def coregLoop(pointlist, ages, plateIDs):
'''
coregLoop
This script reconstructs a shapefile of points to their birth time and
coregisters each point with another set of points, or a raster file.
INPUTS:
pointlist - list of lat/lon
ages - list of ages corresponding to lat/lon point
plateIDs - list of plateIDs corresponding to lat/lon point.
Hardcoded filenames/variables must be changed below:
input_rotation_filename - Rotation file
rasterfile - Time dependent raster files
f - Time dependent kinemtic csv outputs from 'convergence.py'
OUTPUTS:
Coregistered array: List of lat/lons with properties.
METHOD:
Takes a set of points
Rotates the points back to their birth position
Determines the point's birth position geophysical properties (coregisters)
'''
#Set up a list to store the data
timeSteps = 1 # +- Myrs around point to store. Default 1 which means just the measured point age.
noVariables = 18 #The number of variables you save
Nshp = len(pointlist)
coregData = numpy.zeros((Nshp, timeSteps, noVariables))
#Create a rotation model to rotate the points back in time
input_rotation_filename = "Muller_gplates/Global_EarthByte_230-0Ma_GK07_AREPS.rot"
file_registry = pygplates.FeatureCollectionFileFormatRegistry()
rotation_feature_collection = file_registry.read(input_rotation_filename)
rotation_model = pygplates.RotationModel([rotation_feature_collection])
#Loop over all the samples, coregistering each one.
for i, currentPoint in enumerate(pointlist):
lat = currentPoint[1]
lon = currentPoint[0]
age = ages[i]
plateID = int(plateIDs[i])
print("Deposit:", i, "of", Nshp, "Lat:", lat, "Lon:", lon, "Age:", age,
"PlateID:", plateID)
#Loop through each time step in the plate model
for time in xrange(0, 230, 1):
#If the point was formed at the current time (or [timeStepsMyr ] prior/after) then we
#want to find the surrounding plate properties.
#if (time > (age-10)) and (time < (age+10)) or (time > (age+20)) and (time < (age+30)):
if (time > (age - timeSteps)) and (time < (age + timeSteps)):
t = int(numpy.floor(time - age))
#print(t,time,age)
#A raster file, to coregister with, these points have already been rotated
rasterfile = "Muller_etal_2016_AREPS_Agegrids_v1.11/netCDF_0-230Ma/EarthByte_AREPS_v1.11_Muller_etal_2016_AgeGrid-" + str(
time) + ".nc"
[x, y, z] = gridRead(rasterfile)
#A vector file to coregister with, these points have already been rotated
f = numpy.loadtxt("Muller_convergence/subStats_" + str(time) +
".csv",
delimiter=',')
lonlat = f[:, 0:2]
#-------------------#
#Reconstruct a point to its birth position
#-------------------#
latlonPoint = pygplates.LatLonPoint(lat, lon)
point_to_rotate = pygplates.convert_lat_lon_point_to_point_on_sphere(
latlonPoint)
finite_rotation = rotation_model.get_rotation(time, plateID)
birthPosition = finite_rotation * point_to_rotate
latlonBirth = pygplates.convert_point_on_sphere_to_lat_lon_point(
birthPosition)
#allPoints = finite_rotation * pointSet_to_rotate
latBirth = latlonBirth.get_latitude()
lonBirth = latlonBirth.get_longitude()
#-------------------#
#Set the points for coregistering
region = 5.0 #degrees
#-------------------#
#Coregisterring raster 1
#-------------------#
#Find the region in index units
r = numpy.round(region / (x[1] - x[0]))
#Find the index unit of lat and lon
idxLon = (numpy.abs(x - lonBirth)).argmin()
idxLat = (numpy.abs(y - latBirth)).argmin()
#Raster 1
c2 = coregRaster([idxLon, idxLat], z, r)
#Hack to search further around the age grid if it can't find a match, note index units (not degrees)
if numpy.isnan(c2):
c2 = coregRaster([idxLon, idxLat], z, r + 150.0)
print("Trying raster region: ", r + 150.0)
#-------------------#
#Coregisterring vector 1
#-------------------#
index = coregPoint([lonBirth, latBirth], lonlat, region)
if index == 'inf':
print("trying index region", region + 15)
index = coregPoint([lonBirth, latBirth], lonlat,
region + 15.0)
if numpy.isnan(c2) or index == 'inf':
print("Skipping:", i, age, t, time, c2, index, lonBirth,
latBirth)
else:
#Vector 1
segmentLength = f[index, 3]
slabLength = f[index, 9]
distSlabEdge = f[index, 15]
SPcoregNor = f[index, 4]
SPcoregPar = f[index, 12]
OPcoregNor = f[index, 5]
OPcoregPar = f[index, 13]
CONVcoregNor = f[index, 10]
CONVcoregPar = f[index, 11]
subPolCoreg = f[index, 8]
subOblCoreg = f[index, 7]
coregData[i, t, :] = [
lon, lat, lonBirth, latBirth, age, t, c2,
segmentLength, slabLength, distSlabEdge, SPcoregNor,
SPcoregPar, OPcoregNor, OPcoregPar, CONVcoregNor,
CONVcoregPar, subPolCoreg, subOblCoreg
]
#Return the filled coregistered array
return (coregData)
def coregLoop(sampleData, agegrid, kinfolder, input_rotation_filename):
'''
coregLoop
This script reconstructs a shapefile of points to their birth time and
coregisters each point with another set of points, or a raster file.
