def cleanup():
if temporary_vect:
if gscript.find_file(temporary_vect, element='vector')['name']:
gscript.run_command('g.remove', flags='f', type_='vector',
name=temporary_vect, quiet=True)
if gscript.db_table_exist(temporary_vect):
gscript.run_command('db.execute',
sql='DROP TABLE %s' % temporary_vect,
quiet=True)
def cleanup():
if temporary_vect:
if gscript.find_file(temporary_vect, element="vector")["name"]:
gscript.run_command("g.remove",
flags="f",
type_="vector",
name=temporary_vect,
quiet=True)
if gscript.db_table_exist(temporary_vect):
gscript.run_command("db.execute",
sql="DROP TABLE %s" % temporary_vect,
quiet=True)
def main():
table = options['table']
force = flags['f']
if not options['driver'] or not options['database']:
# check if DB parameters are set, and if not set them.
grass.run_command('db.connect', flags='c', quiet=True)
kv = grass.db_connection()
if options['database']:
database = options['database']
else:
database = kv['database']
if options['driver']:
driver = options['driver']
else:
driver = kv['driver']
# schema needed for PG?
if force:
grass.message(_("Forcing ..."))
# check if table exists
if not grass.db_table_exist(table):
grass.warning(
_("Table <%s> not found in database <%s>") % (table, database))
sys.exit(0)
# check if table is used somewhere (connected to vector map)
used = grass.db.db_table_in_vector(table)
if used:
grass.warning(
_("Deleting table <%s> which is attached to following map(s):") %
table)
for vect in used:
grass.warning("%s" % vect)
if not force:
grass.message(_("The table <%s> would be deleted.") % table)
grass.message("")
grass.message(
_("You must use the force flag to actually remove it. Exiting."))
sys.exit(0)
p = grass.feed_command('db.execute',
input='-',
database=database,
driver=driver)
p.stdin.write(encode("DROP TABLE " + table))
p.stdin.close()
p.wait()
if p.returncode != 0:
grass.fatal(_("Cannot continue (problem deleting table)."))
def main():
table = options['table']
force = flags['f']
if not options['driver'] or not options['database']:
# check if DB parameters are set, and if not set them.
grass.run_command('db.connect', flags='c')
kv = grass.db_connection()
if options['database']:
database = options['database']
else:
database = kv['database']
if options['driver']:
driver = options['driver']
else:
driver = kv['driver']
# schema needed for PG?
if force:
grass.message(_("Forcing ..."))
# check if table exists
if not grass.db_table_exist(table):
grass.fatal(_("Table <%s> not found in database <%s>") %
(table, database))
# check if table is used somewhere (connected to vector map)
used = grass.db.db_table_in_vector(table)
if used:
grass.warning(_("Deleting table <%s> which is attached to following map(s):") % table)
for vect in used:
grass.warning("%s" % vect)
if not force:
grass.message(_("The table <%s> would be deleted.") % table)
grass.message("")
grass.message(_("You must use the force flag to actually remove it. Exiting."))
sys.exit(0)
p = grass.feed_command('db.execute', input='-', database=database,
driver=driver)
p.stdin.write("DROP TABLE " + table)
p.stdin.close()
p.wait()
if p.returncode != 0:
grass.fatal(_("Cannot continue (problem deleting table)."))
def main():
table = options['table']
force = flags['f']
# check if DB parameters are set, and if not set them.
grass.run_command('db.connect', flags = 'c')
kv = grass.db_connection()
database = kv['database']
driver = kv['driver']
# schema needed for PG?
if force:
grass.message(_("Forcing ..."))
# check if table exists
nuldev = file(os.devnull, 'w')
if not grass.db_table_exist(table, stdout = nuldev, stderr = nuldev):
grass.fatal(_("Table <%s> not found in current mapset") % table)
# check if table is used somewhere (connected to vector map)
used = []
vects = grass.list_strings('vect')
for vect in vects:
for f in grass.vector_db(vect, stderr = nuldev).itervalues():
if not f:
continue
if f['table'] == table:
used.append(vect)
break
if used:
grass.warning(_("Deleting table <%s> which is attached to following map(s):") % table)
for vect in used:
grass.message(vect)
if not force:
grass.message(_("The table <%s> would be deleted.") % table)
grass.message("")
grass.message(_("You must use the force flag to actually remove it. Exiting."))
sys.exit(0)
p = grass.feed_command('db.execute', input = '-', database = database, driver = driver)
p.stdin.write("DROP TABLE " + table)
p.stdin.close()
p.wait()
if p.returncode != 0:
grass.fatal(_("Cannot continue (problem deleting table)."))
