def __init__(self, all_modes):
self.mode_db = all_modes
self.db = all_modes
#self.ave_db = all_ave
alldb = self.db
#self.modekeys = data[0]['fields']['Ni']['modes'][0].keys()
#print len(alldb)
self.meta = np.array(ListDictKey(self.db, 'meta'))[0]
self.keys = (self.mode_db)[0].keys()
#self.avekeys = data[0]['fields']['Ni']['ave'].keys()
#self.nrun = len(alldb) #number of runs
self.path = np.array(ListDictKey(self.db, 'path'))
self.cxx = []
self.maxN = []
self.ave = np.array(ListDictKey(alldb, 'ave'))
#[self.cxx.append(read_cxx(path=elem,boutcxx='2fluid.cxx.ref')) for elem in self.path]
#[self.maxN.append(findlowpass(elem)) for elem in self.cxx]
[
self.cxx.append(read_cxx(path=elem,
boutcxx='physics_code.cxx.ref'))
for elem in self.path
]
self.maxZ = np.array(ListDictKey(alldb, 'maxZ'))
self.maxN = self.maxZ
#self.maxN = findlowpass(self.cxx) #low pass filt from .cxx
self.nx = np.array(ListDictKey(alldb, 'nx'))[0]
self.ny = np.array(ListDictKey(alldb, 'ny'))[0]
self.nz = np.array(ListDictKey(alldb, 'nz'))[0]
#self.nt = int(data[0]['meta']['NOUT']['v']+1)
self.Rxy = np.array(ListDictKey(alldb, 'Rxy'))
self.Rxynorm = np.array(ListDictKey(alldb, 'Rxynorm'))
self.nt = np.array(ListDictKey(alldb, 'nt'))
self.dt = np.array(ListDictKey(alldb, 'dt'))
self.nfields = np.array(ListDictKey(alldb, 'nfields'))
self.field = np.array(ListDictKey(alldb, 'field'))
self.k = np.array(ListDictKey(alldb, 'k'))
self.k_r = np.array(ListDictKey(alldb, 'k_r'))
self.mn = np.array(ListDictKey(alldb, 'mn'))
#return ListDictKey(alldb,'phase')
#self.phase = np.array(ListDictKey(alldb,'phase'))
self.phase = ListDictKey(alldb, 'phase')
# self.amp= np.array(ListDictKey(alldb,'amp'))
# self.amp_n=np.array(ListDictKey(alldb,'amp_n'))
# self.dc= []
# self.freq = np.array(ListDictKey(alldb,'k'))
# self.gamma = np.array(ListDictKey(alldb,'gamma'))
self.amp = ListDictKey(alldb, 'amp')
self.amp_n = ListDictKey(alldb, 'amp_n')
self.dc = []
#self.freq = np.array(ListDictKey(alldb,'k'))
self.gamma = np.array(ListDictKey(alldb, 'gamma'))
self.gamma_i = np.array(ListDictKey(alldb, 'gamma_i'))
self.freq = np.array(ListDictKey(alldb, 'freq'))
self.IC = np.array(ListDictKey(alldb, 'IC'))
self.dz = np.array(ListDictKey(alldb, 'dz'))
self.meta['dz'] = np.array(list(set(self.dz).union()))
self.nmodes = self.dz.size
self.MN = np.array(ListDictKey(alldb, 'MN'))
#self.MN = np.float32(self.mn)
#self.MN[:,1] = self.mn[:,1]/self.dz
self.nrun = len(set(self.path).union())
self.L = np.array(ListDictKey(alldb, 'L'))
#self.C_s =
self.modeid = np.array(ListDictKey(alldb, 'modeid'))
self.trans = np.array(ListDictKey(alldb, 'transform'))
if np.any(self.trans):
self.phase_r = ListDictKey(alldb, 'phase_r')
self.gamma_r = np.array(ListDictKey(alldb, 'gamma_r'))
self.amp_r = ListDictKey(alldb, 'amp_r')
self.freq_r = np.array(ListDictKey(alldb, 'freq_r'))
# try:
# self.model(haswak=False) #
# except:
# self.M = 0
#try:
try: #analytic model based on simple matrix
self.models = []
#self.models.append(_model(self)) #create a list to contain models
self.models.append(_model(self, haswak=True,
name='haswak')) #another model
#self.models.append(_model(self,haswak=True,name='haswak_0',m=0))
# for Ln in range(10):
# Lval = 10**((.2*Ln -1)/10)
# #Lval = 10**(Ln-1)
# #Lval =
# print Lval
# self.models.append(_model(self,varL=True,name='varL'+str(Lval),Lval=Lval,haswak=True))
except:
