def gridmatch(lmod, ctxt, rtxt):
""" Matches the rows and columns of the second grid to the first
grid """
rgrv = lmod.griddata[rtxt]
cgrv = lmod.griddata[ctxt]
data = rgrv
data2 = cgrv
orig_wkt = data.wkt
orig_wkt2 = data2.wkt
doffset = 0.0
if data.data.min() <= 0:
doffset = data.data.min() - 1.
data.data = data.data - doffset
rows, cols = data.data.shape
rows2, cols2 = data2.data.shape
gtr0 = data.get_gtr()
gtr = data2.get_gtr()
src = data_to_gdal_mem(data, gtr0, orig_wkt, cols, rows)
dest = data_to_gdal_mem(data, gtr, orig_wkt2, cols2, rows2, True)
gdal.ReprojectImage(src, dest, orig_wkt, orig_wkt2, gdal.GRA_Bilinear)
dat = gdal_to_dat(dest, data.dataid)
if doffset != 0.0:
dat.data = dat.data + doffset
data.data = data.data + doffset
return dat.data
def gridmatch(lmod, ctxt, rtxt):
""" Matches the rows and columns of the second grid to the first
grid """
rgrv = lmod.griddata[rtxt]
cgrv = lmod.griddata[ctxt]
data = rgrv
data2 = cgrv
orig_wkt = data.wkt
orig_wkt2 = data2.wkt
doffset = 0.0
if data.data.min() <= 0:
doffset = data.data.min()-1.
data.data = data.data - doffset
gtr0 = (data.tlx, data.xdim, 0.0, data.tly, 0.0, -data.ydim)
gtr = (data2.tlx, data2.xdim, 0.0, data2.tly, 0.0, -data2.ydim)
src = data_to_gdal_mem(data, gtr0, orig_wkt, data.cols, data.rows)
dest = data_to_gdal_mem(data, gtr, orig_wkt2, data2.cols, data2.rows, True)
gdal.ReprojectImage(src, dest, orig_wkt, orig_wkt2, gdal.GRA_Bilinear)
dat = gdal_to_dat(dest, data.dataid)
if doffset != 0.0:
dat.data = dat.data + doffset
data.data = data.data + doffset
return dat.data
def gridmatch(lmod, ctxt, rtxt):
""" Matches the rows and columns of the second grid to the first
grid """
rgrv = lmod.griddata[rtxt]
cgrv = lmod.griddata[ctxt]
data = rgrv
data2 = cgrv
orig_wkt = data.wkt
orig_wkt2 = data2.wkt
doffset = 0.0
if data.data.min() <= 0:
doffset = data.data.min()-1.
data.data = data.data - doffset
gtr0 = (data.tlx, data.xdim, 0.0, data.tly, 0.0, -data.ydim)
gtr = (data2.tlx, data2.xdim, 0.0, data2.tly, 0.0, -data2.ydim)
src = data_to_gdal_mem(data, gtr0, orig_wkt, data.cols, data.rows)
dest = data_to_gdal_mem(data, gtr, orig_wkt2, data2.cols, data2.rows, True)
gdal.ReprojectImage(src, dest, orig_wkt, orig_wkt2, gdal.GRA_Bilinear)
dat = gdal_to_dat(dest, data.dataid)
if doffset != 0.0:
dat.data = dat.data + doffset
data.data = data.data + doffset
return dat.data
def gmerge(master, slave, xrange=None, yrange=None):
"""
This routine is used to merge two grids.
"""
if xrange is None or yrange is None:
return master
xdim = master.xdim
ydim = master.ydim
orig_wkt = master.wkt
xmin = xrange[0]
xmax = xrange[-1]
ymin = yrange[0]
ymax = yrange[-1]
cols = int((xmax - xmin) // xdim) + 1
rows = int((ymax - ymin) // ydim) + 1
gtr = (xmin, xdim, 0.0, ymax, 0.0, -ydim)
dat = []
for data in [master, slave]:
doffset = 0.0
if data.data.min() <= 0:
doffset = data.data.min() - 1.
data.data -= doffset
data.data.set_fill_value(0)
tmp = data.data.filled()
data.data = np.ma.masked_equal(tmp, 0)
data.nullvalue = 0
drows, dcols = data.data.shape
gtr0 = data.get_gtr()
src = data_to_gdal_mem(data, gtr0, orig_wkt, dcols, drows)
dest = data_to_gdal_mem(data, gtr, orig_wkt, cols, rows, True)
gdal.ReprojectImage(src, dest, orig_wkt, orig_wkt, gdal.GRA_Bilinear)
dat.append(gdal_to_dat(dest, data.dataid))
dat[-1].data = np.ma.masked_outside(dat[-1].data, 0.1,
data.data.max() + 1000)
dat[-1].data += doffset
dat[-1].data.set_fill_value(1e+20)
tmp = dat[-1].data.filled()
dat[-1].data = np.ma.masked_equal(tmp, 1e+20)
dat[-1].nullvalue = 1e+20
imask = np.logical_and(dat[0].data.mask, np.logical_not(dat[1].data.mask))
if imask.size > 1:
dat[0].data.data[imask] = dat[1].data.data[imask]
dat[0].data.mask[imask] = False
return dat[0]
def gmerge(master, slave, xrange=None, yrange=None):
"""
This routine is used to merge two grids.
