Add the beta, xing, lumi level and emittance scan classes. Adding repeated LDB query

LHC_AutoScans.py

@@ -0,0 +1,65 @@
+import numpy as np
+import TimberManager as tm
+
+class AutoScan:
+	def __init__(self, timber_variable):
+
+		if type(timber_variable) is str:
+			print 'type var'
+			# if not (IP == 1 or IP == 5):
+			# 	raise ValueError('You need to specify which IP! (1 or 5)')
+			dict_timber = tm.parse_timber_file(timber_variable, verbose=True)
+			timber_variable_SCAN = dict_timber[get_variable_dict['AUTOSCAN']]
+			# if IP == 1:
+			# 	timber_variable_ENABLE = dict_timber[get_variable_dict['LUMILEVELING.IP1:ENABLE']]
+			# elif IP == 5: 
+			# 	timber_variable_ENABLE = dict_timber[get_variable_dict['LUMILEVELING.IP5:ENABLE']]
+
+		elif hasattr(timber_variable, '__getitem__'):
+			print 'type dic'
+			try:
+				timber_variable_SCAN = timber_variable['AUTOMATICSCAN:IP'] #get_variable_dict['AUTOSCAN']]
+				# if IP == 1:
+				# 	timber_variable_ENABLE = timber_variable['LUMILEVELING.IP1:ENABLE']
+				# elif IP == 5: 
+				# 	timber_variable_ENABLE = timber_variable['LUMILEVELING.IP5:ENABLE']
+			except:
+				print '# LHC_AutoScans : No Emittance Scan Information! Returning -1'
+				return -1
+
+		self.t_stamps        = timber_variable_SCAN.t_stamps
+		self.autoscanIP      = timber_variable_SCAN.values
+
+
+		self.autoscanIP     = np.array(np.float_(self.autoscanIP)).ravel()
+		self.t_stamps            = np.array(np.float_(self.t_stamps))
+
+	def nearest_older_sample(self, t_obs, flag_return_time=False):
+		ind_min = np.argmin(np.abs(self.t_stamps - t_obs))
+		if self.t_stamps[ind_min] > t_obs:
+			ind_min -= 1
+		if flag_return_time:    
+			if ind_min == -1:
+				return 0.*self.autoscanIP[ind_min], -1
+			else:   
+				return self.autoscanIP[ind_min], self.t_stamps[ind_min]
+		else:
+			if ind_min == -1:
+				return 0.*self.autoscanIP[ind_min]
+			else:   
+				return self.autoscanIP[ind_min]
+
+
+
+def get_variable_dict():
+	var_dict = {}
+	var_dict['AUTOSCAN'] = 'AUTOMATICSCAN:IP'
+	#var_dict['LUMI_LEVEL_ENABLE_IP5'] = 'LUMILEVELING.IP5:ENABLE'
+
+	return var_dict
+
+def variable_list():
+	var_list = []
+	var_list += get_variable_dict().values()
+
+	return var_list

