def iplotDImean(Dec,Inc,a95,color='k',marker='o',label=''):
"""
Plot a mean declination, inclination with alpha_95 ellipse on an equal area plot.
Before this function is called a plot needs to be initialized with code that looks
something like:
>fignum = 1
>plt.figure(num=fignum,figsize=(10,10),dpi=160)
>IPmag.iplotNET(fignum)
Parameters
----------
Dec : declination of mean being plotted
Inc : inclination of mean being plotted
a95 : a95 confidence ellipse of mean being plotted
color : the default color is black. Other colors can be chosen (e.g. 'r')
marker : the default is a circle. Other symbols can be chose (e.g. 's')
label : the default is no label. Labels can be assigned
"""
DI_dimap=pmag.dimap(Dec,Inc)
if Inc < 0:
pylab.plot(DI_dimap[0],DI_dimap[1],markeredgecolor=color , markerfacecolor='white', marker=marker,label=label)
if Inc >= 0:
pylab.plot(DI_dimap[0],DI_dimap[1],color=color,marker=marker,label=label)
Xcirc,Ycirc=[],[]
Da95,Ia95=pmag.circ(Dec,Inc,a95)
pylab.legend(loc=2)
for k in range(len(Da95)):
XY=pmag.dimap(Da95[k],Ia95[k])
Xcirc.append(XY[0])
Ycirc.append(XY[1])
pylab.plot(Xcirc,Ycirc,color)
pylab.tight_layout()
def main():
"""
NAME
di_eq.py
DESCRIPTION
converts dec, inc pairs to x,y pairs using equal area projection
NB: do only upper or lower hemisphere at a time: does not distinguish between up and down.
SYNTAX
di_eq.py [command line options] [< filename]
OPTIONS
-f FILE, input file
"""
out=""
UP=0
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-f' in sys.argv:
dat=[]
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
f=open(file,'rU')
input=f.readlines()
else:
input = sys.stdin.readlines() # read from standard input
for line in input:
rec=line.split()
d,i=float(rec[0]),float(rec[1])
XY=pmag.dimap(d,i)
print XY[0],XY[1] #
def plot_AMS(sdata,pointsize=50,errors='None',bedding=[],incolor='N',):
"""
adapted from pmagplotlib.plotANIS
set errors to 'h' for hext ellipses, 'b' for bootstrap, 'p' for parametric bootstrap
bootstrap trials currently hard-coded as 1000
for bedding, give as [strike,dip] ;
"""
subplot_net() #set up stereonet
if incolor=='N': colours=['0.4','0.6','0.5'] #specify greyscale colours
else: colours=['lightcoral','lightskyblue','lightgreen']
#if bedding plot bedding plane
if bedding !=[]:
# hard-coded version of pmag.plotC
D_c,I_c=pmag.circ(bedding[0]-90.,90.-bedding[1],90.)
X_c_d,Y_c_d=[],[]
for k in range(len(D_c)):
XY=pmag.dimap(D_c[k],I_c[k])
if I_c[k]>0:
X_c_d.append(XY[0])
Y_c_d.append(XY[1])
plt.plot(X_c_d,Y_c_d,color='grey',dashes=[10,2],linewidth=3,zorder=1)
Vs=[]
#plot individual sample data
for s in sdata:
tau,V=pmag.doseigs(s)
Vs.append(V)
plotEVEC(Vs,pointsize,colours)
#plot mean eigenvectors
nf,sigma,avs=pmag.sbar(sdata)
Vs=[]
mtau,mV=pmag.doseigs(avs)
Vs.append(mV)
plotEVEC(Vs,pointsize*4,['w','w','w'], 'black',7)
#plot confidence limits
hpars=pmag.dohext(nf,sigma,avs)
if errors=='h':
ellpars=[hpars["v1_dec"],hpars["v1_inc"],hpars["e12"],hpars["v2_dec"],hpars["v2_inc"],hpars["e13"],hpars["v3_dec"],hpars["v3_inc"]]
plotELL(ellpars,'black',1,1)
ellpars=[hpars["v2_dec"],hpars["v2_inc"],hpars["e23"],hpars["v3_dec"],hpars["v3_inc"],hpars["e12"],hpars["v1_dec"],hpars["v1_inc"]]
plotELL(ellpars,'black',1,1)
ellpars=[hpars["v3_dec"],hpars["v3_inc"],hpars["e13"],hpars["v1_dec"],hpars["v1_inc"],hpars["e23"],hpars["v2_dec"],hpars["v2_inc"]]
plotELL(ellpars,'black',1,1)
elif errors=='b' or errors=='p':
if errors=='p': ipar=1
else: ipar=0
Tmean,Vmean,Taus,BVs=pmag.s_boot(sdata,ipar,1000) # get eigenvectors of mean tensor
# the problem with the bootstrap is that for fabrics where one or more eigenvectors is close to the horizontal,
# you end up with dipolar data
bpars=pmag.sbootpars(Taus,BVs,Vmean)
bpars['t1']=hpars['t1']
bpars['t2']=hpars['t2']
bpars['t3']=hpars['t3']
#have to pair zeta value with eta dec/inc, and vice-versa, to align error ellipses correctly.
