/
geofield.py
260 lines (185 loc) · 9.1 KB
/
geofield.py
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import numpy
from xyzfield import xyzfieldv #eliminar esta dependencia
import scipy, scipy.sparse, scipy.interpolate
class GaussCoefficientsData(object):
def interpolated(self,times):
shape=(self.nmax+1,self.nmax+1)
gint=numpy.zeros((len(times),*shape)) #ahora es 3D (t,m,l)
hint=gint.copy() #hard copy
t=numpy.array(self.years)
for m in range(self.nmax+1):
for l in range(self.nmax+1):
gy=self.g[:,m,l]
hy=self.h[:,m,l]
ginterpolant=scipy.interpolate.InterpolatedUnivariateSpline(t,gy,k=5)
hinterpolant=scipy.interpolate.InterpolatedUnivariateSpline(t,hy,k=5)
gint[:,m,l]=ginterpolant(numpy.array(times))
hint[:,m,l]=hinterpolant(numpy.array(times))
return gint,hint
def field_at_location(self, lat, lon, times=None, field="f", rparam=1.0):
if times == None:
times=numpy.array(self.years)
thetav=numpy.array([scipy.pi/2-numpy.deg2rad(lat)])
phiv=numpy.array([numpy.deg2rad(lon)])
if field == "f":
xyz = numpy.zeros((len(times),3))
g,h=self.interpolated(times)
for t,i in zip(times,range(len(times))):
xyz[i,:]=numpy.array(xyzfieldv(g[i],h[i],phiv,thetav,rparam))
return times, xyz[:,0], xyz[:,1], xyz[:,2]
elif field == "s":
vtimes,secular=self.secularvariation(times,interval=0.5,phiv=phiv,thetav=thetav)
return vtimes, secular[:,0], secular[:,1], secular[:,2]
elif field == "a":
vtimes,acc=self.secularacceleration(times,interval=0.5,phiv=phiv,thetav=thetav)
return vtimes, acc[:,0], acc[:,1], acc[:,2]
else: raise Exception("you did a bad thing :(")
def secularvariation(self,times,interval=0.5,phiv=scipy.linspace(0.0,scipy.pi*2,100),thetav=scipy.linspace(0.01,scipy.pi-0.01,100),rparam=1.0):
lowt=times-numpy.array(interval)
hight=times+numpy.array(interval)
timepairs=[(l,h,t) for l,h,t in zip(lowt,hight,times) if (l >= min(self.years) and h <= max(self.years))]
validtimes=[p[2] for p in timepairs]
g_high,h_high=self.interpolated([p[1] for p in timepairs])
g_low,h_low=self.interpolated([p[0] for p in timepairs])
diffs=[]
for p,i in zip(timepairs,range(len(timepairs))):
highx,highy,highz=xyzfieldv(g_high[i],h_high[i],phiv,thetav,rparam)
lowx,lowy,lowz=xyzfieldv(g_low[i],h_low[i],phiv,thetav,rparam)
diffx=(highx-lowx)/(p[1]-p[0])
diffy=(highy-lowy)/(p[1]-p[0])
diffz=(highz-lowz)/(p[1]-p[0])
diffs.append((diffx,diffy,diffz))
return validtimes,numpy.array(diffs)
def secularacceleration(self,times,interval=0.5,phiv=scipy.linspace(0.0,scipy.pi*2,100),thetav=scipy.linspace(0.01,scipy.pi-0.01,100),rparam=1.0):
lowt=times-numpy.array(interval)
hight=times+numpy.array(interval)
timepairs=[(l,h,t) for l,h,t in zip(lowt,hight,times) if (l >= min(self.years) and h <= max(self.years))]
validtimes=[p[2] for p in timepairs]
g_high,h_high=self.interpolated([p[1] for p in timepairs])
g_current,h_current=self.interpolated([p[2] for p in timepairs])
g_low,h_low=self.interpolated([p[0] for p in timepairs])
accs=[]
for p,i in zip(timepairs,range(len(timepairs))):
highx,highy,highz=xyzfieldv(g_high[i],h_high[i],phiv,thetav,rparam)
lowx,lowy,lowz=xyzfieldv(g_low[i],h_low[i],phiv,thetav,rparam)
currentx,currenty,currentz=xyzfieldv(g_current[i],h_current[i],phiv,thetav,rparam)
accx=(lowx-2*currentx+highx)/((p[2]-p[0])*(p[1]-p[2]))
accy=(lowy-2*currenty+highy)/((p[2]-p[0])*(p[1]-p[2]))
accz=(lowz-2*currentz+highz)/((p[2]-p[0])*(p[1]-p[2]))
accs.append((accx,accy,accz))
return validtimes,numpy.array(accs)
def secular_power(self, times, interval=10.0/12.0, rparam=1.0):
lowt=times-numpy.array(interval)
hight=times+numpy.array(interval)
timepairs=[(l,h,t) for l,h,t in zip(lowt,hight,times) if (l >= min(self.years) and h <= max(self.years))]
