def clip_value(in_file, ot_dir, min_height, max_height):
"""
オンライン学習４ ベクタデータのフィルタリング
浸水・土砂崩れベクタデータをGISデータの属性値(値)を使用してフィルタリングするプログラムを実行します。
関数 : clip_value
引数1 : 浸水・土砂崩れベクタデータ(*.shp)
引数2 : 出力ディレクトリ名
引数3 : 出力対象となる値の最小値
引数4 : 出力対象となる値の最大値
"""
# Get actual file path
in_file = path.join(DATA_PATH_BASE, in_file)
ot_dir = path.join(DATA_PATH_BASE, ot_dir)
makedirs(ot_dir, exist_ok=True)
ot_file = path.join(
ot_dir, "{0}v.tif".format(path.splitext(path.basename(in_file))[0]))
reader = ShpReader(in_file, encoding='cp932')
writer = ShpWriter(ot_file, encoding='cp932')
# Create DBF schema
height_col_id = None
for i, col in enumerate(
(col for col in reader.fields if col[0] != "DeletionFlag")):
if col[0] != "DeletionFlag":
writer.field(col[0], col[1], col[2], col[3])
if col[0] == "height":
height_col_id = i
if height_col_id is None:
print("height column not found in polygon shapefile")
return
# Filtering
n_mesh = reader.numRecords
cnt_mesh = 0
for data in reader.iterShapeRecords():
height = data.record[height_col_id]
if (height is not None) and (min_height <= height <= max_height):
# This polygon is output target.
writer.shape(data.shape)
writer.record(*data.record)
cnt_mesh = cnt_mesh + 1
if cnt_mesh % 100000 == 0:
print("{0}K / {1}K".format(cnt_mesh / 1000, n_mesh / 1000))
writer.close()
def clip_shape(in_mesh, in_mask, ot_dir, flg_mask):
"""
オンライン学習４ ベクタデータのフィルタリング
浸水・土砂崩れベクタデータをGISデータの形状を利用してフィルタリングします。
関数 : clip_shape
引数1 : 浸水・土砂崩れベクタデータ(*.shp)
引数2 : GISデータ(*.shp)
引数3 : 出力ディレクトリ名
引数4 : 出力フラグ(True：GISデータと重なる部分を出力、False：GISデータと重ならない部分を出力)
"""
# Get actual file path
in_mesh = path.join(DATA_PATH_BASE, in_mesh)
in_mask = path.join(DATA_PATH_BASE, in_mask)
ot_dir = path.join(DATA_PATH_BASE, ot_dir)
makedirs(ot_dir, exist_ok=True)
ot_file = path.join(ot_dir, "{0}s.tif".format(path.splitext(path.basename(in_mesh))[0]))
reader_mesh = ShpReader(in_mesh, encoding='cp932')
reader_mask = ShpReader(in_mask, encoding='cp932')
writer = ShpWriter(ot_file, encoding='cp932')
# Create DBF schema
for col in reader_mesh.fields:
if col[0] != "DeletionFlag":
writer.field(col[0], col[1], col[2], col[3])
# Create set of mask polygon
maskdata = []
for data in reader_mask.iterShapes():
points = data.points
points_split = list(data.parts) + [len(points)]
poly_list = []
for i in range(len(points_split) - 1):
points_part = points[points_split[i]:points_split[i + 1]]
poly_list.append(Polygon(points_part))
# Use as mask polygon only when all key conditions are satisfied.
# Memorize shape and bbox of polygon.
x_range = min(points, key=lambda x: x[0])[0], max(points, key=lambda x: x[0])[0]
y_range = min(points, key=lambda x: x[1])[1], max(points, key=lambda x: x[1])[1]
maskdata.append((x_range, y_range, poly_list))
# Filtering
n_mesh = reader_mesh.numRecords
cnt_mesh = 0
for data in reader_mesh.iterShapeRecords():
center = Polygon(data.shape.points).centroid
x = center.x
y = center.y
masked = False
for x_range, y_range, mask_polys in maskdata:
# Primary screening by mask polygon bbox.
if x < x_range[0] or x > x_range[1] or y < y_range[0] or y > y_range[1]:
continue
mask_count = sum(poly.contains(center) for poly in mask_polys)
if mask_count % 2 == 1:
masked = True
break
if masked == flg_mask:
