def test_append_random_one_arg(self):
base_name = "tmp_abc"
size = 10
full_name = utils.append_random(base_name, size)
self.assertIn(base_name, full_name)
self.assertGreater(len(full_name), len(base_name))
self.assertGreaterEqual(len(full_name), len(base_name) + size)
self.assertTrue(legal_name(full_name))
full_name2 = utils.append_random(base_name, size)
self.assertNotEqual(full_name, full_name2)
def test_append_random_suffix(self):
base_name = "tmp_abc"
size = 10
full_name = utils.append_random(base_name, suffix_length=size)
self.assertIn(base_name, full_name)
self.assertGreater(len(full_name), len(base_name))
self.assertGreaterEqual(len(full_name), len(base_name) + size)
self.assertTrue(legal_name(full_name))
full_name2 = utils.append_random(base_name, suffix_length=size)
# There is a low chance of collision.
self.assertNotEqual(full_name, full_name2)
def main():
options, flags = gs.parser()
original = options["input"]
output = options["output"]
cats = options["cats"]
rules = parse(original, cats)
if flags["c"] and flags["s"]:
gs.warning(
_("The extent of the output reclassified raster cannot be changed")
)
if flags["s"]:
reclass(original, output, rules)
else:
output_tmp = append_random("tmp", 8)
TMP.append(output_tmp)
reclass(original, output_tmp, rules)
if flags["c"]:
gs.use_temp_region()
atexit.register(gs.del_temp_region)
gs.run_command("g.region", zoom=output_tmp)
gs.mapcalc(output + " = " + output_tmp)
gs.run_command("r.colors", map=output, raster=original, quiet=True)
gs.raster_history(output)
def patch_analysis_per_subregion_parallel(development_diff, subregions,
threshold, tmp_clump, tmp_name,
nprocs):
gcore.run_command("r.clump",
input=development_diff,
output=tmp_clump,
overwrite=True,
quiet=True)
cats = (gcore.read_command("r.describe",
flags="1n",
map=subregions,
quiet=True).strip().splitlines())
params = []
toremove = []
for cat in cats:
tmp_clump_cat = append_random(tmp_name, suffix_length=8)
toremove.append(tmp_clump_cat)
params.append((tmp_clump_cat, subregions, cat, tmp_clump, threshold))
with Pool(processes=nprocs) as pool:
results = pool.map_async(analyse_subregion, params).get()
subregions_data = dict(zip(cats, results))
gcore.run_command("g.remove",
type="raster",
flags="f",
name=toremove,
quiet=True)
return subregions_data