def writer(self, array, *args, **kwargs):
if self.scale == 'SAR' and np.iscomplexobj(array):
array = np.abs(array)
array = np.squeeze(array)
out = np.zeros_like(array, dtype='uint8')
if array.ndim == 3 and self.chscl == True:
for k in range(array.shape[0]):
array[k, ...] = array[k, ...] / np.mean(array[k, ...])
if self.scale == 'SAR':
out = sarscale(array)
elif self.scale == 'phase':
out = phascale(array)
elif self.scale == 'coherence':
out = cohscale(array)
else:
logging.error("Scaling method unknown")
return False
if array.ndim == 3:
out = out[self.order, ...]
try:
misc.imsave(self.filename, out, format=self.key)
return True
except IOError as err:
logging.error("ERROR:"+str(err))
return False
else:
logging.error("UNKNOWN ERROR")
return False
def writer(self, array, *args, **kwargs):
if isinstance(self.file, tuple): # remove file type if present
self.file = self.file[0]
if (self.method == 'amplitude'
or self.method == 'intensity') and np.iscomplexobj(array):
array = np.abs(array)
array = np.squeeze(array)
if array.ndim == 4:
nchannels = np.prod(array.shape[0:array.ndim - 2])
array = np.reshape(array,
(nchannels, ) + array.shape[array.ndim - 2:])
if array.ndim == 3 and self.chscl == True:
for k in range(array.shape[0]):
array[k, ...] = array[k, ...] / np.mean(array[k, ...])
if self.method == 'intensity' or self.method == 'amplitude':
if self.method == 'amplitude':
array **= 0.7
if self.method == 'intensity':
array **= 0.35
out = sarscale(array, factor=self.scaling)
elif self.method == 'phase':
out = phascale(array)
elif self.method == 'coherence':
out = cohscale(array)
elif self.method == 'minmax':
start = array.min()
end = array.max()
out = np.uint8(
np.clip((array - start) / (end - start) * 255, 0, 255))
else:
logging.error("Scaling method unknown")
return False
if array.ndim == 3:
if out.shape[0] < 3:
oshp = out.shape
oshp[0] = 3
out = np.resize(out, oshp)
if out.shape[0] > 3:
out = out[0:3, ...]
out = np.rollaxis(np.rollaxis(out[self.order, ...], 2), 2)
else:
out = colortables(self.palette)[1][out]
try:
pilimg = Image.fromarray(out)
pilimg.save(self.file, format=self.key)
logging.info("FINISHED SAVING IMAGE")
return True
except IOError as err:
logging.error("ERROR:" + str(err))
return False
else:
logging.error("UNKNOWN ERROR")
return False
def writer(self, array, *args, **kwargs):
if isinstance(self.file, tuple): # remove file type if present
self.file = self.file[0]
if (self.method == 'amplitude' or self.method == 'intensity') and np.iscomplexobj(array):
array = np.abs(array)
array = np.squeeze(array)
if array.ndim == 4:
nchannels = np.prod(array.shape[0:array.ndim-2])
array = np.reshape(array, (nchannels, )+array.shape[array.ndim-2:])
if array.ndim == 3 and self.chscl == True:
for k in range(array.shape[0]):
array[k, ...] = array[k, ...] / np.mean(array[k, ...])
if self.method == 'intensity' or self.method == 'amplitude':
if self.method == 'amplitude':
array **= 0.7
if self.method == 'intensity':
array **= 0.35
out = sarscale(array, factor=self.scaling)
elif self.method == 'phase':
out = phascale(array)
elif self.method == 'coherence':
out = cohscale(array)
elif self.method == 'minmax':
start = array.min()
end = array.max()
out = np.uint8(np.clip((array - start) / (end - start) * 255, 0, 255))
else:
logging.error("Scaling method unknown")
return False
if array.ndim == 3:
out = np.rollaxis(np.rollaxis(out[self.order, ...], 2), 2)
else:
out = colortables(self.palette)[1][out]
try:
pilimg = Image.fromarray(out)
pilimg.save(self.file, format=self.key)
logging.info("FINISHED SAVING IMAGE")
return True
except IOError as err:
logging.error("ERROR:" + str(err))
return False
else:
logging.error("UNKNOWN ERROR")
return False
def writer(self, array, *args, **kwargs):
if isinstance(self.file, tuple): # remove file type if present
self.file = self.file[0]
if (self.method == 'amplitude'
or self.method == 'intensity') and np.iscomplexobj(array):
array = np.abs(array)
array = np.squeeze(array)
if array.ndim == 4:
nchannels = np.prod(array.shape[0:array.ndim - 2])
array = np.reshape(array,
(nchannels, ) + array.shape[array.ndim - 2:])
if array.ndim == 3 and self.chscl == True:
for k in range(array.shape[0]):
array[k, ...] = array[k, ...] / np.mean(array[k, ...])
if self.method == 'intensity' or self.method == 'amplitude':
if self.method == 'amplitude':
array **= 0.7
if self.method == 'intensity':
array **= 0.35
out = sarscale(array, factor=self.scaling)
elif self.method == 'phase':
out = phascale(array)
elif self.method == 'coherence':
out = cohscale(array)
else:
logging.error("Scaling method unknown")
return False
if array.ndim == 3:
out = np.rollaxis(np.rollaxis(out[self.order, ...], 2), 2)
else:
out = colortables(self.palette)[1][out]
try:
misc.imsave(self.file, out, format=self.key)
logging.info("FINISHED SAVING IMAGE")
return True
except IOError as err:
logging.error("ERROR:" + str(err))
return False
else:
logging.error("UNKNOWN ERROR")
return False
def writer(self, array, *args, **kwargs):
if isinstance(self.file, tuple): # remove file type if present
self.file = self.file[0]
if self.method == 'amplitude' or self.method == 'intensity' and np.iscomplexobj(
array):
array = np.abs(array)
array = np.squeeze(array)
out = np.zeros_like(array, dtype='uint8')
if array.ndim == 3 and self.chscl == True:
for k in range(array.shape[0]):
array[k, ...] = array[k, ...] / np.mean(array[k, ...])
if self.method == 'intensity' or self.method == 'amplitude':
if self.method == 'amplitude':
array **= 0.7
if self.method == 'intensity':
array **= 0.35
out = sarscale(array, factor=self.scaling)
elif self.method == 'phase':
out = phascale(array)
elif self.method == 'coherence':
out = cohscale(array)
else:
logging.error("Scaling method unknown")
return False
if array.ndim == 3:
out = out[self.order, ...]
else:
out = colortables(self.palette)[1][out]
try:
misc.imsave(self.file, out, format=self.key)
return True
except IOError as err:
logging.error("ERROR:" + str(err))
return False
else:
logging.error("UNKNOWN ERROR")
return False