def cleanup():
if temporary_vect:
if gscript.find_file(temporary_vect, element='vector')['name']:
gscript.run_command('g.remove', flags='f', type_='vector',
name=temporary_vect, quiet=True)
if gscript.db_table_exist(temporary_vect):
gscript.run_command('db.execute',
sql='DROP TABLE %s' % temporary_vect,
quiet=True)
if insert_sql:
os.remove(insert_sql)
if stats_temp_file:
os.remove(stats_temp_file)
if rasters:
for tempfile in glob.glob(stats_temp_file + ".*"):
os.remove(tempfile)
def cleanup():
if temporary_vect:
if gscript.find_file(temporary_vect, element="vector")["name"]:
gscript.run_command(
"g.remove", flags="f", type_="vector", name=temporary_vect, quiet=True
)
if gscript.db_table_exist(temporary_vect):
gscript.run_command(
"db.execute", sql="DROP TABLE %s" % temporary_vect, quiet=True
)
if insert_sql:
os.remove(insert_sql)
if stats_temp_file:
os.remove(stats_temp_file)
if rasters:
for tempfile in glob.glob(stats_temp_file + ".*"):
os.remove(tempfile)
def main():
global insert_sql
insert_sql = None
global temporary_vect
temporary_vect = None
global stats_temp_file
stats_temp_file = None
global content
content = None
global raster
raster = options['raster']
global decimals
decimals = int(options['decimals'])
global zone_map
zone_map = options['zone_map']
csvfile = options['csvfile'] if options['csvfile'] else []
separator = gscript.separator(options['separator'])
prefix = options['prefix'] if options['prefix'] else []
classes_list = options['classes_list'].split(
',') if options['classes_list'] else []
vectormap = options['vectormap'] if options['vectormap'] else []
prop = False if 'proportion' not in options['statistics'].split(
',') else True
mode = False if 'mode' not in options['statistics'].split(',') else True
# Check if input layer is CELL
if gscript.parse_command('r.info', flags='g',
map=raster)['datatype'] != 'CELL':
gscript.fatal(
_("The type of the input map 'raster' is not CELL. Please use raster with integer values"
))
if gscript.parse_command('r.info', flags='g',
map=zone_map)['datatype'] != 'CELL':
gscript.fatal(
_("The type of the input map 'zone_map' is not CELL. Please use raster with integer values"
))
# Check if 'decimals' is + and with credible value
if decimals <= 0:
gscript.fatal(_("The number of decimals should be positive"))
if decimals > 100:
gscript.fatal(_("The number of decimals should not be more than 100"))
# Adjust region to input map is flag active
if flags['r']:
gscript.use_temp_region()
gscript.run_command('g.region', raster=zone_map)
# R.STATS
tmpfile = gscript.tempfile()
try:
if flags['n']:
gscript.run_command(
'r.stats',
overwrite=True,
flags='c',
input='%s,%s' % (zone_map, raster),
output=tmpfile,
separator=separator) # Consider null values in R.STATS
else:
gscript.run_command(
'r.stats',
overwrite=True,
flags='cn',
input='%s,%s' % (zone_map, raster),
output=tmpfile,
separator=separator) # Do not consider null values in R.STATS
gscript.message(_("r.stats command finished..."))
except:
gscript.fatal(_("The execution of r.stats failed"))
# COMPUTE STATISTICS
# Open csv file and create a csv reader
rstatsfile = open(tmpfile, 'r')
reader = csv.reader(rstatsfile, delimiter=separator)
# Total pixels per category per zone
totals_dict = {}
for row in reader:
if row[0] not in totals_dict: # Will pass the condition only if the current zone ID does not exists in the dictionary
totals_dict[row[0]] = {
} # Declare a new embedded dictionnary for the current zone ID
totals_dict[row[0]][row[1]] = int(row[2])
# Delete key '*' in 'totals_dict' that could append if there are null values on the zone raster
if '*' in totals_dict:
del totals_dict['*']
# Close file
rstatsfile.close()
# Mode
if mode:
modalclass_dict = {}
for ID in totals_dict:
# The trick was found here : https://stackoverflow.com/a/268285/8013239
mode = max(iter(totals_dict[ID].items()),
key=operator.itemgetter(1))[0]
if mode == '*': # If the mode is NULL values
modalclass_dict[ID] = 'NULL'
else:
modalclass_dict[ID] = mode
# Classes proportions
if prop:
# Get list of categories to output
if classes_list: #If list of classes provided by user
class_dict = {str(a): ''
for a in classes_list
} #To be sure it's string format
else:
class_dict = {}
# Proportion of each category per zone
proportion_dict = {}
for ID in totals_dict:
proportion_dict[ID] = {}
for cl in totals_dict[ID]:
if flags['p']:
proportion_dict[ID][cl] = round(
float(totals_dict[ID][cl]) /
sum(totals_dict[ID].values()) * 100, decimals)
else:
proportion_dict[ID][cl] = round(
float(totals_dict[ID][cl]) /
sum(totals_dict[ID].values()), decimals)
if cl == '*':
class_dict['NULL'] = ''
else:
class_dict[cl] = ''
# Fill class not met in the raster with zero
for ID in proportion_dict:
for cl in class_dict:
if cl not in proportion_dict[ID].keys():
proportion_dict[ID][cl] = '{:.{}f}'.format(0, decimals)
# Get list of class sorted by value (arithmetic)
if 'NULL' in class_dict.keys():
class_list = [int(k) for k in class_dict.keys() if k != 'NULL']
class_list.sort()
class_list.append('NULL')
else:
class_list = [int(k) for k in class_dict.keys()]
class_list.sort()
gscript.verbose(_("Statistics computed..."))
