def main():
"""
NAME
scalc.py
DESCRIPTION
calculates Sb from VGP Long,VGP Lat,Directional kappa,Site latitude data
SYNTAX
scalc -h [command line options] [< standard input]
INPUT
takes space delimited files with PLong, PLat,[kappa, N_site, slat]
OPTIONS
-h prints help message and quits
-f FILE: specify input file
-c cutoff: specify VGP colatitude cutoff value
-k cutoff: specify kappa cutoff
-v : use the VanDammme criterion
-a: use antipodes of reverse data: default is to use only normal
-C: use all data without regard to polarity
-b: do a bootstrap for confidence
-p: do relative to principle axis
NOTES
if kappa, N_site, lat supplied, will consider within site scatter
OUTPUT
N Sb Sb_lower Sb_upper Co-lat. Cutoff
"""
coord, kappa, cutoff = "0", 0, 90.
nb, anti, boot = 1000, 0, 0
all = 0
n = 0
v = 0
spin = 1
coord_key = 'tilt_correction'
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-f' in sys.argv:
ind = sys.argv.index("-f")
in_file = sys.argv[ind + 1]
f = open(in_file, 'rU')
lines = f.readlines()
else:
lines = sys.stdin.readlines()
if '-c' in sys.argv:
ind = sys.argv.index('-c')
cutoff = float(sys.argv[ind + 1])
if '-k' in sys.argv:
ind = sys.argv.index('-k')
kappa = float(sys.argv[ind + 1])
if '-n' in sys.argv:
ind = sys.argv.index('-n')
n = int(sys.argv[ind + 1])
if '-a' in sys.argv: anti = 1
if '-C' in sys.argv: cutoff = 180. # no cutoff
if '-b' in sys.argv: boot = 1
if '-v' in sys.argv: v = 1
if '-p' in sys.argv: spin = 0
#
#
# find desired vgp lat,lon, kappa,N_site data:
#
A, Vgps, slats, Pvgps = 180., [], [], []
for line in lines:
if '\t' in line:
rec = line.replace('\n', '').split(
'\t') # split each line on space to get records
else:
rec = line.replace(
'\n', '').split() # split each line on space to get records
vgp = {}
vgp['vgp_lon'], vgp['vgp_lat'] = rec[0], rec[1]
Pvgps.append([float(rec[0]), float(rec[1])])
if anti == 1:
if float(vgp['vgp_lat']) < 0:
vgp['vgp_lat'] = '%7.1f' % (-1 * float(vgp['vgp_lat']))
vgp['vgp_lon'] = '%7.1f' % (float(vgp['vgp_lon']) - 180.)
if len(rec) == 5:
vgp['average_k'], vgp['average_nn'], vgp['average_lat'] = rec[
2], rec[3], rec[4]
slats.append(float(rec[4]))
else:
vgp['average_k'], vgp['average_nn'], vgp[
'average_lat'] = "0", "0", "0"
if 90. - (float(vgp['vgp_lat'])) <= cutoff and float(
vgp['average_k']) >= kappa and int(vgp['average_nn']) >= n:
Vgps.append(vgp)
if spin == 0: # do transformation to pole
ppars = pmag.doprinc(Pvgps)
for vgp in Vgps:
vlon, vlat = pmag.dotilt(float(vgp['vgp_lon']),
float(vgp['vgp_lat']),
ppars['dec'] - 180., 90. - ppars['inc'])
vgp['vgp_lon'] = vlon
vgp['vgp_lat'] = vlat
vgp['average_k'] = "0"
S_B = pmag.get_Sb(Vgps)
A = cutoff
if v == 1:
thetamax, A = 181., 180.
