def unwrap_py(inph, in_p=(), uv=2 * pi):
"""Return the input matrix unwrapped the value given in uv
The same as unwrapv, but using for-s, written in python
"""
if not is_masked(inph):
fasei = MaskedArray(inph, isnan(inph))
else:
fasei = inph
nx, ny = (fasei.shape[0], fasei.shape[1])
# If the initial unwraping point is not given, take the center of the image
# as initial coordinate
if in_p == ():
in_p = (int(nx / 2), int(ny / 2))
# Create a temporal space to mark if the points are already unwrapped
# 0 the point has not been unwrapped
# 1 the point has not been unwrapped, but it is in the unwrapping list
# 2 the point was already unwrapped
fl = zeros((nx, ny))
# List containing the points to unwrap
l_un = [in_p]
fl[in_p] = 1
# unwrapped values
faseo = fasei.copy()
while len(l_un) > 0:
# remove the first value from the list
cx, cy = l_un.pop(0)
# Put the coordinates of unwrapped the neigbors in the list
# And check for wrapping
nv = 0
wv = 0
for i in range(cx - 1, cx + 2):
for j in range(cy - 1, cy + 2):
if (i > -1) and (i < nx) and (j > -1) and (j < ny):
if (fl[i, j] == 0) & (faseo.mask[i, j] == False):
fl[i, j] = 1
l_un.append((i, j))
elif fl[i, j] == 2:
wv = wv + rint((faseo[i, j] - faseo[cx, cy]) / uv)
nv = nv + 1
if nv != 0:
wv = wv / nv
fl[cx, cy] = 2
faseo[cx, cy] = faseo[cx, cy] + wv * uv
return faseo
def unwrap_py(inph,in_p=(), uv=2*pi):
"""Return the input matrix unwraped the valu given in uv
The same as unwrapv, but using for-s, written in python
"""
if not is_masked(inph):
fasei=MaskedArray(inph, isnan(inph))
else:
fasei=inph
nx, ny=(fasei.shape[0],fasei.shape[1])
# If the initial unwraping point is not given, take the center of the image
# as initial coordinate
if in_p==():
in_p=(int(nx/2),int(ny/2))
# Create a temporal space to mark if the points are already unwrapped
# 0 the point has not been unwrapped
# 1 the point has not been unwrapped, but it is in the unwrapping list
# 2 the point was already unwrapped
fl=zeros((nx, ny))
# List containing the points to unwrap
l_un=[in_p]
fl[in_p]=1
# unwrapped values
faseo=fasei.copy()
while len(l_un)>0:
# remove the first value from the list
cx, cy=l_un.pop(0)
# Put the coordinates of unwrapped the neigbors in the list
# And check for wrapping
nv=0
wv=0
for i in range(cx-1, cx+2):
for j in range(cy-1, cy+2):
if (i>-1) and (i<nx) and (j>-1) and (j<ny):
if (fl[i, j]==0)&(faseo.mask[i, j]==False):
fl[i, j]=1
l_un.append((i, j))
elif fl[i, j]==2:
wv=wv+rint((faseo[i, j]-faseo[cx, cy])/uv)
nv=nv+1
if nv!=0:
wv=wv/nv
fl[cx, cy]=2
faseo[cx, cy]=faseo[cx, cy]+wv*uv
return faseo
def sanitize_masked_array(data: ma.MaskedArray) -> np.ndarray:
"""
Convert numpy MaskedArray to ensure mask is softened.