# OUTPUT CONTENT
# Header
header = [
'cat',
]
if mode:
if prefix:
header.append('%s_mode' % prefix)
else:
header.append('mode')
if prop:
if prefix:
[header.append('%s_prop_%s' % (prefix, cl)) for cl in class_list]
else:
[header.append('prop_%s' % cl) for cl in class_list]
# Values
value_dict = {}
for ID in totals_dict:
value_dict[ID] = []
if mode:
value_dict[ID].append(modalclass_dict[ID])
if prop:
for cl in class_list:
value_dict[ID].append(proportion_dict[ID]['%s' % cl])
# WRITE OUTPUT
if csvfile:
outfile = open(csvfile, 'w')
writer = csv.writer(outfile, delimiter=separator)
writer.writerow(header)
csvcontent_dict = copy.deepcopy(value_dict)
[csvcontent_dict[ID].insert(0, ID) for ID in csvcontent_dict]
[csvcontent_dict[ID] for ID in csvcontent_dict]
writer.writerows(csvcontent_dict.values())
outfile.close()
if vectormap:
gscript.message(_("Creating output vector map..."))
temporary_vect = 'rzonalclasses_tmp_vect_%d' % os.getpid()
gscript.run_command('r.to.vect',
input_=zone_map,
output=temporary_vect,
type_='area',
flags='vt',
overwrite=True,
quiet=True)
insert_sql = gscript.tempfile()
fsql = open(insert_sql, 'w')
fsql.write('BEGIN TRANSACTION;\n')
if gscript.db_table_exist(temporary_vect):
if gscript.overwrite():
fsql.write('DROP TABLE %s;' % temporary_vect)
else:
gscript.fatal(
_("Table %s already exists. Use --o to overwrite") %
temporary_vect)
create_statement = 'CREATE TABLE ' + temporary_vect + ' (cat int PRIMARY KEY);\n'
fsql.write(create_statement)
for col in header[1:]:
if col.split('_')[-1] == 'mode': # Mode column should be integer
addcol_statement = 'ALTER TABLE %s ADD COLUMN %s integer;\n' % (
temporary_vect, col)
else: # Proportions column should be double precision
addcol_statement = 'ALTER TABLE %s ADD COLUMN %s double precision;\n' % (
temporary_vect, col)
fsql.write(addcol_statement)
for key in value_dict:
insert_statement = 'INSERT INTO %s VALUES (%s, %s);\n' % (
temporary_vect, key, ','.join(
[str(x) for x in value_dict[key]]))
fsql.write(insert_statement)
fsql.write('END TRANSACTION;')
fsql.close()
gscript.run_command('db.execute', input=insert_sql, quiet=True)
gscript.run_command('v.db.connect',
map_=temporary_vect,
table=temporary_vect,
quiet=True)
gscript.run_command('g.copy',
vector='%s,%s' % (temporary_vect, vectormap),
quiet=True)
def main():
global insert_sql
insert_sql = None
global temporary_vect
temporary_vect = None
global stats_temp_file
stats_temp_file = None
segment_map = options['map']
csvfile = options['csvfile'] if options['csvfile'] else []
vectormap = options['vectormap'] if options['vectormap'] else []
global rasters
rasters = options['rasters'].split(',') if options['rasters'] else []
area_measures = options['area_measures'].split(',') if (
options['area_measures'] and not flags['s']) else []
if area_measures:
if not gscript.find_program('r.object.geometry', '--help'):
message = _(
"You need to install the addon r.object.geometry to be able")
message += _(" to calculate area measures.\n")
message += _(
" You can install the addon with 'g.extension r.object.geometry'"
)
gscript.fatal(message)
neighborhood = True if flags['n'] else False
if neighborhood:
if not gscript.find_program('r.neighborhoodmatrix', '--help'):
message = _(
"You need to install the addon r.neighborhoodmatrix to be able"
)
message += _(" to calculate area measures.\n")
message += _(
" You can install the addon with 'g.extension r.neighborhoodmatrix'"
)
gscript.fatal(message)
raster_statistics = options['raster_statistics'].split(
',') if options['raster_statistics'] else []
separator = gscript.separator(options['separator'])
processes = int(options['processes'])
output_header = ['cat']
output_dict = collections.defaultdict(list)
raster_stat_dict = {
'zone': 0,
'min': 4,
'third_quart': 16,
'max': 5,
'sum': 12,
'null_cells': 3,
'median': 15,
'label': 1,
'first_quart': 14,
'range': 6,
'mean_of_abs': 8,
'stddev': 9,
'non_null_cells': 2,
'coeff_var': 11,
'variance': 10,
'sum_abs': 13,
'perc_90': 17,
'mean': 7
}
geometry_stat_dict = {
'cat': 0,
'area': 1,
'perimeter': 2,
'compact_square': 3,
'compact_circle': 4,
'fd': 5,
'xcoords': 6,
'ycoords': 7
}
if flags['r']:
gscript.use_temp_region()
gscript.run_command('g.region', raster=segment_map)
stats_temp_file = gscript.tempfile()
if area_measures:
gscript.message(_("Calculating geometry statistics..."))