self.M = 0
try: #analytic models based on user defined complex omega
self.ref = []
self.ref.append(_ref(self))
#self.ref.append(_ref(self,haswak=False,name='drift'))
#demand a complex omega to compare
#self.ref.append(_ref(self,haswas=True,name='haswak'))
except:
self.ref = 0
def __init__(self,alldb):
#self.raw = data
self.db = alldb
#self.modekeys = data[0]['fields']['Ni']['modes'][0].keys()
print len(alldb)
self.meta = np.array(ListDictKey(alldb,'meta'))[0]
self.keys = alldb[0].keys()
#self.avekeys = data[0]['fields']['Ni']['ave'].keys()
#self.nrun = len(alldb) #number of runs
self.path= np.array(ListDictKey(alldb,'path'))
self.cxx =[]
self.maxN =[]
[self.cxx.append(read_cxx(path=elem,boutcxx='2fluid.cxx.ref')) for elem in self.path]
[self.maxN.append(findlowpass(elem)) for elem in self.cxx]
#self.maxN = findlowpass(self.cxx) #low pass filt from .cxx
self.nx = np.array(ListDictKey(alldb,'nx'))[0]
self.ny = np.array(ListDictKey(alldb,'ny'))[0]
self.nz = np.array(ListDictKey(alldb,'nz'))[0]
#self.nt = int(data[0]['meta']['NOUT']['v']+1)
self.Rxy = np.array(ListDictKey(alldb,'Rxy'))
self.Rxynorm = np.array(ListDictKey(alldb,'Rxynorm'))
self.nt = np.array(ListDictKey(alldb,'nt'))
self.dt = np.array(ListDictKey(alldb,'dt'))
self.nfields = np.array(ListDictKey(alldb,'nfields'))
self.field = np.array(ListDictKey(alldb,'field'))
self.k = np.array(ListDictKey(alldb,'k'))
self.k_r = np.array(ListDictKey(alldb,'k_r'))
self.mn = np.array(ListDictKey(alldb,'mn'))
#return ListDictKey(alldb,'phase')
#self.phase = np.array(ListDictKey(alldb,'phase'))
self.phase = ListDictKey(alldb,'phase')
# self.amp= np.array(ListDictKey(alldb,'amp'))
# self.amp_n=np.array(ListDictKey(alldb,'amp_n'))
# self.dc= []
# self.freq = np.array(ListDictKey(alldb,'k'))
# self.gamma = np.array(ListDictKey(alldb,'gamma'))
self.amp= ListDictKey(alldb,'amp')
self.amp_n = ListDictKey(alldb,'amp_n')
self.dc= []
self.freq = np.array(ListDictKey(alldb,'k'))
self.gamma = np.array(ListDictKey(alldb,'gamma'))
self.freq = ListDictKey(alldb,'freq')
self.IC = np.array(ListDictKey(alldb,'IC'))
self.dz = np.array(ListDictKey(alldb,'dz'))
self.meta['dz'] = np.array(list(set(self.dz).union()))
self.nmodes = self.dz.size
self.MN = np.array(ListDictKey(alldb,'MN'))
#self.MN = np.float32(self.mn)
#self.MN[:,1] = self.mn[:,1]/self.dz
self.nrun = len(set(self.path).union())
self.L = np.array(ListDictKey(alldb,'L'))
#self.C_s =
self.modeid = np.array(ListDictKey(alldb,'modeid'))
self.trans = np.array(ListDictKey(alldb,'transform'))
if np.any(self.trans):
self.phase_r = ListDictKey(alldb,'phase_r')
self.gamma_r = np.array(ListDictKey(alldb,'gamma_r'))
self.amp_r = ListDictKey(alldb,'amp_r')
self.freq_r = np.array(ListDictKey(alldb,'freq_r'))
# try:
# self.model(haswak=False) #
# except:
# self.M = 0
#try:
try:
self.models=[]
self.models.append(_model(self)) #create a list to contain models
self.models.append(_model(self,haswak=True,name='haswak')) #another model
self.models.append(_model(self,haswak2=True,name='haswak2'))
except:
self.M = 0
def __init__(self,all_modes):
self.mode_db = all_modes
self.db = all_modes
#self.ave_db = all_ave
alldb = self.db
#self.modekeys = data[0]['fields']['Ni']['modes'][0].keys()
#print len(alldb)
self.meta = np.array(ListDictKey(self.db,'meta'))[0]