vVgps, cnt = [], 0
for vgp in Vgps:
vVgps.append(vgp) # make a copy of Vgps
while thetamax > A:
thetas = []
A = 1.8 * S_B + 5
cnt += 1
for vgp in vVgps:
thetas.append(90. - (float(vgp['vgp_lat'])))
thetas.sort()
thetamax = thetas[-1]
if thetamax < A: break
nVgps = []
for vgp in vVgps:
if 90. - (float(vgp['vgp_lat'])) < thetamax: nVgps.append(vgp)
vVgps = []
for vgp in nVgps:
vVgps.append(vgp)
S_B = pmag.get_Sb(vVgps)
Vgps = []
for vgp in vVgps:
Vgps.append(vgp) # make a new Vgp list
SBs, Ns = [], []
if boot == 1:
print 'please be patient... bootstrapping'
for i in range(nb): # now do bootstrap
BVgps = []
for k in range(len(Vgps)):
ind = random.randint(0, len(Vgps) - 1)
random.jumpahead(int(ind * 1000))
BVgps.append(Vgps[ind])
SBs.append(pmag.get_Sb(BVgps))
SBs.sort()
low = int(.025 * nb)
high = int(.975 * nb)
print len(Vgps), '%7.1f %7.1f %7.1f %7.1f ' % (S_B, SBs[low],
SBs[high], A)
else:
print len(Vgps), '%7.1f %7.1f ' % (S_B, A)
if len(slats) > 2:
stats = pmag.gausspars(slats)
print 'mean lat = ', '%7.1f' % (stats[0])
def main():
"""
NAME
scalc.py
DESCRIPTION
calculates Sb from VGP Long,VGP Lat,Directional kappa,Site latitude data
SYNTAX
scalc -h [command line options] [< standard input]
INPUT
takes space delimited files with PLong, PLat,[kappa, N_site, slat]
OPTIONS
-h prints help message and quits
-f FILE: specify input file
-c cutoff: specify VGP colatitude cutoff value
-k cutoff: specify kappa cutoff
-v : use the VanDammme criterion
-a: use antipodes of reverse data: default is to use only normal
-C: use all data without regard to polarity
-b: do a bootstrap for confidence
-p: do relative to principle axis
NOTES
if kappa, N_site, lat supplied, will consider within site scatter
OUTPUT
N Sb Sb_lower Sb_upper Co-lat. Cutoff
"""
coord,kappa,cutoff="0",0,90.
nb,anti,boot=1000,0,0
all=0
n=0
v=0
spin=1
coord_key='tilt_correction'
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-f' in sys.argv:
ind=sys.argv.index("-f")
in_file=sys.argv[ind+1]
f=open(in_file,'rU')
lines=f.readlines()
else:
lines=sys.stdin.readlines()
if '-c' in sys.argv:
ind=sys.argv.index('-c')
cutoff=float(sys.argv[ind+1])
if '-k' in sys.argv:
ind=sys.argv.index('-k')
kappa=float(sys.argv[ind+1])
if '-n' in sys.argv:
ind=sys.argv.index('-n')
n=int(sys.argv[ind+1])
if '-a' in sys.argv: anti=1
if '-C' in sys.argv: cutoff=180. # no cutoff
if '-b' in sys.argv: boot=1
if '-v' in sys.argv: v=1
if '-p' in sys.argv: spin=0
#
#
# find desired vgp lat,lon, kappa,N_site data:
#
A,Vgps,slats,Pvgps=180.,[],[],[]
for line in lines:
if '\t' in line:
rec=line.replace('\n','').split('\t') # split each line on space to get records
else:
rec=line.replace('\n','').split() # split each line on space to get records
vgp={}
vgp['vgp_lon'],vgp['vgp_lat']=rec[0],rec[1]
Pvgps.append([float(rec[0]),float(rec[1])])
if anti==1:
if float(vgp['vgp_lat'])<0:
vgp['vgp_lat']='%7.1f'%(-1*float(vgp['vgp_lat']))
vgp['vgp_lon']='%7.1f'%(float(vgp['vgp_lon'])-180.)
if len(rec)==5:
vgp['average_k'],vgp['average_nn'],vgp['average_lat']=rec[2],rec[3],rec[4]
slats.append(float(rec[4]))
else:
vgp['average_k'],vgp['average_nn'],vgp['average_lat']="0","0","0"
if 90.-(float(vgp['vgp_lat']))<=cutoff and float(vgp['average_k'])>=kappa and int(vgp['average_nn'])>=n: Vgps.append(vgp)
if spin==0: # do transformation to pole
ppars=pmag.doprinc(Pvgps)
for vgp in Vgps:
vlon,vlat=pmag.dotilt(float(vgp['vgp_lon']),float(vgp['vgp_lat']),ppars['dec']-180.,90.-ppars['inc'])
vgp['vgp_lon']=vlon
vgp['vgp_lat']=vlat
vgp['average_k']="0"
S_B= pmag.get_Sb(Vgps)
A=cutoff
if v==1:
thetamax,A=181.,180.