output_header += area_measures
stat_indices = [geometry_stat_dict[x] for x in area_measures]
gscript.run_command('r.object.geometry',
input_=segment_map,
output=stats_temp_file,
overwrite=True,
quiet=True)
firstline = True
with open(stats_temp_file, 'r') as fin:
for line in fin:
if firstline:
firstline = False
continue
values = line.rstrip().split('|')
output_dict[values[0]] = [values[x] for x in stat_indices]
if rasters:
if not flags['c']:
gscript.message(_("Checking usability of raster maps..."))
rasters_to_remove = []
for raster in rasters:
null_values_found = False
if not gscript.find_file(raster, element='cell')['name']:
gscript.message(_("Cannot find raster '%s'" % raster))
gscript.message(_("Removing this raster from list."))
rasters_to_remove.append(raster)
continue
current_mapset = gscript.gisenv()['MAPSET']
if gscript.find_file('MASK',
element='cell',
mapset=current_mapset)['name']:
null_test = gscript.read_command('r.stats',
flags='N',
input_=['MASK', raster],
quiet=True).splitlines()
if '1 *' in null_test:
null_values_found = True
else:
raster_info = gscript.parse_command('r.univar',
flags='g',
map_=raster,
quiet=True)
if len(raster_info) == 0 or int(
raster_info['null_cells']) > 0:
null_values_found = True
if null_values_found:
message = 'Raster <%s> contains null values.\n' % raster
message += 'This can lead to errors in the calculations.\n'
message += 'Check region settings and raster extent.\n'
message += 'Possibly fill null values of raster.\n'
message += 'Removing this raster from list.'
gscript.warning(message)
rasters_to_remove.append(raster)
for raster in rasters_to_remove:
rasters.remove(raster)
if len(rasters) > 0:
gscript.message(
_("Calculating statistics for the following raster maps:"))
gscript.message(','.join(rasters))
if len(rasters) < processes:
processes = len(rasters)
gscript.message(
_("Only one process per raster. Reduced number of processes to %i."
% processes))
stat_indices = [raster_stat_dict[x] for x in raster_statistics]
pool = Pool(processes)
func = partial(worker, segment_map, stats_temp_file)
pool.map(func, rasters)
pool.close()
pool.join()
for raster in rasters:
rastername = raster.split('@')[0]
rastername = rastername.replace('.', '_')
temp_file = stats_temp_file + '.' + rastername
output_header += [
rastername + "_" + x for x in raster_statistics
]
firstline = True
with open(temp_file, 'r') as fin:
for line in fin:
if firstline:
firstline = False
continue
values = line.rstrip().split('|')
output_dict[values[0]] = output_dict[values[0]] + [
values[x] for x in stat_indices
]
# Calculating neighborhood statistics if requested
if neighborhood:
gscript.message(_("Calculating neighborhood statistics..."))
# Add neighbordhood statistics to headers
original_nb_values = len(output_header) - 1
new_headers = ['neighbors_count']
for i in range(1, len(output_header)):
new_headers.append('%s_nbrmean' % output_header[i])
new_headers.append('%s_nbrstddev' % output_header[i])
output_header += new_headers
# Get sorted neighborhood matrix
nbr_matrix = sorted([
x.split('|')
for x in gscript.read_command('r.neighborhoodmatrix',
input_=segment_map,
flags='d',
quiet=True).splitlines()
])
# Calculate mean and stddev of neighbor values for each variable in the
# output_dict
for key, group in groupby(nbr_matrix, lambda x: x[0]):
d = {}
for i in range(original_nb_values):
d[i] = (0, 0, 0)
nbrlist = [str(x[1]) for x in group]
if len(nbrlist) > 1:
for nbr in nbrlist:
for i in range(original_nb_values):
d[i] = update(d[i], float(output_dict[nbr][i]))
output_dict[key] = output_dict[key] + [str(len(nbrlist))]
output_dict[key] = output_dict[key] + [
str(i) for sub in [finalize(x) for x in d.values()]
for i in sub
]
else:
newvalues = ['1']
nbr = nbrlist[0]
for i in range(original_nb_values):
newvalues.append(output_dict[nbr][i])
newvalues.append('0')
output_dict[key] = output_dict[key] + newvalues
message = _("Some values could not be calculated for the objects below. ")
message += _("These objects are thus not included in the results. ")
message += _("HINT: Check some of the raster maps for null values ")
message += _("and possibly fill these values with r.fillnulls.")