ellpars=[bpars["v1_dec"],bpars["v1_inc"],bpars["v1_eta"],bpars["v1_eta_dec"],bpars["v1_eta_inc"],bpars["v1_zeta"],bpars["v1_zeta_dec"],bpars["v1_zeta_inc"]]
plotELL(ellpars,'black',1,1)
ellpars=[bpars["v2_dec"],bpars["v2_inc"],bpars["v2_eta"],bpars["v2_eta_dec"],bpars["v2_eta_inc"],bpars["v2_zeta"],bpars["v2_zeta_dec"],bpars["v2_zeta_inc"]]
plotELL(ellpars,'black',1,1)
ellpars=[bpars["v3_dec"],bpars["v3_inc"],bpars["v3_eta"],bpars["v3_eta_dec"],bpars["v3_eta_inc"],bpars["v3_zeta"],bpars["v3_zeta_dec"],bpars["v3_zeta_inc"]]
plotELL(ellpars,'black',1,1)
def iplotDI(DIblock,color='k',label=''):
"""
Plot declination, inclination data on an equal area plot
This function modifies the plotDI function of PmagPy for use in the IPython notebook environment
Parameters
----------
DIblock : a DIblock is comprise of a list of unit vectors [dec,inc,1.]
color : the default color is black. Other colors can be chosen (e.g. 'r')
"""
# initialize the variables
X_down,X_up,Y_down,Y_up=[],[],[],[]
for rec in DIblock:
Up,Down=0,0
XY=pmag.dimap(rec[0],rec[1])
if rec[1] >= 0:
X_down.append(XY[0])
Y_down.append(XY[1])
else:
X_up.append(XY[0])
Y_up.append(XY[1])
if len(X_up)>0:
pylab.scatter(X_up,Y_up,facecolors='none', edgecolors=color)
if len(X_down)>0:
pylab.scatter(X_down,Y_down,facecolors=color, edgecolors=color)
pylab.legend(loc=2)
pylab.tight_layout()
def subplot_net(title="", quadrant='all'):
ax=plt.gca()
# modified from plotNET to look nicer, play more nicely with subfigures;
# also modified to allow quadrants/halves only to be plotted
"""
draws circle and tick marks for equal area projection
can zoom in on quadrant/half of stereonet using quadrant='NE','E','S' etc.
"""
quadrants= {'all': [-1.1,1.1,-1.1,1.1],'N': [-1.1,1.1,-0.1,1.1], 'E': [-0.1,1.1,-1.1,1.1],
'S': [-1.1,1.1,-1.1,0.1],'W': [-1.1,0.1,-1.1,1.1], 'NE': [-0.1,1.1,-0.1,1.1],
'SE': [-0.1,1.1,-1.1,0.1],'SW': [-1.1,0.1,-1.1,0.1], 'NW': [-0.1,1.1,-1.1,0.1]}
# make the perimeter
ax.axis("off")
Dcirc=np.arange(0,361.)
Icirc=np.zeros(361,'f')
Xcirc,Ycirc=[],[]
for k in range(361):
XY= pmag.dimap(Dcirc[k],Icirc[k])
Xcirc.append(XY[0])
Ycirc.append(XY[1])
ax.plot(Xcirc,Ycirc,'k', linewidth=2, zorder=2)
ax.set_xlim(quadrants[quadrant][:2])
ax.set_ylim(quadrants[quadrant][-2:])
# put on the tick marks
Xsym,Ysym=[],[]
for I in range(10,100,10):
XY=pmag.dimap(0.,I)
Xsym.append(XY[0])
Ysym.append(XY[1])
ax.scatter(Xsym,Ysym, color='lightgrey', marker='+', s=20)
Xsym,Ysym=[],[]
for I in range(10,90,10):
XY=pmag.dimap(90.,I)
Xsym.append(XY[0])
Ysym.append(XY[1])
ax.scatter(Xsym,Ysym,color='lightgrey', marker='+', s=20)
Xsym,Ysym=[],[]
for I in range(10,90,10):
XY=pmag.dimap(180.,I)
Xsym.append(XY[0])
Ysym.append(XY[1])
ax.scatter(Xsym,Ysym,color='lightgrey', marker='+', s=20)
Xsym,Ysym=[],[]
for I in range(10,90,10):
XY=pmag.dimap(270.,I)
Xsym.append(XY[0])
Ysym.append(XY[1])
ax.scatter(Xsym,Ysym,color='lightgrey', marker='+', s=20)
for D in range(0,360,10):
Xtick,Ytick=[],[]
for I in range(4):
XY=pmag.dimap(D,I)
Xtick.append(XY[0])
Ytick.append(XY[1])
ax.plot(Xtick,Ytick,color='grey', linewidth=1.5,zorder=1)
ax.set_title(title)
ax.set(aspect=1)
def plotEVEC(Vs,symsize=40,colours=['lightcoral','lightskyblue','lightgreen'],symboledgecolor='none',level=5):
"""
plots eigenvector directions of S vectors
adapted from pmagplotlib.plotEVEC
"""
symb,symkey=['s','v','o'],0 # plot V1s as squares, V2s as triangles and V3s as circles
for VEC in range(3):
X,Y=[],[]
for Vdirs in Vs:
# plot the V1 data first
XY=pmag.dimap(Vdirs[VEC][0],Vdirs[VEC][1])
X.append(XY[0])
Y.append(XY[1])
plt.scatter(X,Y,s=symsize,marker=symb[VEC],c=colours[VEC],edgecolors=symboledgecolor, zorder=level)
def draw_net(FIG):
FIG.clear()
eq = FIG
eq.axis((-1, 1, -1, 1))
eq.axis("off")
theta = arange(0.0, 2 * pi, 2 * pi / 1000)
eq.plot(cos(theta), sin(theta), "k", clip_on=False, lw=1)
# eq.vlines((0,0),(0.9,-0.9),(1.0,-1.0),'k')
# eq.hlines((0,0),(0.9,-0.9),(1.0,-1.0),'k')
# eq.plot([0.0],[0.0],'+k')
Xsym, Ysym = [], []
for I in range(10, 100, 10):
XY = dimap(0.0, I)
Xsym.append(XY[0])
Ysym.append(XY[1])
for I in range(10, 90, 10):
XY = dimap(90.0, I)
Xsym.append(XY[0])
Ysym.append(XY[1])
for I in range(10, 90, 10):
XY = dimap(180.0, I)
Xsym.append(XY[0])
Ysym.append(XY[1])
for I in range(10, 90, 10):
XY = dimap(270.0, I)
Xsym.append(XY[0])
Ysym.append(XY[1])
eq.plot(Xsym, Ysym, "k+", clip_on=False, mew=0.5)
for D in range(0, 360, 10):
Xtick, Ytick = [], []
for I in range(4):
XY = dimap(D, I)
Xtick.append(XY[0])
Ytick.append(XY[1])
eq.plot(Xtick, Ytick, "k", clip_on=False, lw=0.5)
eq.axes.set_aspect("equal")
def iplotNET(fignum):
"""
draws circle and tick marks for equal area projection
"""
#
# make the perimeter
#
pylab.figure(num=fignum)
pylab.clf()
pylab.axis("off")
Dcirc=np.arange(0,361.)
