def __init__(self, basis_dir, grid_dir, gap_data_list, flag=1,
file_name="fort.14", table_folder=None,
executable_dir=None):
"""
Initalizes a gridInfo object and sets up a directory with links to the
necessary input files to run :program:`Griddata_v1.1.32.F90` from
within that directory.
To run in parallel use :program:`mpirun` or :program:`ibrun`. If
:program:`Griddata_v1.32.F90` has been compiled using the ``DGHIGHMEM``
option make sure to correctly set ``OMP_NUM_THREADS`` to be the number
of processors per node. Then the number of mpi tasks should be set to
the number of nodes.
:param string basis_dir: the path to create the landuse_##
directories in
:param string grid_dir: the path where the ``fort.14`` formatted file
is located, there also needs to be a ``fort.13`` formatted file
here to use as a template
:param gap_data_list: a list() of
:class:`~polyadcirc.pyGriddata.table_management.gapInfo` objects
:type gap_data_list: list
:param int flag: flag to choose which averaging scheme to use ..see::
:meth:`~polyadcirc.pyADCIRC.flag_fort14.flag_fort14`
:param string file_name: the name of the ``fort.14`` formatted file in
``grid_dir``
:param string table_folder: The folder containing the ``*.table`` file.
This is ONLY necessary when running simutaneous copies of the
:program:`Griddata`.
:param string executable_dir: path to the directory containing the
compiled ``Griddata_*.out`` executable
"""
self.file_name = file_name #: Name of grid file, ``*.14``
self.grid_dir = grid_dir #: path for the dir of the grid file
self.gap_data_files = gap_data_list #: a list of gapInfo objects
self.basis_dir = basis_dir #: path for the dir to create landuse_ in
self.table_folder = table_folder #: path for the dir with ``*.table``
""" list() of :class:`~polyadcirc.table_management.gapInfo` objects """
self.__landclasses = []
self.__unique_tables = {}
for gap in self.gap_data_files:
#: dict of unique ``*.table`` files used
self.__unique_tables[gap.table.file_name] = gap.table
for k, v in self.__unique_tables.iteritems():
for x in v.get_landclasses():
#: list of landclasses used by this grid
self.__landclasses.append((x, k))
self.flag = flag #: averaging scheme flag
if rank == 0:
# Look for ``fort.14`` formatted file in grid_dir and place a link
# to it in basis_dir
fm.symlink(os.path.join(grid_dir, file_name),
os.path.join(basis_dir, file_name))
flagged_file_name = f14.flag_go(self, flag)
self.file_name = os.path.basename(flagged_file_name)
# check to see if Griddata is here
if executable_dir is None:
executable_dir = sys.path
else:
executable_dir = [executable_dir]
if len(glob.glob(os.path.join(self.basis_dir,
'Griddata_*.out'))) == 0:
# check to see if Griddata is compiled and on the python path
compiled_prog = None
for p in executable_dir:
locations1 = glob.glob(os.path.join(p, "*Griddata_*.out"))
locations2 = glob.glob(os.path.join(p, "polyadcirc",
"pyGriddata",
"Griddata_*.out"))
if locations1:
compiled_prog = locations1[0]
elif locations2:
compiled_prog = locations2[0]
else:
compiled_prog = None
break
# put link to Griddata here
if compiled_prog:
fm.symlink(compiled_prog,
os.path.join(basis_dir,
os.path.basename(compiled_prog)))
else:
print """Compile a copy of Griddata_v1.32.F90 and specify
it's location using executable_dir"""
# Create links to gap files (*.asc) using gap_list of gapInfo
# objects
for gap in self.gap_data_files:
local_file_name = os.path.basename(gap.file_name)
fm.symlink(gap.file_name, os.path.join(basis_dir,
local_file_name))
if os.path.exists(gap.file_name+'.binary'):
fm.symlink(gap.file_name+'.binary',
os.path.join(basis_dir,
local_file_name+'.binary'))
gap.file_name = local_file_name
self.file_name = comm.bcast(self.file_name, root=0)
super(gridInfo, self).__init__()
def prep_all(self, removeBinaries=False, class_nums=None, condense=True,
TOL=None):
"""
Assumes that all the necessary input files are in ``self.basis_dir``.