# This polygon is output target.
writer.shape(data.shape)
writer.record(*data.record)
cnt_mesh = cnt_mesh + 1
if cnt_mesh % 100000 == 0:
print("{0}K / {1}K".format(cnt_mesh/1000, n_mesh/1000))
writer.close()
def add_height_vector(in_polys, in_hpoint, dst_fn):
"""
オンライン学習3 被害領域の抽出、ラスタベクタ変換
メッシュデータに標高値を付与します。
関数 ： add_height_vector
引数1 ： 入力メッシュデータ名(.tif)
引数2 ： 数値標高ﾓﾃﾞﾙ名(.shp)
引数3 ： 出力ファイル名(.shp)
"""
# Read DEM data
print("loading DEM data ...")
dem = GridData()
dem_reader = ShpReader(in_hpoint, encoding='cp932')
n_p = dem_reader.numRecords
cnt_p = 0
for data in dem_reader.iterShapeRecords():
point = Point(data.shape.points[0])
p_val = data.record
dem.add_data(point.x, point.y, p_val)
cnt_p = cnt_p + 1
if cnt_p % 100000 == 0:
print("{0}K / {1}K".format(cnt_p/1000, n_p/1000))
print("loaded DEM data .")
print()
# Process each polygon shapefile
for in_poly in in_polys:
print("processing {0} ...".format(in_poly))
poly_reader = ShpReader(in_poly)
poly_writer = ShpWriter(target=dst_fn)
# Create DBF schema
for col in poly_reader.fields:
if col[0] != "DeletionFlag":
poly_writer.field(col[0], col[1], col[2], col[3])
poly_writer.field("height", "N", 18, 9)
# Attach elevation value
n_poly = poly_reader.numRecords
cnt_poly = 0
for data in poly_reader.iterShapeRecords():
center = Polygon(data.shape.points).centroid
key_x = dem.search_nearest_x(center.coords[0][0])
key_y = dem.search_nearest_y(center.coords[0][1])
dem_record = dem.get_data(key_x, key_y)
if dem_record:
# Nearest grid point has elevation value
record = data.record + dem_record
else:
# Nearest grid point doesn't have elevation value
record = data.record + [None]
poly_writer.shape(data.shape)
poly_writer.record(*record)
cnt_poly = cnt_poly + 1
if cnt_poly % 100000 == 0:
print("{0}K / {1}K".format(cnt_poly/1000, n_poly/1000))
poly_writer.close()
print("processed {0} .".format(in_poly))
print()
def _load_boundaries(filename, index, projections=None, encoding='utf-8'):
"""
Load boundaries from a shape file and perform a projection if desired.
Parameters
----------
filename : str
filename to load data from
index : int
index to extract the LSOA identifier from the metadata for each shape
projections : tuple
tuple of projections (from, to)
Returns
-------
boundaries : dict
dictionary of lists of polygons keyed by LSOA code
"""
boundaries = {}
# Extract projections
if projections is not None:
original_projection, target_projection = projections
target_projection = pyproj.Proj(init=target_projection)
original_projection = pyproj.Proj(init=original_projection)
transformer = pyproj.Transformer.from_proj(original_projection, target_projection)
else:
transformer = None
# Iterate over all records
shapefile = ShapefileReader(filename, encoding=encoding)
logging.info("opened shapefile '%s'", filename)
iterator = shapefile.iterShapeRecords()
with tqdm.tqdm(total=shapefile.numRecords) as progress:
while True:
try:
sr = next(iterator)
except IOError:
# the shapefile module has a bug and raises an error when reading, but the data are
# fine, and we ignore the error
break
except StopIteration:
break
# Get the identifier
code = sr.record[index]
# Transform the points if transformations are given
points = sr.shape.points
if projections:
points = np.transpose(transformer.transform(*np.transpose(points)))
# Build a set of polygons and their areas
polygons = []
for part in np.array_split(points, sr.shape.parts[1:]):
polygon = geometry.Polygon(part)
polygons.append((polygon.area, polygon))
# Transpose to get a tuple (areas, polygons)
boundaries[code] = list(zip(*polygons))
assert len(boundaries[code]) == 2, "expected 2 items for %s but got %d" % \
(code, len(boundaries[code]))
progress.update()
# Check we loaded the correct number of boundaries
assert len(boundaries) == shapefile.numRecords, "did not load the correct number of records"
logging.info('loaded %d boundaries from %s', len(boundaries), filename)
return boundaries