Icirc=np.zeros(361,'f')
Xcirc,Ycirc=[],[]
for k in range(361):
XY= pmag.dimap(Dcirc[k],Icirc[k])
Xcirc.append(XY[0])
Ycirc.append(XY[1])
pylab.plot(Xcirc,Ycirc,'k')
#
# put on the tick marks
Xsym,Ysym=[],[]
for I in range(10,100,10):
XY=pmag.dimap(0.,I)
Xsym.append(XY[0])
Ysym.append(XY[1])
pylab.plot(Xsym,Ysym,'k+')
Xsym,Ysym=[],[]
for I in range(10,90,10):
XY=pmag.dimap(90.,I)
Xsym.append(XY[0])
Ysym.append(XY[1])
pylab.plot(Xsym,Ysym,'k+')
Xsym,Ysym=[],[]
for I in range(10,90,10):
XY=pmag.dimap(180.,I)
Xsym.append(XY[0])
Ysym.append(XY[1])
pylab.plot(Xsym,Ysym,'k+')
Xsym,Ysym=[],[]
for I in range(10,90,10):
XY=pmag.dimap(270.,I)
Xsym.append(XY[0])
Ysym.append(XY[1])
pylab.plot(Xsym,Ysym,'k+')
for D in range(0,360,10):
Xtick,Ytick=[],[]
for I in range(4):
XY=pmag.dimap(D,I)
Xtick.append(XY[0])
Ytick.append(XY[1])
pylab.plot(Xtick,Ytick,'k')
pylab.axis("equal")
pylab.tight_layout()
def plotCONF(pars): #Modified from PmagPy (Tauxe et al., 2016) """ plots directions and confidence ellipses """ # # put on the mean direction # x,y=[],[] XY=pmag.dimap(float(pars[0]),float(pars[1])) x.append(XY[0]) y.append(XY[1]) #pylab.figure(num=1) if pars[1]<1:plt.scatter(x, y, edgecolors='m',facecolors='w',marker='*',s=100,zorder=5) else:plt.scatter(x, y, edgecolors='w',facecolors='m',marker='*',s=100,zorder=5) #pylab.scatter(x,y,marker='^',s=80,c='g',zorder=2) #pylab.title(s) # # plot the ellipse # plotELL(pars,'m',0,1)
def iplotDI(DIblock,color='k',marker='o',legend='no',label=''):
"""
Plot declination, inclination data on an equal area plot
This function modifies the plotDI function of PmagPy for use in the IPython notebook environment
Required Parameters
-----------
DIblock : a DIblock is comprised of a list of unit vectors [dec,inc,1.]
Optional Parameters
-----------
color : the default color is black. Other colors can be chosen (e.g. 'r')
marker : the default marker is a circle ('o')
label : the default label is blank ('')
legend : the default is no legend ('no'). Putting 'yes' will plot a legend.
"""
# initialize the variables
X_down,X_up,Y_down,Y_up=[],[],[],[]
for rec in DIblock:
Up,Down=0,0
XY=pmag.dimap(rec[0],rec[1])
if rec[1] >= 0:
X_down.append(XY[0])
Y_down.append(XY[1])
else:
X_up.append(XY[0])
Y_up.append(XY[1])
if len(X_up)>0:
pylab.scatter(X_up,Y_up,facecolors='none', edgecolors=color, marker=marker, label=label)
if len(X_down)>0:
pylab.scatter(X_down,Y_down,facecolors=color, edgecolors=color, marker=marker, label=label)
if legend=='yes':
pylab.legend(loc=2)
pylab.tight_layout()
def main():
"""
NAME
di_eq.py
DESCRIPTION
converts dec, inc pairs to x,y pairs using equal area projection
NB: do only upper or lower hemisphere at a time: does not distinguish between up and down.
SYNTAX
di_eq.py [command line options] [< filename]
OPTIONS
-h prints help message and quits
-f FILE, input file
"""
out=""
UP=0
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-f' in sys.argv:
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
DI=numpy.loadtxt(file,dtype=numpy.float)
else:
DI = numpy.loadtxt(sys.stdin,dtype=numpy.float) # read from standard input
Ds=DI.transpose()[0]
Is=DI.transpose()[1]
if len(DI)>1: #array of data
XY=pmag.dimap_V(Ds,Is)
for xy in XY:
print '%f %f'%(xy[0],xy[1])
else: # single data point
XY=pmag.dimap(Ds,Is)
print '%f %f'%(XY[0],XY[1])
def subplot_net(title="", quadrant='all'):
ax = plt.gca()
# modified from plotNET to look nicer, play more nicely with subfigures;
# also modified to allow quadrants/halves only to be plotted
"""
draws circle and tick marks for equal area projection
can zoom in on quadrant/half of stereonet using quadrant='NE','E','S' etc.