METHOD:
Takes a set of points
Rotates the points back to their birth position
Determines the point's birth position geophysical properties (coregisters)
'''
#Set up a list to store the data
timeSteps = 1
noVariables = 18 #The number of variables you save
Nshp = len(sampleData)
#Initialise the array to store the data
coregData = numpy.zeros((Nshp, timeSteps, noVariables))
#Create a rotation model to rotate the points back in time
file_registry = pygplates.FeatureCollectionFileFormatRegistry()
rotation_feature_collection = file_registry.read(input_rotation_filename)
rotation_model = pygplates.RotationModel([rotation_feature_collection])
#Loop over all the sample, coregistering each one.
for i, nshpSub in enumerate(sampleData):
lat = nshpSub[0]
lon = nshpSub[1]
age = int(nshpSub[2])
plateID = int(nshpSub[3])
print("Deposit:", i, "of", Nshp, "Lat:", lat, "Lon:", lon, "Age:", age,
"PlateID:", plateID)
#Loop through each time step in the plate model
for time in xrange(0, 230, 1):
#If the point was formed at the current time (or 10Myr prior) then we
#want to find the surrounding plate properties.
#if (time > (age-10)) and (time < (age+10)) or (time > (age+20)) and (time < (age+30)):
if (time > (age - 1)) and (time < (age + timeSteps)):
t = time - age
# print t, time
#A raster file, to coregister with, these points have already been rotated
rasterfile = agegrid + str(time) + ".nc"
[x, y, z] = gridRead(rasterfile)
#A vector file to coregister with, these points have already been rotated
f = numpy.loadtxt(kinfolder + "subStats_" + str(time) + ".csv",
delimiter=',')
lonlat = f[:, 0:2]
#-------------------#
#Reconstruct a point to its birth position
#-------------------#
latlonPoint = pygplates.LatLonPoint(lat, lon)
point_to_rotate = pygplates.convert_lat_lon_point_to_point_on_sphere(
latlonPoint)
finite_rotation = rotation_model.get_rotation(time, plateID)
birthPosition = finite_rotation * point_to_rotate
latlonBirth = pygplates.convert_point_on_sphere_to_lat_lon_point(
birthPosition)
#allPoints = finite_rotation * pointSet_to_rotate
latBirth = latlonBirth.get_latitude()
lonBirth = latlonBirth.get_longitude()
#-------------------#
#Set the points for coregistering
region = 5.0 #degrees
#-------------------#
#Coregisterring raster 1
#-------------------#
#Find the region in index units
r = numpy.round(region / (x[1] - x[0]))
#Find the index unit of lat and lon
idxLon = (numpy.abs(x - lonBirth)).argmin()
idxLat = (numpy.abs(y - latBirth)).argmin()
#Raster 1
c2 = coregRaster([idxLon, idxLat], z, r)
#Hack to search further around the age grid if it can't find a match, note index units (not degrees)
if numpy.isnan(c2):
c2 = coregRaster([idxLon, idxLat], z, r + 150.0)
print("Trying raster region: ", r + 150.0)
#-------------------#
#Coregisterring vector 1
#-------------------#
index = coregPoint([lonBirth, latBirth], lonlat, region)
if index == 'inf':
print("trying index region", region + 15)
index = coregPoint([lonBirth, latBirth], lonlat,
region + 15.0)
if numpy.isnan(c2) or index == 'inf':
print("Skipping:", nshpSub, age, t, time, c2, index,
lonBirth, latBirth)
else:
#Vector 1
segmentLength = f[index, 3]
slabLength = f[index, 9]
distSlabEdge = f[index, 15]
SPcoregNor = f[index, 4]
SPcoregPar = f[index, 12]
OPcoregNor = f[index, 5]
OPcoregPar = f[index, 13]
CONVcoregNor = f[index, 10]
CONVcoregPar = f[index, 11]
subPolCoreg = f[index, 8]
subOblCoreg = f[index, 7]
