def test_move(self):
data = np.random.random_sample((50, 49, 31))
test = PFData(data)
move = test.moveDataArray()
self.assertTrue(
np.array_equal(data, move),
'Data obtained from PFData::moveDataArray must match given data')
self.assertIsNone(
test.viewDataArray(),
'Calling PFData::moveDataArray must invalidate the internal data pointer'
)
def _pfb_to_array(self, file_path):
from parflowio.pyParflowio import PFData
array = None
if file_path:
full_path = get_absolute_path(file_path)
# FIXME do something with selector inside parflow-io
pfb_data = PFData(full_path)
pfb_data.loadHeader()
pfb_data.loadData()
array = pfb_data.moveDataArray()
return array
def pfread(pfbfile):
"""
Read a pfb file and return data as an ndarray
:param pfbfile: path to pfb file
:return: An ndarray of ndim=3, with shape (nz, ny, nx)
"""
if not os.path.exists(pfbfile):
raise RuntimeError(f'{pfbfile} not found')
pfb_data = PFData(pfbfile)
pfb_data.loadHeader()
pfb_data.loadData()
arr = pfb_data.moveDataArray()
pfb_data.close()
assert arr.ndim == 3, 'Only 3D arrays are supported'
return arr
def read_file(infile):
"""read an input file and return a 3d numpy array
Parameters
----------
infile : str
file to open (.pfb, .sa, .tif, .tiff)
Returns
-------
res_arr : ndarray
a 3d numpy array with data from file in (z,y,x) format with y axis 0 at bottom
"""
infile_path = Path(infile)
# get extension
ext = infile_path.suffix
file_string_path = os.fspath(infile_path)
if ext in ['.tif', '.tiff']:
res_arr = gdal.Open(file_string_path).ReadAsArray()
if len(res_arr.shape) == 2:
res_arr = res_arr[np.newaxis, ...]
# flip y axis so tiff aligns with PFB native alignment
res_arr = np.flip(res_arr, axis=1)
elif ext == '.sa': # parflow ascii file
with open(file_string_path, 'r') as fi:
header = fi.readline()
nx, ny, nz = [int(x) for x in header.strip().split(' ')]
arr = pd.read_csv(file_string_path, skiprows=1, header=None).values
res_arr = np.reshape(arr, (nz, ny, nx))[:, :, :]
elif ext == '.pfb': # parflow binary file
pfdata = PFData(file_string_path)
pfdata.loadHeader()
pfdata.loadData()
res_arr = pfdata.moveDataArray()
pfdata.close()
del pfdata
else:
raise ValueError('can not read file type ' + ext)
return res_arr
def read_array_pfb(file_name):
from parflowio.pyParflowio import PFData
data = PFData(file_name)
data.loadHeader()
data.loadData()
return data.moveDataArray()