"""
quadrants = {
'all': [-1.1, 1.1, -1.1, 1.1],
'N': [-1.1, 1.1, -0.1, 1.1],
'E': [-0.1, 1.1, -1.1, 1.1],
'S': [-1.1, 1.1, -1.1, 0.1],
'W': [-1.1, 0.1, -1.1, 1.1],
'NE': [-0.1, 1.1, -0.1, 1.1],
'SE': [-0.1, 1.1, -1.1, 0.1],
'SW': [-1.1, 0.1, -1.1, 0.1],
'NW': [-0.1, 1.1, -1.1, 0.1]
}
# make the perimeter
ax.axis("off")
Dcirc = np.arange(0, 361.)
Icirc = np.zeros(361, 'f')
Xcirc, Ycirc = [], []
for k in range(361):
XY = pmag.dimap(Dcirc[k], Icirc[k])
Xcirc.append(XY[0])
Ycirc.append(XY[1])
ax.plot(Xcirc, Ycirc, 'k', linewidth=2, zorder=2)
ax.set_xlim(quadrants[quadrant][:2])
ax.set_ylim(quadrants[quadrant][-2:])
# put on the tick marks
Xsym, Ysym = [], []
for I in range(10, 100, 10):
XY = pmag.dimap(0., I)
Xsym.append(XY[0])
Ysym.append(XY[1])
ax.scatter(Xsym, Ysym, color='lightgrey', marker='+', s=20)
Xsym, Ysym = [], []
for I in range(10, 90, 10):
XY = pmag.dimap(90., I)
Xsym.append(XY[0])
Ysym.append(XY[1])
ax.scatter(Xsym, Ysym, color='lightgrey', marker='+', s=20)
Xsym, Ysym = [], []
for I in range(10, 90, 10):
XY = pmag.dimap(180., I)
Xsym.append(XY[0])
Ysym.append(XY[1])
ax.scatter(Xsym, Ysym, color='lightgrey', marker='+', s=20)
Xsym, Ysym = [], []
for I in range(10, 90, 10):
XY = pmag.dimap(270., I)
Xsym.append(XY[0])
Ysym.append(XY[1])
ax.scatter(Xsym, Ysym, color='lightgrey', marker='+', s=20)
for D in range(0, 360, 10):
Xtick, Ytick = [], []
for I in range(4):
XY = pmag.dimap(D, I)
Xtick.append(XY[0])
Ytick.append(XY[1])
ax.plot(Xtick, Ytick, color='grey', linewidth=1.5, zorder=1)
ax.set_title(title)
ax.set(aspect=1)
def plot_AMS(
sdata,
pointsize=50,
errors='None',
bedding=[],
incolor='N',
):
"""
adapted from pmagplotlib.plotANIS
set errors to 'h' for hext ellipses, 'b' for bootstrap, 'p' for parametric bootstrap
bootstrap trials currently hard-coded as 1000
for bedding, give as [strike,dip] ;
"""
subplot_net() #set up stereonet
if incolor == 'N':
colours = ['0.4', '0.6', '0.5'] #specify greyscale colours
else:
colours = ['lightcoral', 'lightskyblue', 'lightgreen']
#if bedding plot bedding plane
if bedding != []:
# hard-coded version of pmag.plotC
D_c, I_c = pmag.circ(bedding[0] - 90., 90. - bedding[1], 90.)
X_c_d, Y_c_d = [], []
for k in range(len(D_c)):
XY = pmag.dimap(D_c[k], I_c[k])
if I_c[k] > 0:
X_c_d.append(XY[0])
Y_c_d.append(XY[1])
plt.plot(X_c_d,
Y_c_d,
color='grey',
dashes=[10, 2],
linewidth=3,
zorder=1)
Vs = []
#plot individual sample data
for s in sdata:
tau, V = pmag.doseigs(s)
Vs.append(V)
plotEVEC(Vs, pointsize, colours)
#plot mean eigenvectors
nf, sigma, avs = pmag.sbar(sdata)
Vs = []
mtau, mV = pmag.doseigs(avs)
Vs.append(mV)
plotEVEC(Vs, pointsize * 4, ['w', 'w', 'w'], 'black', 7)
#plot confidence limits
hpars = pmag.dohext(nf, sigma, avs)
if errors == 'h':
ellpars = [
hpars["v1_dec"], hpars["v1_inc"], hpars["e12"], hpars["v2_dec"],
hpars["v2_inc"], hpars["e13"], hpars["v3_dec"], hpars["v3_inc"]
]
plotELL(ellpars, 'black', 1, 1)
ellpars = [
hpars["v2_dec"], hpars["v2_inc"], hpars["e23"], hpars["v3_dec"],
hpars["v3_inc"], hpars["e12"], hpars["v1_dec"], hpars["v1_inc"]
]
plotELL(ellpars, 'black', 1, 1)
ellpars = [
hpars["v3_dec"], hpars["v3_inc"], hpars["e13"], hpars["v1_dec"],
hpars["v1_inc"], hpars["e23"], hpars["v2_dec"], hpars["v2_inc"]
]
plotELL(ellpars, 'black', 1, 1)
elif errors == 'b' or errors == 'p':
if errors == 'p': ipar = 1
else: ipar = 0
Tmean, Vmean, Taus, BVs = pmag.s_boot(
sdata, ipar, 1000) # get eigenvectors of mean tensor
# the problem with the bootstrap is that for fabrics where one or more eigenvectors is close to the horizontal,
# you end up with dipolar data
bpars = pmag.sbootpars(Taus, BVs, Vmean)
bpars['t1'] = hpars['t1']
bpars['t2'] = hpars['t2']
bpars['t3'] = hpars['t3']
#have to pair zeta value with eta dec/inc, and vice-versa, to align error ellipses correctly.