coregData[i, t, :] = [
lon, lat, lonBirth, latBirth, age, t, c2,
segmentLength, slabLength, distSlabEdge, SPcoregNor,
SPcoregPar, OPcoregNor, OPcoregPar, CONVcoregNor,
CONVcoregPar, subPolCoreg, subOblCoreg
]
#Return the filled coregistered array
return (coregData)
def coregLoopHistory(pointlist, ts0=0, ts1=230, plateID=201):
'''
coregLoopHistory
This script reconstructs a list of points throughout history and
coregisters each point with another set of points, or a raster file.
INPUTS:
pointlist - list of lat/lon
ts0 - time step to rotate points from (probably 0Ma)
ts1 - time step to rotate points to (probably 230Ma).
Hardcoded filenames/variables must be changed below:
input_rotation_filename - Rotation file
rasterfile - Time dependent raster files
f - Time dependent kinemtic csv outputs from 'convergence.py'
OUTPUTS:
Coregistered array: List of lat/lons with properties.
METHOD:
Takes a set of points
Rotates the points back to their birth position
Determines the point's birth position geophysical properties (coregisters)
'''
#Set up an array to store the data
timeSteps = ts1 - ts0 #The length of time before mineralisation you care about
noVariables = 18 #The number of variables you save
Nshp = len(pointlist)
coregData = numpy.zeros((Nshp, timeSteps, noVariables))
#Create a rotation model to rotate the points back in time
input_rotation_filename = "Muller_gplates/Global_EarthByte_230-0Ma_GK07_AREPS.rot"
file_registry = pygplates.FeatureCollectionFileFormatRegistry()
rotation_feature_collection = file_registry.read(input_rotation_filename)
rotation_model = pygplates.RotationModel([rotation_feature_collection])
#Loop through each time step in the plate model
for time in xrange(ts0, ts1, 1):
#A raster file, to coregister with, these points have already been rotated
rasterfile = "Muller_etal_2016_AREPS_Agegrids_v1.11/netCDF_0-230Ma/EarthByte_AREPS_v1.11_Muller_etal_2016_AgeGrid-" + str(
time) + ".nc"
[x, y, z] = gridRead(rasterfile)
#A vector file to coregister with, these points have already been rotated
f = numpy.loadtxt("Muller_convergence/subStats_" + str(time) + ".csv",
delimiter=',')
lonlat = f[:, 0:2]
for i, currentPoint in enumerate(pointlist):
shapeArray = currentPoint
age = ts0
t = time - age
print(i, age, time, t, plateID)
#-------------------#
#Reconstruct a point to its birth position
#-------------------#
latlonPoint = pygplates.LatLonPoint(shapeArray[1], shapeArray[0])
point_to_rotate = pygplates.convert_lat_lon_point_to_point_on_sphere(
latlonPoint)
finite_rotation = rotation_model.get_rotation(time, plateID)
birthPosition = finite_rotation * point_to_rotate
latlonBirth = pygplates.convert_point_on_sphere_to_lat_lon_point(
birthPosition)
#allPoints = finite_rotation * pointSet_to_rotate
latBirth = latlonBirth.get_latitude()
lonBirth = latlonBirth.get_longitude()
#-------------------#
#Set the points for coregistering
region = 5.0 #degrees
#-------------------#
#Coregisterring raster 1
#-------------------#
#Find the region in index units
r = numpy.round(region / (x[1] - x[0]))
#Find the index unit of lat and lon
idxLon = (numpy.abs(x - lonBirth)).argmin()
idxLat = (numpy.abs(y - latBirth)).argmin()
#Raster 1
c2 = coregRaster([idxLon, idxLat], z, r)
#Hack to search further around the age grid if it can't find a match, \
#note index units (not degrees)
if numpy.isnan(c2):
c2 = coregRaster([idxLon, idxLat], z, r + 150.0)