self.keys = (self.mode_db)[0].keys()
#self.avekeys = data[0]['fields']['Ni']['ave'].keys()
#self.nrun = len(alldb) #number of runs
self.path= np.array(ListDictKey(self.db,'path'))
self.cxx =[]
self.maxN =[]
self.ave = np.array(ListDictKey(alldb,'ave'))
#[self.cxx.append(read_cxx(path=elem,boutcxx='2fluid.cxx.ref')) for elem in self.path]
#[self.maxN.append(findlowpass(elem)) for elem in self.cxx]
[self.cxx.append(read_cxx(path=elem,boutcxx='physics_code.cxx.ref')) for elem in self.path]
self.maxZ = np.array(ListDictKey(alldb,'maxZ'))
self.maxN = self.maxZ
#self.maxN = findlowpass(self.cxx) #low pass filt from .cxx
self.nx = np.array(ListDictKey(alldb,'nx'))[0]
self.ny = np.array(ListDictKey(alldb,'ny'))[0]
self.nz = np.array(ListDictKey(alldb,'nz'))[0]
#self.nt = int(data[0]['meta']['NOUT']['v']+1)
self.Rxy = np.array(ListDictKey(alldb,'Rxy'))
self.Rxynorm = np.array(ListDictKey(alldb,'Rxynorm'))
self.nt = np.array(ListDictKey(alldb,'nt'))
self.dt = np.array(ListDictKey(alldb,'dt'))
self.nfields = np.array(ListDictKey(alldb,'nfields'))
self.field = np.array(ListDictKey(alldb,'field'))
self.k = np.array(ListDictKey(alldb,'k'))
self.k_r = np.array(ListDictKey(alldb,'k_r'))
self.mn = np.array(ListDictKey(alldb,'mn'))
#return ListDictKey(alldb,'phase')
#self.phase = np.array(ListDictKey(alldb,'phase'))
self.phase = ListDictKey(alldb,'phase')
# self.amp= np.array(ListDictKey(alldb,'amp'))
# self.amp_n=np.array(ListDictKey(alldb,'amp_n'))
# self.dc= []
# self.freq = np.array(ListDictKey(alldb,'k'))
# self.gamma = np.array(ListDictKey(alldb,'gamma'))
self.amp= ListDictKey(alldb,'amp')
self.amp_n = ListDictKey(alldb,'amp_n')
self.dc= []
#self.freq = np.array(ListDictKey(alldb,'k'))
self.gamma = np.array(ListDictKey(alldb,'gamma'))
self.gamma_i = np.array(ListDictKey(alldb,'gamma_i'))
self.freq = np.array(ListDictKey(alldb,'freq'))
self.IC = np.array(ListDictKey(alldb,'IC'))
self.dz = np.array(ListDictKey(alldb,'dz'))
self.meta['dz'] = np.array(list(set(self.dz).union()))
self.nmodes = self.dz.size
self.MN = np.array(ListDictKey(alldb,'MN'))
#self.MN = np.float32(self.mn)
#self.MN[:,1] = self.mn[:,1]/self.dz
self.nrun = len(set(self.path).union())
self.L = np.array(ListDictKey(alldb,'L'))
#self.C_s =
self.modeid = np.array(ListDictKey(alldb,'modeid'))
self.trans = np.array(ListDictKey(alldb,'transform'))
if np.any(self.trans):
self.phase_r = ListDictKey(alldb,'phase_r')
self.gamma_r = np.array(ListDictKey(alldb,'gamma_r'))
self.amp_r = ListDictKey(alldb,'amp_r')
self.freq_r = np.array(ListDictKey(alldb,'freq_r'))
# try:
# self.model(haswak=False) #
# except:
# self.M = 0
#try:
try: #analytic model based on simple matrix
self.models=[]
#self.models.append(_model(self)) #create a list to contain models
self.models.append(_model(self,haswak=True,name='haswak')) #another model
#self.models.append(_model(self,haswak=True,name='haswak_0',m=0))
# for Ln in range(10):
# Lval = 10**((.2*Ln -1)/10)
# #Lval = 10**(Ln-1)
# #Lval =
# print Lval
# self.models.append(_model(self,varL=True,name='varL'+str(Lval),Lval=Lval,haswak=True))
except:
self.M = 0
try: #analytic models based on user defined complex omega
self.ref=[]
self.ref.append(_ref(self))
#self.ref.append(_ref(self,haswak=False,name='drift'))
#demand a complex omega to compare
#self.ref.append(_ref(self,haswas=True,name='haswak'))
except:
self.ref =0