LHC_BetaStar.py

@@ -0,0 +1,65 @@
+import numpy as np
+import TimberManager as tm
+
+class BetaStar:
+        def __init__(self, timber_variable, IP=0):
+
+                timber_variable_BETA = None
+                if type(timber_variable) is str:
+                        print 'type var'
+                        if not (IP ==1 or IP==5):
+                                raise ValueError('You need to specify with IP! (1 or 5)')
+                        dict_timber = tm.parse_timber_file(timber_variable, verbose=True)
+                        if IP == 1:
+                                timber_variable_BETA = dict_timber[get_variable_dict['BETASTAR_IP1']]
+                        elif IP == 5:
+                                timber_variable_BETA = dict_timber[get_variable_dict['BETASTAR_IP5']]
+
+                elif hasattr(timber_variable, '__getitem__'):
+
+                        try:
+                                if IP == 1:
+                                        timber_variable_BETA = timber_variable['HX:BETASTAR_IP1']
+                                elif IP == 5: 
+                                        timber_variable_BETA = timber_variable['HX:BETASTAR_IP5']
+                        except:
+                                print '# BetaStar : No BetaStar Information! Returning -1'
+                                return -1
+
+                self.t_stamps = timber_variable_BETA.t_stamps
+                self.beta = timber_variable_BETA.values
+
+
+                self.beta     = np.array(np.float_(self.beta)).ravel()
+                self.t_stamps = np.array(np.float_(self.t_stamps))
+
+        def nearest_older_sample(self, t_obs, flag_return_time=False):
+                ind_min = np.argmin(np.abs(self.t_stamps - t_obs))
+                if self.t_stamps[ind_min] > t_obs:
+                        ind_min -= 1
+                if flag_return_time:    
+                        if ind_min == -1:
+                                return 0.*self.beta[ind_min], -1
+                        else:   
+                                return self.beta[ind_min], self.t_stamps[ind_min]
+                else:
+                        if ind_min == -1:
+                                return 0.*self.beta[ind_min]
+                        else:   
+                                return self.beta[ind_min]
+
+
+
+def get_variable_dict():
+        var_dict = {}
+        var_dict['BETASTAR_IP1'] = 'HX:BETASTAR_IP1'
+        var_dict['BETASTAR_IP5'] = 'HX:BETASTAR_IP5'
+        #var_dict['LUMI_LEVEL_ENABLE_IP5'] = 'LUMILEVELING.IP5:ENABLE'
+
+        return var_dict
+
+def variable_list():
+        var_list = []
+        var_list += get_variable_dict().values()
+
+        return var_list

LHC_Crossing.py

@@ -0,0 +1,61 @@
+import numpy as np
+import TimberManager as tm
+
+class Crossing:
+	def __init__(self, timber_variable, IP=0):
+
+		if type(timber_variable) is str:
+			if not (IP == 1 or IP == 5):
+				raise ValueError('You need to specify which IP! (1 or 5)')
+			dict_timber = tm.parse_timber_file(timber_variable, verbose=True)
+			if IP == 1:
+				timber_variable_XING = dict_timber[get_variable_dict['LHC.RUNCONFIG:IP1-XING-V-MURAD']]
+			elif IP == 5: 
+				timber_variable_XING = dict_timber[get_variable_dict['LHC.RUNCONFIG:IP5-XING-H-MURAD']]
+
+		elif hasattr(timber_variable, '__getitem__'):
+			try:
+				if IP == 1:
+					timber_variable_XING = timber_variable['LHC.RUNCONFIG:IP1-XING-V-MURAD']
+				elif IP == 5: 
+					timber_variable_XING = timber_variable['LHC.RUNCONFIG:IP5-XING-H-MURAD']
+			except:
+				print '# LHC_Crossing : No Crossing Angle Information! Returning -1'
+				return -1
+
+		self.t_stamps = timber_variable_XING.t_stamps
+		self.xing = timber_variable_XING.values
+
+
+		self.xing     = np.array(np.float_(self.xing)).ravel()
+		self.t_stamps = np.array(np.float_(self.t_stamps))
+
+	def nearest_older_sample(self, t_obs, flag_return_time=False):
+		ind_min = np.argmin(np.abs(self.t_stamps - t_obs))
+		if self.t_stamps[ind_min] > t_obs:
+			ind_min -= 1
+		if flag_return_time:    
+			if ind_min == -1:
+				return 0.*self.xing[ind_min], -1
+			else:   
+				return self.xing[ind_min], self.t_stamps[ind_min]
+		else:
+			if ind_min == -1:
+				return 0.*self.xing[ind_min]
+			else:   
+				return self.xing[ind_min]
+
+
+
+def get_variable_dict():
+	var_dict = {}
+	var_dict['CROSSING_ANGLE_IP1'] = 'LHC.RUNCONFIG:IP1-XING-V-MURAD'
+	var_dict['CROSSING_ANGLE_IP5'] = 'LHC.RUNCONFIG:IP5-XING-H-MURAD'
+
+	return var_dict
+
+def variable_list():
+	var_list = []
+	var_list += get_variable_dict().values()
+
+	return var_list

