def __init__(self, annotated_filename, logger=None):
"""Constructor.
Args:
annotated_filename (str): full filename for annotated occurrence CSV file
logger (object): logger for saving relevant processing messages
Raises:
FileNotFoundError: on any missing file in occ_filename_list
"""
if not os.path.exists(annotated_filename):
raise FileNotFoundError(
f"File {annotated_filename} does not exist")
datapath, _ = os.path.split(annotated_filename)
self._datapath = datapath
self._csvfile = annotated_filename
if logger is None:
logger = get_logger(datapath)
# Hold all counties found in each state
self.states = {}
self._init_states()
self._log = logger
# {county_or_state: {species: count, ... }
# ... }
self.locations = {}
def __init__(self, riis_filename, logger=None):
"""Constructor sets the authority and species files and headers expected for BISON-RIIS processing.
Args:
riis_filename (str): Path to the base of the input data, used to construct full
filenames from basepath and relative path constants.
logger (object): logger for writing messages to file and console
Raises:
Exception: on unexpected file header
"""
datapath, fname_w_ext = os.path.split(riis_filename)
basename, ext = os.path.splitext(fname_w_ext)
self._datapath = datapath
self._csvfile = riis_filename
if logger is None:
logger = get_logger(datapath)
self._log = logger
self.auth_fname = f"{os.path.join(self._datapath, RIIS_AUTHORITY.FNAME)}.{RIIS.DATA_EXT}"
# Test and clean headers of non-ascii characters
self._test_header(self.auth_fname, RIIS_AUTHORITY.HEADER)
good_header = self._test_header(self._csvfile, RIIS_SPECIES.HEADER)
if good_header is False:
raise Exception(f"Unexpected file header found in {self._csvfile}")
# Trimmed and updated Non-native Species List, built from RIIS
self.by_gbif_taxkey = None
self.by_riis_id = None
self.nnsl_header = None
def __init__(self, gbif_occ_filename, nnsl=None, logger=None):
"""Constructor.
Args:
gbif_occ_filename (str): full path of CSV occurrence file to annotate
nnsl (bison.common.riis.NNSL): object containing USGS RIIS data for annotating records
logger (object): logger for saving relevant processing messages
"""
datapath, _ = os.path.split(gbif_occ_filename)
self._datapath = datapath
self._csvfile = gbif_occ_filename
if logger is None:
logger = get_logger(datapath)
self._log = logger
if nnsl is not None:
self.nnsl = nnsl
else:
riis_filename = os.path.join(datapath, RIIS_SPECIES.FNAME)
self.nnsl = NNSL(riis_filename, logger=logger)
self.nnsl.read_riis(read_resolved=True)
# Must georeference points to add new, consistent state and county fields
self._geo_county = GeoResolver(US_CENSUS_COUNTY.FILE,
US_CENSUS_COUNTY.CENSUS_BISON_MAP,
self._log)
# Input reader
self._dwcdata = DwcData(self._csvfile, logger=logger)
# Output writer
self._csv_writer = None
self._conus_states = []
for k, v in US_STATES.items():
if k not in ("Alaska", "Hawaii"):
self._conus_states.extend([k, v])
self._all_states = self._conus_states.copy()
self._all_states.extend(["Alaska", "Hawaii", "AK", "HI"])
# Test DwC record contents
self.good_locations = {}
self.bad_locations = {}
self.missing_states = 0
self.matched_states = 0
self.mismatched_states = 0
def __init__(self, occ_filename, logger=None):
"""Construct an object to read a GBIF datafile.
Args:
occ_filename(str): full path of CSV occurrence file to read
logger (object): logger for saving relevant processing messages
"""
datapath, _ = os.path.split(occ_filename)
self._datapath = datapath
self._csvfile = occ_filename
if logger is None:
logger = get_logger(datapath)
self._log = logger
# Open file
self._inf = None
# CVS DictReader and current record
self._csv_reader = None
self.dwcrec = None
"Record {} taxon key {} is not an accepted name {}".format(
rec[GBIF.ID_FLD], taxkey, taxstatus))
# Make sure simple CSV data sciname matches name for taxonkey
if rec[GBIF.NAME_FLD] != taxname:
self.logit(
"Record {} name {} does not match taxon key {} name {}".