print("Trying raster region: ", r + 150.0)
#-------------------#
#Coregisterring vector 1
#-------------------#
index = coregPoint([lonBirth, latBirth], lonlat, region)
if index == 'inf':
print("trying index region", region + 15)
index = coregPoint([lonBirth, latBirth], lonlat, region + 15.0)
if numpy.isnan(c2) or index == 'inf':
#if we have some null data, let's save it anyway, see what happens
print("Skipping:", i, age, t, time, c2, index, lonBirth,
latBirth)
else:
#Vector 1
segmentLength = f[index, 3]
slabLength = f[index, 9]
distSlabEdge = f[index, 15]
SPcoregNor = f[index, 4]
SPcoregPar = f[index, 12]
OPcoregNor = f[index, 5]
OPcoregPar = f[index, 13]
CONVcoregNor = f[index, 10]
CONVcoregPar = f[index, 11]
subPolCoreg = f[index, 8]
subOblCoreg = f[index, 7]
coregData[i, t, :] = [
shapeArray[0], shapeArray[1], lonBirth, latBirth, age, t,
c2, segmentLength, slabLength, distSlabEdge, SPcoregNor,
SPcoregPar, OPcoregNor, OPcoregPar, CONVcoregNor,
CONVcoregPar, subPolCoreg, subOblCoreg
]
return (coregData)
def coregLoopTimeFirst(recs, shapes, fields, Nshp, shapeType):
'''
coregLoop
This script reconstructs a shapefile of points to their birth time and
coregisters each point with another set of points, or a raster file.
INPUTS:
Can best be used with the output of readTopologyPlatepolygonFile()
which reads a shapefile and returns the 'records', 'shapes', 'fields',
and 'number of shapes'.
Hardcoded filenames/variables must be changed below:
Rotation file - input_rotation_filename
Time dependent raster files - rasterfile
Time dependent vector csv outputs from 'convergence.py' - f
OUTPUTS:
Coregistered array: List of lat/lons with properties.
METHOD:
Takes a set of points (from a shapefile)
Rotates the points back to their birth position
Determines the point's birth position geophysical properties (coregisters)
'''
#Set up a list to store the data
if shapeType == 0:
timeSteps = 230 #The length of time before mineralisation you care about
else:
timeSteps = 1
noVariables = 18 #The number of variables you save
input_rotation_filename = "Muller_gplates/Global_EarthByte_230-0Ma_GK07_AREPS.rot"
#Create a rotation model to rotate the points back in time
file_registry = pygplates.FeatureCollectionFileFormatRegistry()
rotation_feature_collection = file_registry.read(input_rotation_filename)
rotation_model = pygplates.RotationModel([rotation_feature_collection])
#Initialise the array to store the data
coregData = numpy.zeros((Nshp, timeSteps, noVariables))
#Loop through each time step in the plate model
for time in xrange(0, 230, 1):
#A raster file, to coregister with, these points have already been rotated
rasterfile = "Muller_etal_2016_AREPS_Agegrids_v1.11/netCDF_0-230Ma/EarthByte_AREPS_v1.11_Muller_etal_2016_AgeGrid-" + str(
time) + ".nc"
[x, y, z] = gridRead(rasterfile)
#A vector file to coregister with, these points have already been rotated
f = numpy.loadtxt(kinfolder + "subStats_" + str(time) + ".csv",
delimiter=',')
lonlat = f[:, 0:2]
for i, nshpSub in enumerate(xrange(Nshp)):
#!!! Warning: These are shapefile specific attributes,
#if you use a different shapefile, you must change these hard codes
#to the corresponding age and plateID column in the shapefile
if shapeType == 0:
shapeArray = numpy.array(shapes[nshpSub])
age = 0
plateID = 201
else:
shapeArray = numpy.array(shapes[nshpSub].points)
#Here age is in the last column, and plateID in 7th.