This function generates a ``landuse_##`` folder in ``self.basis_dir``
for every land classification number containing a ``fort.13`` file
specific to that land classification number.
.. todo:: Update so that landuse folders can be prepped n at a time and
so that this could be run on a HPC system
Currently, the parallel option preps the first folder and then all the
remaining folders at once.
:param binary parallel: Flag whether or not to simultaneously prep
landuse folders.
:param binary removeBinarues: Flag whether or not to remove
``*.asc.binary`` files when completed.
:param list class_nums: List of integers indicating which classes to
prep. This assumes all the ``*.asc.binary`` files are already in
existence.
:param bool condense: Flag whether or not to condense ``fort.13`` to
only non-zero values within a tolerance.
:param double TOL: Tolerance below which to consider a Manning's n
value to be zero if ``condense == True``
"""
if class_nums is None:
class_nums = range(len(self.__landclasses))
if rank > class_nums:
print "There are more MPI TASKS than land classes."
print "This code only scales to MPI_TASKS = len(land_classes)."
print "Extra MPI TASKS will not be used."
return
# Are there any binary files?
binaries = glob.glob(os.path.join(self.basis_dir, '*.asc.binary'))
# If not create them
if not(binaries) and rank == 0:
# set up first landuse folder
first_script = self.setup_landuse_folder(class_nums[0])
# set up remaining land-use classifications
script_list = self.setup_landuse_folders(False)
# run grid_all_data in this folder
subprocess.call(['./'+first_script], cwd=self.basis_dir)
class_nums.remove(0)
landuse_folder = 'landuse_00'
self.cleanup_landuse_folder(os.path.join(self.basis_dir,
landuse_folder))
fm.rename13([landuse_folder], self.basis_dir)
if condense:
print "Removing values below TOL"
landuse_folder_path = os.path.join(self.basis_dir,
landuse_folder)
# read fort.13 file
mann_dict = f13.read_nodal_attr_dict(landuse_folder_path)
# condense fort.13 file
condensed_bv = tmm.condense_bv_dict(mann_dict, TOL)
# write new file
f13.update_mann(condensed_bv, landuse_folder_path)
elif rank == 0:
script_list = self.setup_landuse_folders()
else:
script_list = None
class_nums = None
class_nums = comm.bcast(class_nums, root=0)
script_list = comm.bcast(script_list, root=0)
if len(class_nums) != len(script_list):
temp = [script_list[i] for i in class_nums]
script_list = temp
# run remaining bash scripts
for i in range(0+rank, len(script_list), size):
# run griddata
subprocess.call(['./'+script_list[i]], cwd=self.basis_dir)
# clean up folder
match_string = r"grid_all_(.*)_"+self.file_name[:-3]+r"\.sh"
landuse_folder = re.match(match_string, script_list[i]).groups()[0]
self.cleanup_landuse_folder(os.path.join(self.basis_dir,
landuse_folder))
# rename fort.13 file
fm.rename13([landuse_folder], self.basis_dir)
if condense:
print "Removing values below TOL"
landuse_folder_path = os.path.join(self.basis_dir,
landuse_folder)
# read fort.13 file
mann_dict = f13.read_nodal_attr_dict(landuse_folder_path)
# condense fort.13 file
condensed_bv = tmm.condense_bv_dict(mann_dict, TOL)
# write new file
f13.update_mann(condensed_bv, landuse_folder_path)
print "Done"
# remove unnecessary files
if removeBinaries and rank == 0:
binaries = glob.glob(os.path.join(self.basis_dir, '*.asc.binary'))
for f in binaries:
os.remove(f)