ellpars = [
bpars["v1_dec"], bpars["v1_inc"], bpars["v1_eta"],
bpars["v1_eta_dec"], bpars["v1_eta_inc"], bpars["v1_zeta"],
bpars["v1_zeta_dec"], bpars["v1_zeta_inc"]
]
plotELL(ellpars, 'black', 1, 1)
ellpars = [
bpars["v2_dec"], bpars["v2_inc"], bpars["v2_eta"],
bpars["v2_eta_dec"], bpars["v2_eta_inc"], bpars["v2_zeta"],
bpars["v2_zeta_dec"], bpars["v2_zeta_inc"]
]
plotELL(ellpars, 'black', 1, 1)
ellpars = [
bpars["v3_dec"], bpars["v3_inc"], bpars["v3_eta"],
bpars["v3_eta_dec"], bpars["v3_eta_inc"], bpars["v3_zeta"],
bpars["v3_zeta_dec"], bpars["v3_zeta_inc"]
]
plotELL(ellpars, 'black', 1, 1)
def main():
"""
NAME
site_edit_magic.py
DESCRIPTION
makes equal area projections site by site
from pmag_specimens.txt file with
Fisher confidence ellipse using McFadden and McElhinny (1988)
technique for combining lines and planes
allows testing and reject specimens for bad orientations
SYNTAX
site_edit_magic.py [command line options]
OPTIONS
-h: prints help and quits
-f: specify pmag_specimen format file, default is pmag_specimens.txt
-fsa: specify er_samples.txt file
-exc: use existing pmag_criteria.txt file
-N: reset all sample flags to good
OUPUT
edited er_samples.txt file
"""
dir_path='.'
FIG={} # plot dictionary
FIG['eqarea']=1 # eqarea is figure 1
in_file='pmag_specimens.txt'
sampfile='er_samples.txt'
out_file=""
fmt,plot='svg',1
Crits=""
M,N=180.,1
repeat=''
renew=0
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-WD' in sys.argv:
ind=sys.argv.index('-WD')
dir_path=sys.argv[ind+1]
if '-f' in sys.argv:
ind=sys.argv.index("-f")
in_file=sys.argv[ind+1]
if '-fsa' in sys.argv:
ind=sys.argv.index("-fsa")
sampfile=sys.argv[ind+1]
if '-exc' in sys.argv:
Crits,file_type=pmag.magic_read(dir_path+'/pmag_criteria.txt')
for crit in Crits:
if crit['pmag_criteria_code']=='DE-SPEC':
M=float(crit['specimen_mad'])
N=float(crit['specimen_n'])
if '-fmt' in sys.argv:
ind=sys.argv.index("-fmt")
fmt=sys.argv[ind+1]
if '-N' in sys.argv: renew=1
#
if in_file[0]!="/":in_file=dir_path+'/'+in_file
if sampfile[0]!="/":sampfile=dir_path+'/'+sampfile
crd='s'
Specs,file_type=pmag.magic_read(in_file)
if file_type!='pmag_specimens':
print ' bad pmag_specimen input file'
sys.exit()
Samps,file_type=pmag.magic_read(sampfile)
if file_type!='er_samples':
print ' bad er_samples input file'
sys.exit()
SO_methods=[]
for rec in Samps:
if 'sample_orientation_flag' not in rec.keys(): rec['sample_orientation_flag']='g'
if 'sample_description' not in rec.keys(): rec['sample_description']=''
if renew==1:
rec['sample_orientation_flag']='g'
description=rec['sample_description']
if '#' in description:
newdesc=""
c=0
while description[c]!='#' and c<len(description)-1: # look for first pound sign
newdesc=newdesc+description[c]
c+=1
while description[c]=='#':
c+=1# skip first set of pound signs
while description[c]!='#':c+=1 # find second set of pound signs
while description[c]=='#' and c<len(description)-1:c+=1 # skip second set of pound signs
while c<len(description)-1: # look for first pound sign
newdesc=newdesc+description[c]
c+=1
rec['sample_description']=newdesc # edit out old comment about orientations
if "magic_method_codes" in rec:
methlist=rec["magic_method_codes"]
for meth in methlist.split(":"):
if "SO" in meth.strip() and "SO-POM" not in meth.strip():
if meth.strip() not in SO_methods: SO_methods.append(meth.strip())
pmag.magic_write(sampfile,Samps,'er_samples')
SO_priorities=pmag.set_priorities(SO_methods,0)
sitelist=[]
for rec in Specs:
if rec['er_site_name'] not in sitelist: sitelist.append(rec['er_site_name'])
sitelist.sort()
EQ={}
EQ['eqarea']=1
pmagplotlib.plot_init(EQ['eqarea'],5,5)
k=0
while k<len(sitelist):
site=sitelist[k]
print site
data=[]
ThisSiteSpecs=pmag.get_dictitem(Specs,'er_site_name',site,'T')
ThisSiteSpecs=pmag.get_dictitem(ThisSiteSpecs,'specimen_tilt_correction','-1','T') # get all the unoriented data
for spec in ThisSiteSpecs:
if spec['specimen_mad']!="" and spec['specimen_n']!="" and float(spec['specimen_mad'])<=M and float(spec['specimen_n'])>=N:
# good spec, now get orientation....
redo,p=1,0
if len(SO_methods)<=1:
az_type=SO_methods[0]
orient=pmag.find_samp_rec(spec["er_sample_name"],Samps,az_type)
redo=0
while redo==1:
if p>=len(SO_priorities):
print "no orientation data for ",spec['er_sample_name']
orient["sample_azimuth"]=""
orient["sample_dip"]=""
redo=0
else:
az_type=SO_methods[SO_methods.index(SO_priorities[p])]
orient=pmag.find_samp_rec(spec["er_sample_name"],Samps,az_type)
if orient["sample_azimuth"] !="":
redo=0
p+=1
if orient['sample_azimuth']!="":
rec={}
for key in spec.keys():rec[key]=spec[key]
rec['dec'],rec['inc']=pmag.dogeo(float(spec['specimen_dec']),float(spec['specimen_inc']),float(orient['sample_azimuth']),float(orient['sample_dip']))
rec["tilt_correction"]='1'
crd='g'
rec['sample_azimuth']=orient['sample_azimuth']
rec['sample_dip']=orient['sample_dip']
data.append(rec)
if len(data)>2:
print 'specimen, dec, inc, n_meas/MAD,| method codes '
for i in range(len(data)):
print '%s: %7.1f %7.1f %s / %s | %s' % (data[i]['er_specimen_name'], data[i]['dec'], data[i]['inc'], data[i]['specimen_n'], data[i]['specimen_mad'], data[i]['magic_method_codes'])
fpars=pmag.dolnp(data,'specimen_direction_type')
print "\n Site lines planes kappa a95 dec inc"
print site, fpars["n_lines"], fpars["n_planes"], fpars["K"], fpars["alpha95"], fpars["dec"], fpars["inc"], fpars["R"]
if out_file!="":
if float(fpars["alpha95"])<=acutoff and float(fpars["K"])>=kcutoff:
out.write('%s %s %s\n'%(fpars["dec"],fpars['inc'],fpars['alpha95']))
pmagplotlib.plotLNP(EQ['eqarea'],site,data,fpars,'specimen_direction_type')
pmagplotlib.drawFIGS(EQ)
if k!=0 and repeat!='y':
ans=raw_input("s[a]ve plot, [q]uit, [e]dit specimens, [p]revious site, <return> to continue:\n ")
elif k==0 and repeat!='y':
ans=raw_input("s[a]ve plot, [q]uit, [e]dit specimens, <return> to continue:\n ")
if ans=="p": k-=2
if ans=="a":
files={}
files['eqarea']=site+'_'+crd+'_eqarea'+'.'+fmt
pmagplotlib.saveP(EQ,files)
if ans=="q": sys.exit()
if ans=="e" and Samps==[]:
print "can't edit samples without orientation file, sorry"
elif ans=="e":
# k-=1
testspec=raw_input("Enter name of specimen to check: ")
for spec in data:
if spec['er_specimen_name']==testspec:
# first test wrong direction of drill arrows (flip drill direction in opposite direction and re-calculate d,i
d,i=pmag.dogeo(float(spec['specimen_dec']),float(spec['specimen_inc']),float(spec['sample_azimuth'])-180.,-float(spec['sample_dip']))
XY=pmag.dimap(d,i)
pmagplotlib.plotXY(EQ['eqarea'],[XY[0]],[XY[1]],sym='g^')
# first test wrong end of compass (take az-180.)
d,i=pmag.dogeo(float(spec['specimen_dec']),float(spec['specimen_inc']),float(spec['sample_azimuth'])-180.,float(spec['sample_dip']))
XY=pmag.dimap(d,i)
pmagplotlib.plotXY(EQ['eqarea'],[XY[0]],[XY[1]],sym='kv')
# did the sample spin in the hole?
# now spin around specimen's z
X_up,Y_up,X_d,Y_d=[],[],[],[]
for incr in range(0,360,5):
d,i=pmag.dogeo(float(spec['specimen_dec'])+incr,float(spec['specimen_inc']),float(spec['sample_azimuth']),float(spec['sample_dip']))
XY=pmag.dimap(d,i)
if i>=0:
X_d.append(XY[0])
Y_d.append(XY[1])
else:
X_up.append(XY[0])
Y_up.append(XY[1])
pmagplotlib.plotXY(EQ['eqarea'],X_d,Y_d,sym='b.')
pmagplotlib.plotXY(EQ['eqarea'],X_up,Y_up,sym='c.')
pmagplotlib.drawFIGS(EQ)
break
print "Triangle: wrong arrow for drill direction."
print "Delta: wrong end of compass."
print "Small circle: wrong mark on sample. [cyan upper hemisphere]"
deleteme=raw_input("Mark this sample as bad? y/[n] ")
if deleteme=='y':
reason=raw_input("Reason: [1] broke, [2] wrong drill direction, [3] wrong compass direction, [4] bad mark, [5] displaced block [6] other ")
if reason=='1':
description=' sample broke while drilling'
if reason=='2':
description=' wrong drill direction '
if reason=='3':
description=' wrong compass direction '
if reason=='4':
description=' bad mark in field'
if reason=='5':
description=' displaced block'
if reason=='6':
description=raw_input('Enter brief reason for deletion: ')
for samp in Samps:
if samp['er_sample_name']==spec['er_sample_name']:
samp['sample_orientation_flag']='b'
samp['sample_description']=samp['sample_description']+' ## direction deleted because: '+description+'##' # mark description
pmag.magic_write(sampfile,Samps,'er_samples')
repeat=raw_input("Mark another sample, this site? y/[n] ")
if repeat=='y': k-=1
else:
print 'skipping site - not enough data with specified coordinate system'
k+=1
print "sample flags stored in ",sampfile
def main():
"""
NAME
site_edit_magic.py
DESCRIPTION
makes equal area projections site by site
from zeq_specimens_g.txt file with
Fisher confidence ellipse using McFadden and McElhinny (1988)
technique for combining lines and planes
allows testing and reject specimens for bad orientations
SYNTAX
site_edit_magic.py [command line options]
OPTIONS
-h: prints help and quits
-f: specify pmag_specimen format file, default is zeq_specimens_s.txt
-fsa: specify er_samples.txt file
-exc: use existing pmag_criteria.txt file
-N: reset all sample flags to good
OUPUT
edited er_samples.txt file
"""
dir_path = "."
