def test_assert_is_non_negative_numpy_array_non_negative_with_nan_allowed(
self):
"""Checks assert_is_geq_numpy_array; base_value = 0, inputs >= 0.
In this case, input array contains NaN's and allow_nan = True.
"""
error_checking.assert_is_geq_numpy_array(
NON_NEGATIVE_NUMPY_ARRAY_WITH_NANS, 0, allow_nan=True)
def test_assert_is_non_negative_numpy_array_positive_with_nan_banned(self):
"""Checks assert_is_geq_numpy_array; base_value = 0, inputs > 0.
In this case, input array contains NaN's and allow_nan = False.
"""
with self.assertRaises(ValueError):
error_checking.assert_is_geq_numpy_array(
POSITIVE_NUMPY_ARRAY_WITH_NANS, 0, allow_nan=False)
def _polygons_to_mask_one_panel(polygon_objects_grid_coords, num_grid_rows,
num_grid_columns):
"""Converts list of polygons to binary mask.
M = number of rows in grid
N = number of columns in grid
:param polygon_objects_grid_coords: See doc for
`polygons_from_pixel_to_grid_coords`.
:param num_grid_rows: Same.
:param num_grid_columns: Same.
:return: mask_matrix: M-by-N numpy array of Boolean flags. If
mask_matrix[i, j] == True, grid point [i, j] is in/on at least one of
the polygons.
"""
mask_matrix = numpy.full((num_grid_rows, num_grid_columns),
False,
dtype=bool)
num_polygons = len(polygon_objects_grid_coords)
if num_polygons == 0:
return mask_matrix
# TODO(thunderhoser): This triple for-loop is probably inefficient.
for k in range(num_polygons):
these_grid_columns = numpy.array(
polygon_objects_grid_coords[k].exterior.xy[0])
error_checking.assert_is_geq_numpy_array(these_grid_columns, -0.5)
error_checking.assert_is_leq_numpy_array(these_grid_columns,
num_grid_columns - 0.5)
these_grid_rows = numpy.array(
polygon_objects_grid_coords[k].exterior.xy[1])
error_checking.assert_is_geq_numpy_array(these_grid_rows, -0.5)
error_checking.assert_is_leq_numpy_array(these_grid_rows,
num_grid_rows - 0.5)
for i in range(num_grid_rows):
for j in range(num_grid_columns):
if mask_matrix[i, j]:
continue
mask_matrix[i, j] = polygons.point_in_or_on_polygon(
polygon_object=polygon_objects_grid_coords[k],
query_x_coordinate=j,
query_y_coordinate=i)
return mask_matrix
def _check_polygons(polygon_objects_grid_coords, num_panel_rows,
num_panel_columns, panel_row_by_polygon,
panel_column_by_polygon):
"""Error-checks list of polygons.
:param polygon_objects_grid_coords: See doc for
`polygons_from_pixel_to_grid_coords`.
:param num_panel_rows: Same.
:param num_panel_columns: Same.
:param panel_row_by_polygon: Same.
:param panel_column_by_polygon: Same.
"""
error_checking.assert_is_integer(num_panel_rows)
error_checking.assert_is_greater(num_panel_rows, 0)
error_checking.assert_is_integer(num_panel_columns)
error_checking.assert_is_greater(num_panel_columns, 0)
num_polygons = len(polygon_objects_grid_coords)
if num_polygons == 0:
return
error_checking.assert_is_numpy_array(numpy.array(
polygon_objects_grid_coords, dtype=object),
num_dimensions=1)
these_expected_dim = numpy.array([num_polygons], dtype=int)
error_checking.assert_is_integer_numpy_array(panel_row_by_polygon)
error_checking.assert_is_numpy_array(panel_row_by_polygon,
exact_dimensions=these_expected_dim)
error_checking.assert_is_geq_numpy_array(panel_row_by_polygon, 0)
error_checking.assert_is_less_than_numpy_array(panel_row_by_polygon,
num_panel_rows)
error_checking.assert_is_integer_numpy_array(panel_column_by_polygon)
error_checking.assert_is_numpy_array(panel_column_by_polygon,
exact_dimensions=these_expected_dim)
error_checking.assert_is_geq_numpy_array(panel_column_by_polygon, 0)
error_checking.assert_is_less_than_numpy_array(panel_column_by_polygon,
num_panel_columns)
def write_points(output_file_name,
grid_row_by_point,
grid_column_by_point,
panel_row_by_point,
panel_column_by_point,
full_storm_id_string=None,
storm_time_unix_sec=None):
"""Writes human points of interest for one image to NetCDF file.