error_objects = []
if csvfile:
with open(csvfile, 'w') as f:
f.write(separator.join(output_header) + "\n")
for key in output_dict:
if len(output_dict[key]) + 1 == len(output_header):
f.write(key + separator +
separator.join(output_dict[key]) + "\n")
else:
error_objects.append(key)
f.close()
if vectormap:
gscript.message(_("Creating output vector map..."))
temporary_vect = 'segmstat_tmp_vect_%d' % os.getpid()
gscript.run_command('r.to.vect',
input_=segment_map,
output=temporary_vect,
type_='area',
flags='vt',
overwrite=True,
quiet=True)
insert_sql = gscript.tempfile()
fsql = open(insert_sql, 'w')
fsql.write('BEGIN TRANSACTION;\n')
if gscript.db_table_exist(temporary_vect):
if gscript.overwrite():
fsql.write('DROP TABLE %s;' % temporary_vect)
else:
gscript.fatal(
_("Table %s already exists. Use --o to overwrite" %
temporary_vect))
create_statement = 'CREATE TABLE ' + temporary_vect + ' (cat int PRIMARY KEY);\n'
fsql.write(create_statement)
for header in output_header[1:]:
addcol_statement = 'ALTER TABLE %s ADD COLUMN %s double precision;\n' % (
temporary_vect, header)
fsql.write(addcol_statement)
for key in output_dict:
if len(output_dict[key]) + 1 == len(output_header):
sql = "INSERT INTO %s VALUES (%s, %s);\n" % (
temporary_vect, key, ",".join(output_dict[key]))
sql = sql.replace('inf', 'NULL')
sql = sql.replace('nan', 'NULL')
fsql.write(sql)
else:
if not csvfile:
error_objects.append(key)
fsql.write('END TRANSACTION;')
fsql.close()
gscript.run_command('db.execute', input=insert_sql, quiet=True)
gscript.run_command('v.db.connect',
map_=temporary_vect,
table=temporary_vect,
quiet=True)
gscript.run_command('g.copy',
vector="%s,%s" % (temporary_vect, vectormap),
quiet=True)
if error_objects:
object_string = ', '.join(error_objects[:100])
message += _(
"\n\nObjects with errors (only first 100 are shown):\n%s" %
object_string)
gscript.message(message)
def main():
global insert_sql
insert_sql = None
global temporary_vect
temporary_vect = None
global stats_temp_file
stats_temp_file = None
segment_map = options["map"]
csvfile = options["csvfile"] if options["csvfile"] else []
vectormap = options["vectormap"] if options["vectormap"] else []
global rasters
rasters = options["rasters"].split(",") if options["rasters"] else []
area_measures = (
options["area_measures"].split(",")
if (options["area_measures"] and not flags["s"])
else []
)
neighborhood = True if flags["n"] else False
if neighborhood:
if not gscript.find_program("r.neighborhoodmatrix", "--help"):
message = _("You need to install the addon r.neighborhoodmatrix to be able")
message += _(" to calculate area measures.\n")
message += _(
" You can install the addon with 'g.extension r.neighborhoodmatrix'"
)
gscript.fatal(message)
raster_statistics = (
options["raster_statistics"].split(",") if options["raster_statistics"] else []
)
separator = gscript.separator(options["separator"])
processes = int(options["processes"])
output_header = ["cat"]
output_dict = collections.defaultdict(list)
raster_stat_dict = {
"zone": 0,
"min": 4,
"third_quart": 16,
"max": 5,
"sum": 12,
"null_cells": 3,
"median": 15,
"label": 1,
"first_quart": 14,
"range": 6,
"mean_of_abs": 8,
"stddev": 9,
"non_null_cells": 2,
"coeff_var": 11,
"variance": 10,
"sum_abs": 13,
"perc_90": 17,
"mean": 7,
}
geometry_stat_dict = {
"cat": 0,
"area": 1,
"perimeter": 2,
"compact_square": 3,
"compact_circle": 4,
"fd": 5,
"xcoords": 6,
"ycoords": 7,
}
if flags["r"]:
gscript.use_temp_region()
gscript.run_command("g.region", raster=segment_map)
stats_temp_file = gscript.tempfile()
if area_measures:
gscript.message(_("Calculating geometry statistics..."))