"""
if xrange is None or yrange is None:
return master
xdim = master.xdim
ydim = master.ydim
orig_wkt = master.wkt
xmin = xrange[0]
xmax = xrange[-1]
ymin = yrange[0]
ymax = yrange[-1]
cols = int((xmax - xmin)//xdim)+1
rows = int((ymax - ymin)//ydim)+1
gtr = (xmin, xdim, 0.0, ymax, 0.0, -ydim)
dat = []
for data in [master, slave]:
doffset = 0.0
if data.data.min() <= 0:
doffset = data.data.min()-1.
data.data -= doffset
data.data.set_fill_value(0)
tmp = data.data.filled()
data.data = np.ma.masked_equal(tmp, 0)
data.nullvalue = 0
gtr0 = (data.tlx, data.xdim, 0.0, data.tly, 0.0, -data.ydim)
src = data_to_gdal_mem(data, gtr0, orig_wkt, data.cols, data.rows)
dest = data_to_gdal_mem(data, gtr, orig_wkt, cols, rows, True)
gdal.ReprojectImage(src, dest, orig_wkt, orig_wkt, gdal.GRA_Bilinear)
dat.append(gdal_to_dat(dest, data.dataid))
dat[-1].data = np.ma.masked_outside(dat[-1].data, 0.1,
data.data.max() + 1000)
dat[-1].data += doffset
dat[-1].data.set_fill_value(1e+20)
tmp = dat[-1].data.filled()
dat[-1].data = np.ma.masked_equal(tmp, 1e+20)
dat[-1].nullvalue = 1e+20
imask = np.logical_and(dat[0].data.mask == True, dat[1].data.mask == False)
if imask.size > 1:
dat[0].data.data[imask] = dat[1].data.data[imask]
dat[0].data.mask[imask] = False
return dat[0]
def gridmatch(lmod, ctxt, rtxt):
"""
Matches the rows and columns of the second grid to the first
grid.
Parameters
----------
lmod : LithModel
Lithology Model.
ctxt : str
First grid text label.
rtxt : str
Second grid text label.
Returns
-------
dat : numpy array
Numpy array of data.
"""
rgrv = lmod.griddata[rtxt]
cgrv = lmod.griddata[ctxt]
data = rgrv
data2 = cgrv
orig_wkt = data.wkt
orig_wkt2 = data2.wkt
doffset = 0.0
if data.data.min() <= 0:
doffset = data.data.min() - 1.
data.data = data.data - doffset
rows, cols = data.data.shape
rows2, cols2 = data2.data.shape
gtr0 = data.get_gtr()
gtr = data2.get_gtr()
src = data_to_gdal_mem(data, gtr0, orig_wkt, cols, rows)
dest = data_to_gdal_mem(data, gtr, orig_wkt2, cols2, rows2, True)
gdal.ReprojectImage(src, dest, orig_wkt, orig_wkt2, gdal.GRA_Bilinear)
dat = gdal_to_dat(dest, data.dataid)
if doffset != 0.0:
dat.data = dat.data + doffset
data.data = data.data + doffset
return dat.data
def gmerge(master, slave, xrange=None, yrange=None):
"""
This routine is used to merge two grids.
Parameters
----------
master : PyGMI Data
PyGMI raster dataset.
slave : PyGMI Data
PyGMI raster dataset.
xrange : list, optional
List containg range of minimum and maximum X. The default is None.
yrange : list, optional
List containg range of minimum and maximum Y. The default is None.
Returns
-------
PyGMI Data
PyGMI raster dataset.
"""
if xrange is None or yrange is None:
return master
xdim = master.xdim
ydim = master.ydim
orig_wkt = master.wkt
xmin = xrange[0]
xmax = xrange[-1]
ymin = yrange[0]
ymax = yrange[-1]
cols = int((xmax - xmin) // xdim) + 1
rows = int((ymax - ymin) // ydim) + 1
gtr = (xmin, xdim, 0.0, ymax, 0.0, -ydim)
dat = []
for data in [master, slave]:
doffset = 0.
data.data = data.data.astype(float)
if data.data.min() <= 0.:
doffset = data.data.min() - 1.
data.data = data.data - doffset
data.data.set_fill_value(0.)
tmp = data.data.filled()
data.data = np.ma.masked_equal(tmp, 0.)
data.nullvalue = 0
drows, dcols = data.data.shape
gtr0 = data.get_gtr()
src = data_to_gdal_mem(data, gtr0, orig_wkt, dcols, drows)
dest = data_to_gdal_mem(data, gtr, orig_wkt, cols, rows, True)
gdal.ReprojectImage(src, dest, orig_wkt, orig_wkt, gdal.GRA_Bilinear)
dat.append(gdal_to_dat(dest, data.dataid))
dat[-1].data = np.ma.masked_outside(dat[-1].data, 0.1,
data.data.max() + 1000)
dat[-1].data = dat[-1].data + doffset
dat[-1].data.set_fill_value(1e+20)
tmp = dat[-1].data.filled()
dat[-1].data = np.ma.masked_equal(tmp, 1e+20)
dat[-1].nullvalue = 1e+20
imask = np.logical_and(dat[0].data.mask, np.logical_not(dat[1].data.mask))
if imask.size > 1:
dat[0].data.data[imask] = dat[1].data.data[imask]
dat[0].data.mask[imask] = False
return dat[0]