validtimes=[p[2] for p in timepairs]
g_high, h_high = self.interpolated([p[1] for p in timepairs])
g_current, h_current = self.interpolated([p[2] for p in timepairs])
g_low, h_low = self.interpolated([p[0] for p in timepairs])
accs=[]
for p,i in zip(timepairs, range(len(timepairs))):
g_acc = ((g_low[i]-2*g_current[i]+g_high[i])/((p[2]-p[0])*(p[1]-p[2])))**2
h_acc = ((h_low[i]-2*h_current[i]+h_high[i])/((p[2]-p[0])*(p[1]-p[2])))**2
l_acc = (g_acc+h_acc).sum(axis=0)
l_array = rparam**(2*numpy.arange(len(l_acc))+4)*(numpy.arange(len(l_acc))+1)
accs.append(l_array*l_acc)
return validtimes, numpy.array(accs)
class SHADIFData(GaussCoefficientsData):
def __init__(self,filename,filename_err=None):
fs=open(filename, "r")
if filename_err:
fe=open(filename_err, "r")
coefs={}
errors={}
for line in fs:
year, l, m, gcoef, hcoef = [float(v) for v in line.split()]
if year not in coefs:
coefs[year]=[]
coefs[year].append(gcoef)
if m != 0:
coefs[year].append(hcoef)
if filename_err:
for line in fe:
year, l, m, gerr, herr = [float(v) for v in line.split()]
if year not in errors:
errors[year]=[]
errors[year].append(gerr)
if m != 0:
errors[year].append(herr)
self.years = sorted(coefs)
self.gcomp = numpy.zeros((len(self.years),max([len(coefs[y]) for y in self.years])))
self.gcomp_err = self.gcomp.copy()
for i, y in enumerate(self.years):
self.gcomp[i]=numpy.array(coefs[y])
if filename_err:
self.gcomp_err[i]=numpy.array(errors[y])
class SwarmData(GaussCoefficientsData):
def __init__(self,filename,sparse=False):
import scipy.sparse
fs=open(filename,"r")
yearsread=False
for line in fs:
if not line.startswith("#"):
if not yearsread:
self.nmin,self.nmax,self.ntimes,self.spline_order,self.nstep=(int(x) for x in line.split()[:5])
line=fs.readline()
self.years=[float(i) for i in line.split()]
yearsread=True;
#init arrays
if(sparse):
self.g=scipy.sparse.csc_matrix(shape=(self.ntimes,self.nmax+1,self.nmax+1))
self.h=self.g.copy()
else:
self.g=numpy.zeros((self.ntimes,self.nmax+1,self.nmax+1))
self.h=self.g.copy()
else:
elems=line.split()
l=int(elems[0])
m=int(elems[1])
values=elems[2:]
if m < 0:
for y,v,i in zip(self.years,values,range(self.ntimes)):
self.h[i,-m,l]=float(v)
else:
for y,v,i in zip(self.years,values,range(self.ntimes)):
self.g[i,m,l]=float(v)
class ChaosData(GaussCoefficientsData):
def __init__(self,filename,sparse=False):
import scipy.sparse
fs = open(filename, "r")
self.years = [float(i) for i in fs.readline().split()]
self.ntimes = len(self.years)
self.nmin = 1; self.nmax = 20
self.gcomp = scipy.zeros((self.ntimes,self.nmax*(self.nmax+2)+1))
if sparse:
self.g = scipy.sparse.csc_matrix(shape=(self.ntimes, self.nmax+1, self.nmax+1))
self.h = self.g.copy()
else:
self.g = numpy.zeros((self.ntimes, self.nmax+1, self.nmax+1))
self.h = self.g.copy()
orders=[]
for l in range(self.nmin,self.nmax+1):
for m in range(0,l+1):
if m == 0:
orders.append((l,m))
else:
orders.append((l,m))
orders.append((l,-m))
for i, order, line in zip(range(1,self.nmax+1),orders,fs):
values=[float(v) for v in line.split()]
self.gcomp[:,i] = numpy.array(values)
l,m=order
#print(l,m)
if m < 0:
self.h[:,-m,l] = numpy.array(values)
else:
self.g[:,m,l] = numpy.array(values)
if l >= self.nmax:
break
def locationfield(lat,lon,x,y,z,phiv,thetav):
theta=scipy.pi/2-numpy.deg2rad(lat)
phi=numpy.deg2rad(lon)
x_atlocation=scipy.interpolate.interp2d(thetav,phiv,x,kind="linear")(theta,phi)
y_atlocation=scipy.interpolate.interp2d(thetav,phiv,y,kind="linear")(theta,phi)
z_atlocation=scipy.interpolate.interp2d(thetav,phiv,z,kind="linear")(theta,phi)
return numpy.array((x_atlocation,y_atlocation,z_atlocation))