FIG = {} # plot dictionary
FIG["eqarea"] = 1 # eqarea is figure 1
in_file = "zeq_specimens_s.txt"
sampfile = "er_samples.txt"
out_file = ""
fmt, plot = "svg", 1
Crits = ""
M, N = 180.0, 1
repeat = ""
renew = 0
if "-h" in sys.argv:
print main.__doc__
sys.exit()
if "-WD" in sys.argv:
ind = sys.argv.index("-WD")
dir_path = sys.argv[ind + 1]
if "-f" in sys.argv:
ind = sys.argv.index("-f")
in_file = sys.argv[ind + 1]
if "-fsa" in sys.argv:
ind = sys.argv.index("-fsa")
sampfile = sys.argv[ind + 1]
if "-exc" in sys.argv:
Crits, file_type = pmag.magic_read(dir_path + "/pmag_criteria.txt")
for crit in Crits:
if crit["pmag_criteria_code"] == "DE-SPEC":
M = float(crit["specimen_mad"])
N = float(crit["specimen_n"])
if "-fmt" in sys.argv:
ind = sys.argv.index("-fmt")
fmt = sys.argv[ind + 1]
if "-N" in sys.argv:
renew = 1
#
in_file = dir_path + "/" + in_file
sampfile = dir_path + "/" + sampfile
Specs, file_type = pmag.magic_read(in_file)
if file_type != "pmag_specimens":
print " bad pmag_specimen input file"
sys.exit()
Samps, file_type = pmag.magic_read(sampfile)
if file_type != "er_samples":
print " bad er_samples input file"
sys.exit()
SO_methods = []
for rec in Samps:
if "sample_orientation_flag" not in rec.keys():
rec["sample_orientation_flag"] = "g"
if "sample_description" not in rec.keys():
rec["sample_description"] = ""
if renew == 1:
rec["sample_orientation_flag"] = "g"
description = rec["sample_description"]
if "#" in description:
newdesc = ""
c = 0
while description[c] != "#" and c < len(description) - 1: # look for first pound sign
newdesc = newdesc + description[c]
c += 1
while description[c] == "#":
c += 1 # skip first set of pound signs
while description[c] != "#":
c += 1 # find second set of pound signs
while description[c] == "#" and c < len(description) - 1:
c += 1 # skip second set of pound signs
while c < len(description) - 1: # look for first pound sign
newdesc = newdesc + description[c]
c += 1
rec["sample_description"] = newdesc # edit out old comment about orientations
if "magic_method_codes" in rec:
methlist = rec["magic_method_codes"]
for meth in methlist.split(":"):
if "SO" in meth.strip() and "SO-POM" not in meth.strip():
if meth.strip() not in SO_methods:
SO_methods.append(meth.strip())
pmag.magic_write(sampfile, Samps, "er_samples")
SO_priorities = pmag.set_priorities(SO_methods, 0)
sitelist = []
for rec in Specs:
if rec["er_site_name"] not in sitelist:
sitelist.append(rec["er_site_name"])
sitelist.sort()
EQ = {}
EQ["eqarea"] = 1
pmagplotlib.plot_init(EQ["eqarea"], 5, 5)
k = 0
while k < len(sitelist):
site = sitelist[k]
print site
data = []
for spec in Specs:
if spec["er_site_name"] == site:
if (
spec["specimen_mad"] != ""
and spec["specimen_n"] != ""
and float(spec["specimen_mad"]) <= M
and float(spec["specimen_n"]) >= N
):
# good spec, now get orientation....
redo, p = 1, 0
if len(SO_methods) <= 1:
az_type = SO_methods[0]
orient = pmag.find_samp_rec(spec["er_sample_name"], Samps, az_type)
redo = 0
while redo == 1:
if p >= len(SO_priorities):
print "no orientation data for ", spec["er_sample_name"]
orient["sample_azimuth"] = ""
orient["sample_dip"] = ""
redo = 0
else:
az_type = SO_methods[SO_methods.index(SO_priorities[p])]
orient = pmag.find_samp_rec(spec["er_sample_name"], Samps, az_type)
if orient["sample_azimuth"] != "":
redo = 0
p += 1
if orient["sample_azimuth"] != "":
rec = {}
for key in spec.keys():
rec[key] = spec[key]
rec["dec"], rec["inc"] = pmag.dogeo(
float(spec["specimen_dec"]),
float(spec["specimen_inc"]),
float(orient["sample_azimuth"]),
float(orient["sample_dip"]),
)
rec["tilt_correction"] = "1"
rec["sample_azimuth"] = orient["sample_azimuth"]
rec["sample_dip"] = orient["sample_dip"]
data.append(rec)
if len(data) > 2:
print "specimen, dec, inc, n_meas/MAD,| method codes "
for i in range(len(data)):
print "%s: %7.1f %7.1f %s / %s | %s" % (
data[i]["er_specimen_name"],
data[i]["dec"],
data[i]["inc"],
data[i]["specimen_n"],
data[i]["specimen_mad"],
data[i]["magic_method_codes"],
)
fpars = pmag.dolnp(data, "specimen_direction_type")
print "\n Site lines planes kappa a95 dec inc"
print site, fpars["n_lines"], fpars["n_planes"], fpars["K"], fpars["alpha95"], fpars["dec"], fpars[
"inc"
], fpars["R"]
if out_file != "":
if float(fpars["alpha95"]) <= acutoff and float(fpars["K"]) >= kcutoff:
out.write("%s %s %s\n" % (fpars["dec"], fpars["inc"], fpars["alpha95"]))
pmagplotlib.plotLNP(EQ["eqarea"], site, data, fpars, "specimen_direction_type")
if k != 0 and repeat != "y":
ans = raw_input("s[a]ve plot, [q]uit, [e]dit specimens, [p]revious site, <return> to continue:\n ")
elif k == 0 and repeat != "y":
ans = raw_input("s[a]ve plot, [q]uit, [e]dit specimens, <return> to continue:\n ")
if ans == "p":
k -= 2
if ans == "a":
files = {}
files["eqarea"] = site + "_" + crd + "_" + "eqarea" + "." + fmt
pmagplotlib.saveP(EQ, files)
if ans == "q":
sys.exit()
if ans == "e" and Samps == []:
print "can't edit samples without orientation file, sorry"
elif ans == "e":
# k-=1
testspec = raw_input("Enter name of specimen to check: ")
for spec in data:
if spec["er_specimen_name"] == testspec:
# first test wrong direction of drill arrows (flip drill direction in opposite direction and re-calculate d,i
d, i = pmag.dogeo(
float(spec["specimen_dec"]),
float(spec["specimen_inc"]),
float(spec["sample_azimuth"]) - 180.0,
-float(spec["sample_dip"]),
)
XY = pmag.dimap(d, i)
pmagplotlib.plotXY(EQ["eqarea"], [XY[0]], [XY[1]], "g^", "", "", "")