vVgps,cnt=[],0
for vgp in Vgps:vVgps.append(vgp) # make a copy of Vgps
while thetamax>A:
thetas=[]
A=1.8*S_B+5
cnt+=1
for vgp in vVgps:thetas.append(90.-(float(vgp['vgp_lat'])))
thetas.sort()
thetamax=thetas[-1]
if thetamax<A:break
nVgps=[]
for vgp in vVgps:
if 90.-(float(vgp['vgp_lat']))<thetamax:nVgps.append(vgp)
vVgps=[]
for vgp in nVgps:vVgps.append(vgp)
S_B= pmag.get_Sb(vVgps)
Vgps=[]
for vgp in vVgps:Vgps.append(vgp) # make a new Vgp list
SBs,Ns=[],[]
if boot==1:
print 'please be patient... bootstrapping'
for i in range(nb): # now do bootstrap
BVgps=[]
for k in range(len(Vgps)):
ind=random.randint(0,len(Vgps)-1)
random.jumpahead(int(ind*1000))
BVgps.append(Vgps[ind])
SBs.append(pmag.get_Sb(BVgps))
SBs.sort()
low=int(.025*nb)
high=int(.975*nb)
print len(Vgps),'%7.1f %7.1f %7.1f %7.1f '%(S_B,SBs[low],SBs[high],A)
else:
print len(Vgps),'%7.1f %7.1f '%(S_B,A)
if len(slats)>2:
stats= pmag.gausspars(slats)
print 'mean lat = ','%7.1f'%(stats[0])
def main():
"""
NAME
scalc_magic.py
DESCRIPTION
calculates Sb from pmag_results files
SYNTAX
scalc_magic -h [command line options]
INPUT
takes magic formatted pmag_results table
pmag_result_name must start with "VGP: Site"
must have average_lat if spin axis is reference
OPTIONS
-h prints help message and quits
-f FILE: specify input results file, default is 'pmag_results.txt'
-c cutoff: specify VGP colatitude cutoff value
-k cutoff: specify kappa cutoff
-crd [s,g,t]: specify coordinate system, default is geographic
-v : use the VanDammme criterion
-a: use antipodes of reverse data: default is to use only normal
-C: use all data without regard to polarity
-r: use reverse data only
-p: do relative to principle axis
-b: do bootstrap confidence bounds
OUTPUT:
if option -b used: N, S_B, lower and upper bounds
otherwise: N, S_B, cutoff
"""
in_file = 'pmag_results.txt'
coord, kappa, cutoff = "0", 1., 90.
nb, anti, spin, v, boot = 1000, 0, 1, 0, 0
coord_key = 'tilt_correction'
rev = 0
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-f' in sys.argv:
ind = sys.argv.index("-f")
in_file = sys.argv[ind + 1]
if '-c' in sys.argv:
ind = sys.argv.index('-c')
cutoff = float(sys.argv[ind + 1])
if '-k' in sys.argv:
ind = sys.argv.index('-k')
kappa = float(sys.argv[ind + 1])
if '-crd' in sys.argv:
ind = sys.argv.index("-crd")
coord = sys.argv[ind + 1]
if coord == 's': coord = "-1"
if coord == 'g': coord = "0"
if coord == 't': coord = "100"
if '-a' in sys.argv: anti = 1
if '-C' in sys.argv: cutoff = 180. # no cutoff
if '-r' in sys.argv: rev = 1
if '-p' in sys.argv: spin = 0
if '-v' in sys.argv: v = 1
if '-b' in sys.argv: boot = 1
data, file_type = pmag.magic_read(in_file)
#
#
# find desired vgp lat,lon, kappa,N_site data:
#
#
#
A, Vgps, Pvgps = 180., [], []
VgpRecs = pmag.get_dictitem(data, 'vgp_lat', '',
'F') # get all non-blank vgp latitudes
VgpRecs = pmag.get_dictitem(VgpRecs, 'vgp_lon', '',
'F') # get all non-blank vgp longitudes
SiteRecs = pmag.get_dictitem(VgpRecs, 'data_type', 'i',
'T') # get VGPs (as opposed to averaged)
SiteRecs = pmag.get_dictitem(SiteRecs, coord_key, coord,
'T') # get right coordinate system
for rec in SiteRecs:
if anti == 1:
if 90. - abs(float(rec['vgp_lat'])) <= cutoff and float(
rec['average_k']) >= kappa:
if float(rec['vgp_lat']) < 0:
rec['vgp_lat'] = '%7.1f' % (-1 * float(rec['vgp_lat']))
rec['vgp_lon'] = '%7.1f' % (float(rec['vgp_lon']) - 180.)
