matplotlib.dates.HourLocator(byhour=range(24), interval=1) + matplotlib.dates.AutoDateLocator() + ) + ax.xaxis.set_major_formatter( + matplotlib.dates.DateFormatter('%Hh') +# matplotlib.dates.AutoDateFormatter() + ) + plt.legend() + plt.draw() + +# plt.ylim(12,41) + plt.savefig(sys.argv[2]) Index: /fact/tools/pyscripts/sandbox/dneise/SlowDataPlotting/plot_hums.py =================================================================== --- /fact/tools/pyscripts/sandbox/dneise/SlowDataPlotting/plot_hums.py (revision 14430) +++ /fact/tools/pyscripts/sandbox/dneise/SlowDataPlotting/plot_hums.py (revision 14430) @@ -0,0 +1,90 @@ +#!/usr/bin/python -tti + +############################################## +# based on plot_trigger_rate.py by QW and TPK +############################################## + +from array import array +import os +import re +import sys +import numpy as np +import time + +from pyfact import SlowData + +#from ROOT import TCanvas, TGraph, TGraphErrors, TH2F +from ROOT import gROOT +#from ROOT import gStyle + +import matplotlib.pyplot as plt +import matplotlib.dates + +gROOT.SetStyle("Plain") +plt.ion() + +filelist = [] +if len(sys.argv) > 1: + base_path = sys.argv[1] +else: + print 'Usage:', sys.argv[0], '/your/search/path' + +for base,subdirs,files in os.walk(base_path): + for filename in files: + #include only run files + regex = re.search(r'\d\d\d\d\d\d\d\d\.FSC_CONTROL_HUMIDITY.fits',filename) + #include run files and also the nightly file + #regex = re.search(r'FTM_CONTROL_TRIGGER_RATES',filename) + if regex: + filelist.append(os.path.join(base,filename)) + + +plotlist = ['H'] +plotfmts = ['.:b'] +per_name = [] + +for filename in filelist: + + print filename + + f = SlowData(filename) + + f.register("all") + + f.stack() + for row in f: + pass + + + for name in plotlist: + per_name.append(f.columns[name][0]) + + fig = plt.figure() + ax = fig.add_subplot(111) + plt.hold(True) + for i,name in enumerate(plotlist): + for number in range(per_name[i]): + print name, number + Time = f.stacked_cols['Time'] + data = f.stacked_cols[name][:,number] + med = np.median(Time) + # get rid of Times of the previous day. + Time_today = Time[np.where( Time>med-0.25 )[0]] + data_today = data[np.where( Time>med-0.25)[0]] + + ax.plot_date( Time_today, data_today, fmt=plotfmts[i]) + today_str = time.strftime('%d.%m.' ,time.gmtime(Time_today[0]*24*3600)) + print today_str + plt.title('Humidity \n'+today_str) + ax.xaxis.set_major_locator( +# matplotlib.dates.HourLocator(byhour=range(24), interval=1) + matplotlib.dates.AutoDateLocator() + ) + ax.xaxis.set_major_formatter( +# matplotlib.dates.DateFormatter('%Hh') + matplotlib.dates.AutoDateFormatter() + ) + plt.draw() + +# plt.ylim(12,41) + plt.savefig(sys.argv[2]) Index: /fact/tools/pyscripts/sandbox/dneise/SlowDataPlotting/plot_temps.py =================================================================== --- /fact/tools/pyscripts/sandbox/dneise/SlowDataPlotting/plot_temps.py (revision 14430) +++ /fact/tools/pyscripts/sandbox/dneise/SlowDataPlotting/plot_temps.py (revision 14430) @@ -0,0 +1,99 @@ +#!/usr/bin/python -tt + +############################################## +# based on plot_trigger_rate.py by QW and TPK +############################################## + +from array import array +import os +import re +import sys +import numpy as np +import time + +from pyfact import SlowData + +#from ROOT import TCanvas, TGraph, TGraphErrors, TH2F +#from ROOT import gStyle + +import matplotlib.pyplot as plt +import matplotlib.dates + +filelist = [] +if len(sys.argv) > 1: + base_path = sys.argv[1] +else: + print 'Usage:', sys.argv[0], '/your/search/path' + +for base,subdirs,files in os.walk(base_path): + for filename in files: + #include only run files + regex = re.search(r'\d\d\d\d\d\d\d\d\.FSC_CONTROL_TEMPERATURE.fits',filename) + #include run files and also the nightly file + #regex = re.search(r'FTM_CONTROL_TRIGGER_RATES',filename) + if regex: + filelist.append(os.path.join(base,filename)) + + +plotlist = ['T_aux', 'T_back', 'T_crate', 'T_eth', 'T_ps', 'T_sens'] +plotfmts = ['.:g', '.:k', '.:r', '.:y', '.:b', '.:m'] +per_name = [] + +for filename in filelist: + + print filename + + f = SlowData(filename) +# 'columns': {'QoS': (1L, 4L, 'J', ''), +# 'T_aux': (4L, 4L, 'E', 'deg'), +# 'T_back': (4L, 4L, 'E', 'deg'), +# 'T_crate': (8L, 4L, 'E', 'deg'), +# 'T_eth': (4L, 4L, 'E', 'deg'), +# 'T_ps': (8L, 4L, 'E', 'deg'), +# 'T_sens': (31L, 4L, 'E', 'deg'), +# 'Time': (1L, 8L, 'D', 'MJD'), +# 't': (1L, 4L, 'E', 's')}, + + f.register("all") + + f.stack() + for row in f: + pass + + + for name in plotlist: + per_name.append(f.columns[name][0]) + + fig = plt.figure() + ax = fig.add_subplot(111) + plt.hold(True) + for i,name in enumerate(plotlist): + for number in range(per_name[i]): + print name, number + Time = f.stacked_cols['Time'] + data = f.stacked_cols[name][:,number] + med = np.median(Time) + # get rid of Times of the previous day. + Time_today = Time[np.where( Time>med-0.25 )[0]] + data_today = data[np.where( Time>med-0.25)[0]] + + ax.plot_date( Time_today, data_today, fmt=plotfmts[i]) + today_str = time.strftime('%d.%m.' ,time.gmtime(Time_today[0]*24*3600)) + print today_str + plt.title('T_ps:blue T_eth:yellow T_aux:green T_crate:red T_back:black T_sens:magenta \n'+today_str) + ax.xaxis.set_major_locator( + matplotlib.dates.HourLocator(byhour=range(24), interval=1) + ) + ax.xaxis.set_major_formatter( + matplotlib.dates.DateFormatter('%Hh') + ) + + plt.ylim(12,41) + + if len(sys.argv) > 2: + plt.savefig(sys.argv[2]) + print 'plot saved to', sys.argv[2] + else: + print "WARNING:" + print "plot was not saved..." + print "please type: plt.savefig('') or so ... to save it" Index: /fact/tools/pyscripts/sandbox/dneise/SlowDataPlotting/plot_volt.py =================================================================== --- /fact/tools/pyscripts/sandbox/dneise/SlowDataPlotting/plot_volt.py (revision 14430) +++ /fact/tools/pyscripts/sandbox/dneise/SlowDataPlotting/plot_volt.py (revision 14430) @@ -0,0 +1,98 @@ +#!/usr/bin/python -tti + +############################################## +# based on plot_trigger_rate.py by QW and TPK +############################################## + +from array import array +import os +import re +import sys +import numpy as np +import time + +from pyfact import SlowData + +#from ROOT import TCanvas, TGraph, TGraphErrors, TH2F +from ROOT import gROOT +#from ROOT import gStyle + +import matplotlib.pyplot as plt +import matplotlib.dates + +gROOT.SetStyle("Plain") +plt.ion() + +filelist = [] +if len(sys.argv) > 1: + base_path = sys.argv[1] +else: + print 'Usage:', sys.argv[0], '/your/search/path' + +for base,subdirs,files in os.walk(base_path): + for filename in files: + #include only run files + regex = re.search(r'\d\d\d\d\d\d\d\d\.FSC_CONTROL_VOLTAGE.fits',filename) + #include run files and also the nightly file + #regex = re.search(r'FTM_CONTROL_TRIGGER_RATES',filename) + if regex: + filelist.append(os.path.join(base,filename)) + + +plotlist = ['FAD_Ud'] +plotfmts = ['+:r'] +per_name = [] + +for filename in filelist: + + print filename + + f = SlowData(filename) + + f.register("all") + + f.stack() + for row in f: + pass + + + for name in plotlist: + per_name.append(f.columns[name][0]) + + fig = plt.figure() + ax = fig.add_subplot(111) + plt.hold(True) + for i,name in enumerate(plotlist): + for number in range(per_name[i]): + print name, number + Time = f.stacked_cols['Time'] + data = f.stacked_cols[name][:,number] + med = np.median(Time) + # get rid of Times of the previous day. + Time_today = Time[np.where( Time>med-0.25 )[0]] + data_today = data[np.where( Time>med-0.25)[0]] +# if number == 0: +# ax.plot_date( Time_today, data_today, fmt=plotfmts[i], label=name) +# else: +# ax.plot_date( Time_today, data_today, fmt=plotfmts[i]) + ax.plot_date( Time_today, data_today, fmt='.:', label=name+str(number)) + today_str = time.strftime('%d.%m.' ,time.gmtime(Time_today[0]*24*3600)) + print today_str + + for i in range(10): + print Time_today[i] + + plt.title('Voltage \n'+today_str) + ax.xaxis.set_major_locator( +# matplotlib.dates.HourLocator(byhour=range(24), interval=1) + matplotlib.dates.AutoDateLocator() + ) + ax.xaxis.set_major_formatter( + matplotlib.dates.DateFormatter('%Hh') +# matplotlib.dates.AutoDateFormatter() + ) + plt.legend() + plt.draw() + +# plt.ylim(12,41) + plt.savefig(sys.argv[2])