# first test wrong end of compass (take az-180.)
d, i = pmag.dogeo(
float(spec["specimen_dec"]),
float(spec["specimen_inc"]),
float(spec["sample_azimuth"]) - 180.0,
float(spec["sample_dip"]),
)
XY = pmag.dimap(d, i)
pmagplotlib.plotXY(EQ["eqarea"], [XY[0]], [XY[1]], "kv", "", "", "")
# did the sample spin in the hole?
# now spin around specimen's z
X_up, Y_up, X_d, Y_d = [], [], [], []
for incr in range(0, 360, 5):
d, i = pmag.dogeo(
float(spec["specimen_dec"]) + incr,
float(spec["specimen_inc"]),
float(spec["sample_azimuth"]),
float(spec["sample_dip"]),
)
XY = pmag.dimap(d, i)
if i >= 0:
X_d.append(XY[0])
Y_d.append(XY[1])
else:
X_up.append(XY[0])
Y_up.append(XY[1])
pmagplotlib.plotXY(EQ["eqarea"], X_d, Y_d, "b.", "", "", "")
pmagplotlib.plotXY(EQ["eqarea"], X_up, Y_up, "c.", "", "", "")
pmagplotlib.drawFIGS(EQ)
break
print "Triangle: wrong arrow for drill direction."
print "Delta: wrong end of compass."
print "Small circle: wrong mark on sample. [cyan upper hemisphere]"
deleteme = raw_input("Mark this sample as bad? y/[n] ")
if deleteme == "y":
reason = raw_input(
"Reason: [1] broke, [2] wrong drill direction, [3] wrong compass direction, [4] bad mark, [5] displaced block [6] other "
)
if reason == "1":
description = " sample broke while drilling"
if reason == "2":
description = " wrong drill direction "
if reason == "3":
description = " wrong compass direction "
if reason == "4":
description = " bad mark in field"
if reason == "5":
description = " displaced block"
if reason == "6":
description = raw_input("Enter brief reason for deletion: ")
for samp in Samps:
if samp["er_sample_name"] == spec["er_sample_name"]:
samp["sample_orientation_flag"] = "b"
samp["sample_description"] = (
samp["sample_description"] + " ## direction deleted because: " + description + "##"
) # mark description
pmag.magic_write(sampfile, Samps, "er_samples")
repeat = raw_input("Mark another sample, this site? y/[n] ")
if repeat == "y":
k -= 1
else:
print "skipping site - not enough data with specified coordinate system"
k += 1
print "sample flags stored in ", sampfile
def plot_di_mean(dec,
inc,
a95,
color='k',
marker='o',
markersize=20,
label='',
legend='no',
zorder=3): #Modified from PmagPy (Tauxe et al., 2016)
"""
Plot a mean direction (declination, inclination) with alpha_95 ellipse on
an equal area plot.
Before this function is called, a plot needs to be initialized with code
that looks something like:
>fignum = 1
>plt.figure(num=fignum,figsize=(10,10),dpi=160)
>ipmag.plot_net(fignum)
Required Arguments
-----------
dec : declination of mean being plotted
inc : inclination of mean being plotted
a95 : a95 confidence ellipse of mean being plotted
Optional Keywords
-----------
color : the default color is black. Other colors can be chosen (e.g. 'r').
marker : the default is a circle. Other symbols can be chosen (e.g. 's').
markersize : the default is 20. Other sizes can be chosen.
label : the default is no label. Labels can be assigned.
legend : the default is no legend ('no'). Putting 'yes' will plot a legend.
"""
DI_dimap = pmag.dimap(dec, inc)
if inc < 0:
plt.scatter(DI_dimap[0],
DI_dimap[1],
edgecolors=color,
facecolors='white',
marker=marker,
s=markersize,
label=label,
zorder=4)
if inc >= 0:
plt.scatter(DI_dimap[0],
DI_dimap[1],
edgecolors=color,
facecolors=color,
marker=marker,
s=markersize,
label=label,
zorder=zorder)
Xcirc, Ycirc = [], []
Da95, Ia95 = pmag.circ(dec, inc, a95)
if legend == 'yes':
plt.legend(loc=2)
for k in range(len(Da95)):
XY = pmag.dimap(Da95[k], Ia95[k])
Xcirc.append(XY[0])
Ycirc.append(XY[1])
plt.plot(Xcirc, Ycirc, c=color, linewidth=0.5, zorder=3)
plt.tight_layout()