Vgps.append(rec)
Pvgps.append([float(rec['vgp_lon']), float(rec['vgp_lat'])])
elif rev == 0: # exclude normals
if 90. - (float(rec['vgp_lat'])) <= cutoff and float(
rec['average_k']) >= kappa:
Vgps.append(rec)
Pvgps.append([float(rec['vgp_lon']), float(rec['vgp_lat'])])
else: # include normals
if 90. - abs(float(rec['vgp_lat'])) <= cutoff and float(
rec['average_k']) >= kappa:
if float(rec['vgp_lat']) < 0:
rec['vgp_lat'] = '%7.1f' % (-1 * float(rec['vgp_lat']))
rec['vgp_lon'] = '%7.1f' % (float(rec['vgp_lon']) - 180.)
Vgps.append(rec)
Pvgps.append(
[float(rec['vgp_lon']),
float(rec['vgp_lat'])])
if spin == 0: # do transformation to pole
ppars = pmag.doprinc(Pvgps)
for vgp in Vgps:
vlon, vlat = pmag.dotilt(float(vgp['vgp_lon']),
float(vgp['vgp_lat']),
ppars['dec'] - 180., 90. - ppars['inc'])
vgp['vgp_lon'] = vlon
vgp['vgp_lat'] = vlat
vgp['average_k'] = "0"
S_B = pmag.get_Sb(Vgps)
A = cutoff
if v == 1:
thetamax, A = 181., 180.
vVgps, cnt = [], 0
for vgp in Vgps:
vVgps.append(vgp) # make a copy of Vgps
while thetamax > A:
thetas = []
A = 1.8 * S_B + 5
cnt += 1
for vgp in vVgps:
thetas.append(90. - (float(vgp['vgp_lat'])))
thetas.sort()
thetamax = thetas[-1]
if thetamax < A: break
nVgps = []
for vgp in vVgps:
if 90. - (float(vgp['vgp_lat'])) < thetamax: nVgps.append(vgp)
vVgps = []
for vgp in nVgps:
vVgps.append(vgp)
S_B = pmag.get_Sb(vVgps)
Vgps = []
for vgp in vVgps:
Vgps.append(vgp) # make a new Vgp list
SBs = []
if boot == 1:
for i in range(nb): # now do bootstrap
BVgps = []
if i % 100 == 0: print(i, ' out of ', nb)
for k in range(len(Vgps)):
random.seed()
ind = random.randint(0, len(Vgps) - 1)
BVgps.append(Vgps[ind])
SBs.append(pmag.get_Sb(BVgps))
SBs.sort()
low = int(.025 * nb)
high = int(.975 * nb)
print(len(Vgps),
'%7.1f _ %7.1f ^ %7.1f %7.1f' % (S_B, SBs[low], SBs[high], A))
else:
print(len(Vgps), '%7.1f %7.1f ' % (S_B, A))
def main():
"""
NAME
scalc_magic.py
DESCRIPTION
calculates Sb from pmag_results files
SYNTAX
scalc_magic -h [command line options]
INPUT
takes magic formatted pmag_results table
pmag_result_name must start with "VGP: Site"
must have average_lat if spin axis is reference
OPTIONS
-h prints help message and quits
-f FILE: specify input results file, default is 'pmag_results.txt'
-c cutoff: specify VGP colatitude cutoff value
-k cutoff: specify kappa cutoff
-crd [s,g,t]: specify coordinate system, default is geographic
-v : use the VanDammme criterion
-a: use antipodes of reverse data: default is to use only normal
-C: use all data without regard to polarity
-r: use reverse data only
-p: do relative to principle axis
-b: do bootstrap confidence bounds
OUTPUT:
if option -b used: N, S_B, lower and upper bounds
otherwise: N, S_B, cutoff
"""
in_file='pmag_results.txt'
coord,kappa,cutoff="0",1.,90.