format(rec[GBIF.ID_FLD], rec[GBIF.NAME_FLD], taxkey,
taxname))
# .............................................................................
if __name__ == "__main__":
logname = "test_gbif"
csvfile = GBIF.TEST_DATA
# Test the taxonkey contents in GBIF simple CSV download file
logger = get_logger(DATA_PATH, logname=logname)
Tst = TestGBIFData(DATA_PATH, csvfile, logger)
Tst.test_gbif_name_accepted()
"""
from test.test_gbif import *
logname = "test_gbif"
csvfile = GBIF.TEST_DATA
logger = get_logger(DATA_PATH, logname=logname)
Tst = TestGBIFData(DATA_PATH, csvfile, logger)
Tst.test_gbif_name_accepted()
"""
self.append_dwca_records()
print(f" Matched states: {self.matched_states}")
print(f" Mis-matched states: {self.mismatched_states}")
print(f" Missing states: {self.missing_states}")
print(" Good states: ")
for st, counties in self.good_locations.items():
print(f" {st}: {counties}")
print(" Bad states: ")
for st, counties in self.bad_locations.items():
print(f" {st}: {counties}")
# .............................................................................
if __name__ == "__main__":
# Test the taxonkey contents in GBIF simple CSV download file
logger = get_logger(DATA_PATH, logname="test_annotate")
nnsl_data = NNSL(DATA_PATH, logger=logger)
big_gbif_fname = os.path.join(DATA_PATH, GBIF.TEST_DATA)
chunk_fnames = chunk_files(big_gbif_fname)
for fname in chunk_fnames:
tst = TestAnnotator(fname, do_resolve=False, logger=logger)
tst.test_annotate_records()
"""
from test.test_annotate import *
outpath = "/tmp"
logname = "test_annotate"
csvfile = GBIF.TEST_DATA
logger = get_logger(DATA_PATH, logname=logname)
if is_test:
test_fname = RIIS_SPECIES.TEST_FNAME
resolved_nnsl = NNSL(DATA_PATH, test_fname=test_fname)
resolved_nnsl.read_riis(read_resolved=True)
# Count originals
for occid in self.nnsl_by_id.keys():
try:
resolved_nnsl.nnsl_by_id[occid]
except KeyError:
logit(self._log, "Missing record {}".format(occid))
# .............................................................................
if __name__ == "__main__":
logger = get_logger(DATA_PATH, "test_riis_resolve")
tt = TestRIISTaxonomy(DATA_PATH, logger=logger)
tt.test_missing_taxon_authority_resolution()
tt.test_taxonomy_keys()
tt.test_duplicate_name_localities()
tt.test_gbif_resolution_inconsistency()
tt.test_itis_resolution_inconsistency()
tt = None
# These overwrite resolved test data RIIS species w/ 100 records
tt = TestRIISTaxonomy(DATA_PATH,
test_fname=RIIS_SPECIES.TEST_FNAME,
logger=logger)
tt.test_resolve_gbif()
tt.test_resolution_output(is_test=True)
args = parser.parse_args()
cmd = args.cmd
big_csv_filename = os.path.join(DATA_PATH, args.big_csv_filename)
do_split = True if args.do_split.lower() in ("yes", "y", "true",
"1") else False
# ...............................................
# Test data
# ...............................................
cmd = "summarize_assessments"
big_csv_filename = os.path.join(DATA_PATH, "gbif_2022-03-16_100k.csv")
# ...............................................
# ...............................................
logger = get_logger(DATA_PATH, logname=f"main_{cmd}")
logger.info(f"Command: {cmd}")
if cmd == "resolve":
resolved_riis_filename = resolve_riis_taxa(riis_filename, logger)
print(resolved_riis_filename)
log_output(logger, f"Resolved RIIS filename: {resolved_riis_filename}")
elif cmd == "split":
input_filenames = find_or_create_subset_files(big_csv_filename, logger)
log_output(logger, "Input filenames:", outlist=input_filenames)
else:
if do_split is True:
input_filenames = find_or_create_subset_files(
big_csv_filename, logger)
else:
input_filenames = [big_csv_filename]
# Make sure files to be processed exist