"""
mask = ma.getmaskarray(data)
if mask.any():
data, fill_value = maybe_upcast(data, copy=True)
data.soften_mask() # set hardmask False if it was True
data[mask] = fill_value
else:
data = data.copy()
return data
def createNetCDF4(self,fpath,matrix,dtype, fillvalue = None):
if not os.path.exists(os.path.dirname(fpath)):
try:
os.makedirs(os.path.dirname(fpath))
except OSError as exc: # Guard against race condition
if exc.errno != errno.EEXIST:
raise
rootgrp = Dataset(fpath, "w", format="NETCDF4")
# add dimensions
lat = rootgrp.createDimension("lat", DileGeometry.YSIZE)
lon = rootgrp.createDimension("lon", DileGeometry.XSIZE)
# add variables
latitudes = rootgrp.createVariable("lat","f4",("lat",))
longitudes = rootgrp.createVariable("lon","f4",("lon",))
latitudes.units = 'degrees_north'
latitudes.axis = 'Y'
longitudes.units = 'degrees_east'
longitudes.axis = 'X'
bb = self.asBoundingBox()
lats = linspace(bb['lat_min'],bb['lat_max'],self.YSIZE, endpoint=True)
lons = linspace(bb['lon_min'],bb['lon_max'],self.XSIZE, endpoint=True)
latitudes[:] = lats
longitudes[:] = lons
if fillvalue:
data = rootgrp.createVariable(self.variable,dtype,("lat","lon",),fill_value = fillvalue)
else:
data = rootgrp.createVariable("data",dtype,("lat","lon",))
if isinstance(matrix, MaskedArray):
data[:] = MaskedArray.copy(matrix)
else:
data[:] = matrix
for attr in self.attributes:
if attr != '_FillValue':
data.setncattr(attr,self.attributes[attr])
rootgrp.close()
return fpath
def unwrapv(inph, in_p=(), uv=2 * pi):
"""Return the input matrix unwrapped the value given in uv
This is a vectorized routine, but is not as fast as it should
"""
if not is_masked(inph):
fasei = MaskedArray(inph, isnan(inph))
else:
fasei = inph.copy()
size = fasei.shape
nx, ny = size
# If the initial unwraping point is not given, take the center of the image
# as initial coordinate
if in_p == ():
in_p = (int(size[0] / 2), int(size[1] / 2))
# Create a temporal space to mark if the points are already unwrapped
# 0 the point has not been unwrapped
# 1 the point has not been unwrapped, but it is in the unwrapping list
# 2 the point was already unwrapped
fl = N.zeros(size)
# List containing the points to unwrap
l_un = [in_p]
fl[in_p] = 1
# unwrapped values
faseo = fasei.copy()
XI_, YI_ = meshgrid(range(-1, 2), range(-1, 2))
XI_ = XI_.flatten()
YI_ = YI_.flatten()
while len(l_un) > 0:
# remove the first value from the list
unp = l_un.pop(0)
#l_un[0:1]=[]
XI = XI_ + unp[0]
YI = YI_ + unp[1]
#Remove from the list the values where XI is negative
nxi = XI > -1
nyi = YI > -1
nxf = XI < nx
nyf = YI < ny
n = nonzero(nxi & nyi & nxf & nyf)
lco = zip(XI[n], YI[n])
# Put the coordinates of unwrapped the neigbors in the list
# And check for wrapping
nv = 0
wv = 0
for co in lco:
if (fl[co] == 0) & (faseo.mask[co] == False):
fl[co] = 1
l_un.append(co)
elif fl[co] == 2:
wv = wv + rint((faseo[co] - faseo[unp]) / uv)
nv = nv + 1
if nv != 0:
wv = wv / nv
#if wv>=0: wv=int(wv+0.5)
#else: wv=int(wv-0.5)
fl[unp] = 2
faseo[unp] = faseo[unp] + wv * uv
return faseo
def unwrapv(inph,in_p=(), uv=2*pi):
"""Return the input matrix unwraped the value given in uv
This is a vectorized routine, but is not as fast as it should
"""
if not is_masked(inph):
fasei=MaskedArray(inph, isnan(inph))
else:
fasei=inph.copy()
size=fasei.shape
nx, ny=size
# If the initial unwraping point is not given, take the center of the image
# as initial coordinate
if in_p==():
in_p=(int(size[0]/2),int(size[1]/2))
# Create a temporal space to mark if the points are already unwrapped
# 0 the point has not been unwrapped
# 1 the point has not been unwrapped, but it is in the unwrapping list
# 2 the point was already unwrapped
fl=N.zeros(size)
# List containing the points to unwrap
l_un=[in_p]
fl[in_p]=1
# unwrapped values
faseo=fasei.copy()
XI_, YI_= meshgrid(range(-1, 2), range(-1, 2))
XI_=XI_.flatten()
YI_=YI_.flatten()
while len(l_un)>0:
# remove the first value from the list
unp=l_un.pop(0)
#l_un[0:1]=[]
XI=XI_+unp[0]
YI=YI_+unp[1]
#Remove from the list the values where XI is negative
nxi=XI>-1
nyi=YI>-1
nxf=XI<nx
nyf=YI<ny
n=nonzero(nxi& nyi & nxf & nyf)
lco=zip(XI[n], YI[n])
# Put the coordinates of unwrapped the neigbors in the list
# And check for wrapping
nv=0
wv=0
for co in lco:
if (fl[co]==0) & (faseo.mask[co]==False):
fl[co]=1
l_un.append(co)
elif fl[co]==2:
wv=wv+rint((faseo[co]-faseo[unp])/uv)
nv=nv+1
if nv!=0:
wv=wv/nv
#if wv>=0: wv=int(wv+0.5)
#else: wv=int(wv-0.5)
fl[unp]=2
faseo[unp]=faseo[unp]+wv*uv
return faseo