nb,anti,spin,v,boot=1000,0,1,0,0
coord_key='tilt_correction'
rev=0
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-f' in sys.argv:
ind=sys.argv.index("-f")
in_file=sys.argv[ind+1]
if '-c' in sys.argv:
ind=sys.argv.index('-c')
cutoff=float(sys.argv[ind+1])
if '-k' in sys.argv:
ind=sys.argv.index('-k')
kappa=float(sys.argv[ind+1])
if '-crd' in sys.argv:
ind=sys.argv.index("-crd")
coord=sys.argv[ind+1]
if coord=='s':coord="-1"
if coord=='g':coord="0"
if coord=='t':coord="100"
if '-a' in sys.argv: anti=1
if '-C' in sys.argv: cutoff=180. # no cutoff
if '-r' in sys.argv: rev=1
if '-p' in sys.argv: spin=0
if '-v' in sys.argv: v=1
if '-b' in sys.argv: boot=1
data,file_type=pmag.magic_read(in_file)
#
#
# find desired vgp lat,lon, kappa,N_site data:
#
#
#
A,Vgps,Pvgps=180.,[],[]
VgpRecs=pmag.get_dictitem(data,'vgp_lat','','F') # get all non-blank vgp latitudes
VgpRecs=pmag.get_dictitem(VgpRecs,'vgp_lon','','F') # get all non-blank vgp longitudes
SiteRecs=pmag.get_dictitem(VgpRecs,'data_type','i','T') # get VGPs (as opposed to averaged)
SiteRecs=pmag.get_dictitem(SiteRecs,coord_key,coord,'T') # get right coordinate system
for rec in SiteRecs:
if anti==1:
if 90.-abs(float(rec['vgp_lat']))<=cutoff and float(rec['average_k'])>=kappa:
if float(rec['vgp_lat'])<0:
rec['vgp_lat']='%7.1f'%(-1*float(rec['vgp_lat']))
rec['vgp_lon']='%7.1f'%(float(rec['vgp_lon'])-180.)
Vgps.append(rec)
Pvgps.append([float(rec['vgp_lon']),float(rec['vgp_lat'])])
elif rev==0: # exclude normals
if 90.-(float(rec['vgp_lat']))<=cutoff and float(rec['average_k'])>=kappa:
Vgps.append(rec)
Pvgps.append([float(rec['vgp_lon']),float(rec['vgp_lat'])])
else: # include normals
if 90.-abs(float(rec['vgp_lat']))<=cutoff and float(rec['average_k'])>=kappa:
if float(rec['vgp_lat'])<0:
rec['vgp_lat']='%7.1f'%(-1*float(rec['vgp_lat']))
rec['vgp_lon']='%7.1f'%(float(rec['vgp_lon'])-180.)
Vgps.append(rec)
Pvgps.append([float(rec['vgp_lon']),float(rec['vgp_lat'])])
if spin==0: # do transformation to pole
ppars=pmag.doprinc(Pvgps)
for vgp in Vgps:
vlon,vlat=pmag.dotilt(float(vgp['vgp_lon']),float(vgp['vgp_lat']),ppars['dec']-180.,90.-ppars['inc'])
vgp['vgp_lon']=vlon
vgp['vgp_lat']=vlat
vgp['average_k']="0"
S_B= pmag.get_Sb(Vgps)
A=cutoff
if v==1:
thetamax,A=181.,180.
vVgps,cnt=[],0
for vgp in Vgps:vVgps.append(vgp) # make a copy of Vgps
while thetamax>A:
thetas=[]
A=1.8*S_B+5
cnt+=1
for vgp in vVgps:thetas.append(90.-(float(vgp['vgp_lat'])))
thetas.sort()
thetamax=thetas[-1]
if thetamax<A:break
nVgps=[]
for vgp in vVgps:
if 90.-(float(vgp['vgp_lat']))<thetamax:nVgps.append(vgp)
vVgps=[]
for vgp in nVgps:vVgps.append(vgp)
S_B= pmag.get_Sb(vVgps)
Vgps=[]
for vgp in vVgps:Vgps.append(vgp) # make a new Vgp list
SBs=[]
if boot==1:
for i in range(nb): # now do bootstrap
BVgps=[]
if i%100==0: print(i,' out of ',nb)
for k in range(len(Vgps)):
random.seed()
ind=random.randint(0,len(Vgps)-1)
BVgps.append(Vgps[ind])
SBs.append(pmag.get_Sb(BVgps))
SBs.sort()
low=int(.025*nb)
high=int(.975*nb)
print(len(Vgps),'%7.1f _ %7.1f ^ %7.1f %7.1f'%(S_B,SBs[low],SBs[high],A))
else:
print(len(Vgps),'%7.1f %7.1f '%(S_B,A))