output_header += area_measures
stat_indices = [geometry_stat_dict[x] for x in area_measures]
gscript.run_command(
"r.object.geometry",
input_=segment_map,
output=stats_temp_file,
overwrite=True,
quiet=True,
)
firstline = True
with open(stats_temp_file, "r") as fin:
for line in fin:
if firstline:
firstline = False
continue
values = line.rstrip().split("|")
output_dict[values[0]] = [values[x] for x in stat_indices]
if rasters:
if not flags["c"]:
gscript.message(_("Checking usability of raster maps..."))
rasters_to_remove = []
for raster in rasters:
null_values_found = False
if not gscript.find_file(raster, element="cell")["name"]:
gscript.message(_("Cannot find raster '%s'" % raster))
gscript.message(_("Removing this raster from list."))
rasters_to_remove.append(raster)
continue
current_mapset = gscript.gisenv()["MAPSET"]
if gscript.find_file("MASK", element="cell", mapset=current_mapset)[
"name"
]:
null_test = gscript.read_command(
"r.stats", flags="N", input_=["MASK", raster], quiet=True
).splitlines()
if "1 *" in null_test:
null_values_found = True
else:
raster_info = gscript.parse_command(
"r.univar", flags="g", map_=raster, quiet=True
)
if len(raster_info) == 0 or int(raster_info["null_cells"]) > 0:
null_values_found = True
if null_values_found:
message = "Raster <%s> contains null values.\n" % raster
message += "This can lead to errors in the calculations.\n"
message += "Check region settings and raster extent.\n"
message += "Possibly fill null values of raster.\n"
message += "Removing this raster from list."
gscript.warning(message)
rasters_to_remove.append(raster)
for raster in rasters_to_remove:
rasters.remove(raster)
if len(rasters) > 0:
gscript.message(_("Calculating statistics for the following raster maps:"))
gscript.message(",".join(rasters))
if len(rasters) < processes:
processes = len(rasters)
gscript.message(
_(
"Only one process per raster. Reduced number of processes to %i."
% processes
)
)
stat_indices = [raster_stat_dict[x] for x in raster_statistics]
pool = Pool(processes)
func = partial(worker, segment_map, stats_temp_file)
pool.map(func, rasters)
pool.close()
pool.join()
for raster in rasters:
rastername = raster.split("@")[0]
rastername = rastername.replace(".", "_")
temp_file = stats_temp_file + "." + rastername
output_header += [rastername + "_" + x for x in raster_statistics]
firstline = True
with open(temp_file, "r") as fin:
for line in fin:
if firstline:
firstline = False
continue
values = line.rstrip().split("|")
output_dict[values[0]] = output_dict[values[0]] + [
values[x] for x in stat_indices
]
# Calculating neighborhood statistics if requested
if neighborhood:
gscript.message(_("Calculating neighborhood statistics..."))
# Add neighbordhood statistics to headers
original_nb_values = len(output_header) - 1
new_headers = ["neighbors_count"]
for i in range(1, len(output_header)):
new_headers.append("%s_nbrmean" % output_header[i])
new_headers.append("%s_nbrstddev" % output_header[i])
output_header += new_headers
# Get sorted neighborhood matrix
nbr_matrix = sorted(
[
x.split("|")
for x in gscript.read_command(
"r.neighborhoodmatrix", input_=segment_map, flags="d", quiet=True
).splitlines()
]
)
# Calculate mean and stddev of neighbor values for each variable in the
# output_dict
for key, group in groupby(nbr_matrix, lambda x: x[0]):
d = {}
for i in range(original_nb_values):
d[i] = (0, 0, 0)
nbrlist = [str(x[1]) for x in group]
if len(nbrlist) > 1:
for nbr in nbrlist:
for i in range(original_nb_values):
d[i] = update(d[i], float(output_dict[nbr][i]))
output_dict[key] = output_dict[key] + [str(len(nbrlist))]
output_dict[key] = output_dict[key] + [
str(i) for sub in [finalize(x) for x in d.values()] for i in sub
]
else:
newvalues = ["1"]
nbr = nbrlist[0]
for i in range(original_nb_values):
newvalues.append(output_dict[nbr][i])
newvalues.append("0")
output_dict[key] = output_dict[key] + newvalues
message = _("Some values could not be calculated for the objects below. ")
message += _("These objects are thus not included in the results. ")
message += _("HINT: Check some of the raster maps for null values ")
message += _("and possibly fill these values with r.fillnulls.")
error_objects = []
if csvfile:
with open(csvfile, "w") as f:
f.write(separator.join(output_header) + "\n")
for key in output_dict:
if len(output_dict[key]) + 1 == len(output_header):
f.write(key + separator + separator.join(output_dict[key]) + "\n")
else:
error_objects.append(key)
f.close()
if vectormap:
gscript.message(_("Creating output vector map..."))