LHC_LumiLevelling.py

@@ -0,0 +1,61 @@
+import numpy as np
+import TimberManager as tm
+
+class LumiLevelling:
+	def __init__(self, timber_variable, IP=0):
+
+		if type(timber_variable) is str:
+			if not (IP == 1 or IP == 5):
+				raise ValueError('You need to specify which IP! (1 or 5)')
+			dict_timber = tm.parse_timber_file(timber_variable, verbose=True)
+			if IP == 1:
+				timber_variable_ENABLE = dict_timber[get_variable_dict['LUMI_LEVEL_ENABLE_IP1']]
+			elif IP == 5: 
+				timber_variable_ENABLE = dict_timber[get_variable_dict['LUMI_LEVEL_ENABLE_IP5']]
+
+		elif hasattr(timber_variable, '__getitem__'):
+			try:
+				if IP == 1:
+					timber_variable_ENABLE = timber_variable['LUMILEVELING.IP1:ENABLE']
+				elif IP == 5: 
+					timber_variable_ENABLE = timber_variable['LUMILEVELING.IP5:ENABLE']
+			except:
+				print '# LHC_LumiLevelling : No Lumi Levelling Information! Returning -1'
+				return -1
+
+		self.t_stamps        = timber_variable_ENABLE.t_stamps
+		self.enableLevelling = timber_variable_ENABLE.values
+
+
+		self.enableLevelling     = np.array(np.float_(self.enableLevelling)).ravel()
+		self.t_stamps            = np.array(np.float_(self.t_stamps))
+
+	def nearest_older_sample(self, t_obs, flag_return_time=False):
+		ind_min = np.argmin(np.abs(self.t_stamps - t_obs))
+		if self.t_stamps[ind_min] > t_obs:
+			ind_min -= 1
+		if flag_return_time:    
+			if ind_min == -1:
+				return 0.*self.enableLevelling[ind_min], -1
+			else:   
+				return self.enableLevelling[ind_min], self.t_stamps[ind_min]
+		else:
+			if ind_min == -1:
+				return 0.*self.enableLevelling[ind_min]
+			else:   
+				return self.enableLevelling[ind_min]
+
+
+
+def get_variable_dict():
+	var_dict = {}
+	var_dict['LUMI_LEVEL_ENABLE_IP1'] = 'LUMILEVELING.IP1:ENABLE'
+	var_dict['LUMI_LEVEL_ENABLE_IP5'] = 'LUMILEVELING.IP5:ENABLE'
+
+	return var_dict
+
+def variable_list():
+	var_list = []
+	var_list += get_variable_dict().values()
+
+	return var_list

lhc_log_db_query_repeat.py

@@ -0,0 +1,44 @@
+import os
+import time
+
+def UnixTimeStamp2UTCTimberTimeString(t):
+    return time.strftime('%Y-%m-%d %H:%M:%S.000', time.gmtime(t))
+
+def dbquery(varlist, t_start, t_stop, filename):
+
+    if type(t_start) is not str:
+        t_start_str_UTC = UnixTimeStamp2UTCTimberTimeString(t_start)
+    else:
+        t_start_str_UTC = t_start
+
+    if type(t_stop) is not str:
+        t_stop_str_UTC = UnixTimeStamp2UTCTimberTimeString(t_stop)
+    else:
+        t_stop_str_UTC = t_stop
+
+    if type(varlist) is not list:
+        raise TypeError
+
+    varlist_str = ''
+    for var in varlist:
+        varlist_str += var+','
+    varlist_str = varlist_str[:-1]
+
+    currpath = os.path.dirname(os.path.abspath(__file__))
+
+    execut = 'java -jar %s/accsoft-cals-extr-client-nodep.jar '%(currpath)
+    config = ' -C %s/ldb_UTC.conf '%(currpath)
+    time_interval = ' -t1 "'+ t_start_str_UTC +'" -t2 "'+t_stop_str_UTC+'"'
+    variables = '-vs "%s"'%(varlist_str)
+    repeat = ' -sa REPEAT -ss 1 -si MINUTE'
+
+    if filename[0] == "/":
+        outpfile = ' -N '+filename
+    else:
+        outpfile = ' -N .//'+filename
+
+    command = execut+config+variables+time_interval+repeat+outpfile
+
+    print command
+
+    os.system(command)