#1, 2 For porcu/main_edited.shp use 43 for the plateID
#1, 2 For porcu/main_edited.shp use 9 for the age and 42 for the random age
#3, 4 For XYBer14_t2_ANDES.shp use 7 for plateID
#3, 4 For XYBer14_t2_ANDES.shp use 6 for age and -1 for Random
if shapeType == 1:
age = round(recs[nshpSub][9])
plateID = recs[nshpSub][43]
elif shapeType == 2:
age = round(recs[nshpSub][42])
plateID = recs[nshpSub][43]
elif shapeType == 3:
age = round(recs[nshpSub][6])
plateID = recs[nshpSub][7]
elif shapeType == 4:
age = round(recs[nshpSub][-1])
plateID = recs[nshpSub][7]
t = time - age
print(i, age, time, t, plateID)
#-------------------#
#Reconstruct a point to its birth position
#-------------------#
if shapeType == 0:
latlonPoint = pygplates.LatLonPoint(shapeArray[1],
shapeArray[0])
else:
latlonPoint = pygplates.LatLonPoint(shapeArray[0][1],
shapeArray[0][0])
point_to_rotate = pygplates.convert_lat_lon_point_to_point_on_sphere(
latlonPoint)
finite_rotation = rotation_model.get_rotation(time, plateID)
birthPosition = finite_rotation * point_to_rotate
latlonBirth = pygplates.convert_point_on_sphere_to_lat_lon_point(
birthPosition)
#allPoints = finite_rotation * pointSet_to_rotate
latBirth = latlonBirth.get_latitude()
lonBirth = latlonBirth.get_longitude()
#-------------------#
#Set the points for coregistering
region = 5.0 #degrees
#-------------------#
#Coregisterring raster 1
#-------------------#
#Find the region in index units
r = numpy.round(region / (x[1] - x[0]))
#Find the index unit of lat and lon
idxLon = (numpy.abs(x - lonBirth)).argmin()
idxLat = (numpy.abs(y - latBirth)).argmin()
#Raster 1
c2 = coregRaster([idxLon, idxLat], z, r)
#Hack to search further around the age grid if it can't find a match, note index units (not degrees)
if numpy.isnan(c2):
c2 = coregRaster([idxLon, idxLat], z, r + 150.0)
print("Trying raster region: ", r + 150.0)
#-------------------#
#Coregisterring vector 1
#-------------------#
index = coregPoint([lonBirth, latBirth], lonlat, region)
if index == 'inf':
print("trying index region", region + 15)
index = coregPoint([lonBirth, latBirth], lonlat, region + 15.0)
if numpy.isnan(c2) or index == 'inf':
#if we have some null data, let's save it anyway, see what happens
print("Skipping:", i, age, t, time, c2, index, lonBirth,
latBirth)
else:
#Vector 1
segmentLength = f[index, 3]
slabLength = f[index, 9]
distSlabEdge = f[index, 15]
SPcoregNor = f[index, 4]
SPcoregPar = f[index, 12]
OPcoregNor = f[index, 5]
OPcoregPar = f[index, 13]
CONVcoregNor = f[index, 10]
CONVcoregPar = f[index, 11]
subPolCoreg = f[index, 8]
subOblCoreg = f[index, 7]
if shapeType == 0:
coregData[i,t,:]=[shapeArray[0],shapeArray[1],lonBirth,latBirth,\
age,t,c2,\
segmentLength,slabLength,distSlabEdge,\
SPcoregNor,SPcoregPar,OPcoregNor,OPcoregPar,CONVcoregNor,CONVcoregPar,\
subPolCoreg,subOblCoreg]
else:
coregData[i,t,:]=[shapeArray[0][0],shapeArray[0][1],lonBirth,latBirth,\
age,t,c2,\
segmentLength,slabLength,distSlabEdge,\
SPcoregNor,SPcoregPar,OPcoregNor,OPcoregPar,CONVcoregNor,CONVcoregPar,\
subPolCoreg,subOblCoreg]
return (coregData)