temporary_vect = "segmstat_tmp_vect_%d" % os.getpid()
gscript.run_command(
"r.to.vect",
input_=segment_map,
output=temporary_vect,
type_="area",
flags="vt",
overwrite=True,
quiet=True,
)
insert_sql = gscript.tempfile()
fsql = open(insert_sql, "w")
fsql.write("BEGIN TRANSACTION;\n")
if gscript.db_table_exist(temporary_vect):
if gscript.overwrite():
fsql.write("DROP TABLE %s;" % temporary_vect)
else:
gscript.fatal(
_("Table %s already exists. Use --o to overwrite" % temporary_vect)
)
create_statement = (
"CREATE TABLE " + temporary_vect + " (cat int PRIMARY KEY);\n"
)
fsql.write(create_statement)
for header in output_header[1:]:
addcol_statement = "ALTER TABLE %s ADD COLUMN %s double precision;\n" % (
temporary_vect,
header,
)
fsql.write(addcol_statement)
for key in output_dict:
if len(output_dict[key]) + 1 == len(output_header):
sql = "INSERT INTO %s VALUES (%s, %s);\n" % (
temporary_vect,
key,
",".join(output_dict[key]),
)
sql = sql.replace("inf", "NULL")
sql = sql.replace("nan", "NULL")
fsql.write(sql)
else:
if not csvfile:
error_objects.append(key)
fsql.write("END TRANSACTION;")
fsql.close()
gscript.run_command("db.execute", input=insert_sql, quiet=True)
gscript.run_command(
"v.db.connect", map_=temporary_vect, table=temporary_vect, quiet=True
)
gscript.run_command(
"g.copy", vector="%s,%s" % (temporary_vect, vectormap), quiet=True
)
if error_objects:
object_string = ", ".join(error_objects[:100])
message += _(
"\n\nObjects with errors (only first 100 are shown):\n%s" % object_string
)
gscript.message(message)
def main():
global insert_sql
insert_sql = None
global temporary_vect
temporary_vect = None
global stats_temp_file
stats_temp_file = None
global content
content = None
global raster
raster = options["raster"]
global decimals
decimals = int(options["decimals"])
global zone_map
zone_map = options["zone_map"]
csvfile = options["csvfile"] if options["csvfile"] else []
separator = gscript.separator(options["separator"])
prefix = options["prefix"] if options["prefix"] else []
classes_list = options["classes_list"].split(
",") if options["classes_list"] else []
vectormap = options["vectormap"] if options["vectormap"] else []
prop = False if "proportion" not in options["statistics"].split(
",") else True
mode = False if "mode" not in options["statistics"].split(",") else True
if flags[
"c"]: # Check only if flag activated - Can be bottleneck in case of very large raster.
# Check if input layer is CELL
if gscript.parse_command("r.info", flags="g",
map=raster)["datatype"] != "CELL":
gscript.fatal(
_("The type of the input map 'raster' is not CELL. Please use raster with integer values"
))
if (gscript.parse_command("r.info", flags="g",
map=zone_map)["datatype"] != "CELL"):
gscript.fatal(
_("The type of the input map 'zone_map' is not CELL. Please use raster with integer values"
))
# Check if 'decimals' is + and with credible value
if decimals <= 0:
gscript.fatal(_("The number of decimals should be positive"))
if decimals > 100:
gscript.fatal(_("The number of decimals should not be more than 100"))
# Adjust region to input map is flag active
if flags["r"]:
gscript.use_temp_region()
gscript.run_command("g.region", raster=zone_map)
# R.STATS
tmpfile = gscript.tempfile()
try:
if flags["n"]:
gscript.run_command(
"r.stats",
overwrite=True,
flags="c",
input="%s,%s" % (zone_map, raster),
output=tmpfile,
separator=separator,
) # Consider null values in R.STATS
else:
gscript.run_command(
"r.stats",
overwrite=True,
flags="cn",
input="%s,%s" % (zone_map, raster),
output=tmpfile,
separator=separator,
) # Do not consider null values in R.STATS
gscript.message(_("r.stats command finished..."))
except:
gscript.fatal(_("The execution of r.stats failed"))
# COMPUTE STATISTICS
# Open csv file and create a csv reader
rstatsfile = open(tmpfile, "r")
reader = csv.reader(rstatsfile, delimiter=separator)
# Total pixels per category per zone
totals_dict = {}
for row in reader:
if (
row[0] not in totals_dict
): # Will pass the condition only if the current zone ID does not exists yet in the dictionary
totals_dict[row[0]] = {
} # Declare a new embedded dictionnary for the current zone ID
if (
flags["l"] and row[1] in classes_list
): # Will pass only if flag -l is active and if the current class is in the 'classes_list'
totals_dict[row[0]][row[1]] = int(row[2])
else:
totals_dict[row[0]][row[1]] = int(row[2])
# Delete key '*' in 'totals_dict' that could append if there are null values on the zone raster
if "*" in totals_dict:
del totals_dict["*"]
# Close file
rstatsfile.close()
# Get list of ID
id_list = [ID for ID in totals_dict]
# Mode
if mode:
modalclass_dict = {}
for ID in id_list:
# The trick was found here : https://stackoverflow.com/a/268285/8013239
mode = max(iter(totals_dict[ID].items()),
key=operator.itemgetter(1))[0]
if mode == "*": # If the mode is NULL values
modalclass_dict[ID] = "NULL"
else:
modalclass_dict[ID] = mode
# Class proportions
if prop:
# Get list of categories to output
if classes_list: # If list of classes provided by user
class_dict = {str(int(a)): ""
for a in classes_list
} # To be sure it's string format
else:
class_dict = {}
# Proportion of each category per zone
proportion_dict = {}
for ID in id_list:
proportion_dict[ID] = {}
for cl in totals_dict[ID]:
if (
flags["l"] and cl not in classes_list
): # with flag -l, output will contain only classes from 'classes_list'
continue
if flags["p"]:
prop_value = (float(totals_dict[ID][cl]) /
sum(totals_dict[ID].values()) * 100)
else:
prop_value = float(totals_dict[ID][cl]) / sum(
totals_dict[ID].values())
proportion_dict[ID][cl] = "{:.{}f}".format(
prop_value, decimals)
if cl == "*":
class_dict["NULL"] = ""
else:
class_dict[cl] = ""
# Fill class not met in the raster with zero
for ID in proportion_dict:
for cl in class_dict:
if cl not in proportion_dict[ID].keys():
proportion_dict[ID][cl] = "{:.{}f}".format(0, decimals)
# Get list of class sorted by value (arithmetic ordering)
if "NULL" in class_dict.keys():
class_list = sorted(
[int(k) for k in class_dict.keys() if k != "NULL"])
class_list.append("NULL")
else:
class_list = sorted([int(k) for k in class_dict.keys()])
gscript.verbose(_("Statistics computed..."))
# Set 'totals_dict' to None to try RAM release
totals_dict = None
# OUTPUT CONTENT
# Header
header = [
"cat",
]
if mode:
if prefix:
header.append("%s_mode" % prefix)
else:
header.append("mode")
if prop:
if prefix:
[header.append("%s_prop_%s" % (prefix, cl)) for cl in class_list]
else:
[header.append("prop_%s" % cl) for cl in class_list]
# Values
value_dict = {}
for ID in id_list:
value_dict[ID] = []
value_dict[ID].append(ID)
if mode:
value_dict[ID].append(modalclass_dict[ID])
if prop:
for cl in class_list:
value_dict[ID].append(proportion_dict[ID]["%s" % cl])
# WRITE OUTPUT
if csvfile:
with open(csvfile, "w", newline="") as outfile:
writer = csv.writer(outfile, delimiter=separator)
writer.writerow(header)
writer.writerows(value_dict.values())
if vectormap:
gscript.message(_("Creating output vector map..."))
temporary_vect = "rzonalclasses_tmp_vect_%d" % os.getpid()
gscript.run_command(
"r.to.vect",
input_=zone_map,
output=temporary_vect,
type_="area",
flags="vt",
overwrite=True,
quiet=True,
)
insert_sql = gscript.tempfile()
with open(insert_sql, "w", newline="") as fsql:
fsql.write("BEGIN TRANSACTION;\n")
if gscript.db_table_exist(temporary_vect):
if gscript.overwrite():
fsql.write("DROP TABLE %s;" % temporary_vect)
else:
gscript.fatal(
_("Table %s already exists. Use --o to overwrite") %
temporary_vect)
create_statement = ("CREATE TABLE %s (cat int PRIMARY KEY);\n" %
temporary_vect)
fsql.write(create_statement)
for col in header[1:]:
if col.split(
"_")[-1] == "mode": # Mode column should be integer
addcol_statement = "ALTER TABLE %s ADD COLUMN %s integer;\n" % (
temporary_vect,
col,
)
else: # Proportions column should be double precision
addcol_statement = (
"ALTER TABLE %s ADD COLUMN %s double precision;\n" %
(temporary_vect, col))
fsql.write(addcol_statement)
for key in value_dict:
insert_statement = "INSERT INTO %s VALUES (%s);\n" % (
temporary_vect,
",".join(value_dict[key]),
)
fsql.write(insert_statement)
fsql.write("END TRANSACTION;")
gscript.run_command("db.execute", input=insert_sql, quiet=True)
gscript.run_command("v.db.connect",
map_=temporary_vect,
table=temporary_vect,
quiet=True)
gscript.run_command("g.copy",
vector="%s,%s" % (temporary_vect, vectormap),
quiet=True)