K = number of points of interest
:param output_file_name: Path to output (NetCDF) file.
:param grid_row_by_point: length-K numpy array of row indices in data grid
(floats).
:param grid_column_by_point: length-K numpy array of column indices in data
grid (floats).
:param panel_row_by_point: length-K numpy array of row indices in panel grid
(integers).
:param panel_column_by_point: length-K numpy array of column indices in
panel grid (integers).
:param full_storm_id_string: See doc for `write_polygons`.
:param storm_time_unix_sec: Same.
"""
is_composite = (full_storm_id_string is None
and storm_time_unix_sec is None)
if is_composite:
full_storm_id_string = DUMMY_STORM_ID_STRING
storm_time_unix_sec = -1
error_checking.assert_is_string(full_storm_id_string)
error_checking.assert_is_integer(storm_time_unix_sec)
# error_checking.assert_is_integer(num_grid_rows)
# error_checking.assert_is_greater(num_grid_rows, 0)
# error_checking.assert_is_integer(num_grid_columns)
# error_checking.assert_is_greater(num_grid_columns, 0)
error_checking.assert_is_numpy_array(grid_row_by_point, num_dimensions=1)
error_checking.assert_is_geq_numpy_array(grid_row_by_point, -0.5)
# error_checking.assert_is_leq_numpy_array(
# grid_row_by_point, num_grid_rows - 0.5)
num_points = len(grid_row_by_point)
these_expected_dim = numpy.array([num_points], dtype=int)
error_checking.assert_is_numpy_array(grid_column_by_point,
exact_dimensions=these_expected_dim)
error_checking.assert_is_geq_numpy_array(grid_column_by_point, -0.5)
# error_checking.assert_is_leq_numpy_array(
# grid_column_by_point, num_grid_columns - 0.5)
error_checking.assert_is_numpy_array(panel_row_by_point,
exact_dimensions=these_expected_dim)
error_checking.assert_is_integer_numpy_array(panel_row_by_point)
error_checking.assert_is_geq_numpy_array(panel_row_by_point, 0)
error_checking.assert_is_numpy_array(panel_column_by_point,
exact_dimensions=these_expected_dim)
error_checking.assert_is_integer_numpy_array(panel_column_by_point)
error_checking.assert_is_geq_numpy_array(panel_column_by_point, 0)
file_system_utils.mkdir_recursive_if_necessary(file_name=output_file_name)
dataset_object = netCDF4.Dataset(output_file_name,
'w',
format='NETCDF3_64BIT_OFFSET')
dataset_object.setncattr(STORM_ID_KEY, full_storm_id_string)
dataset_object.setncattr(STORM_TIME_KEY, storm_time_unix_sec)
dataset_object.createDimension(POINT_DIMENSION_KEY, num_points)
dataset_object.createVariable(GRID_ROW_BY_POINT_KEY,
datatype=numpy.float32,
dimensions=POINT_DIMENSION_KEY)
dataset_object.variables[GRID_ROW_BY_POINT_KEY][:] = grid_row_by_point
dataset_object.createVariable(GRID_COLUMN_BY_POINT_KEY,
datatype=numpy.float32,
dimensions=POINT_DIMENSION_KEY)
dataset_object.variables[
GRID_COLUMN_BY_POINT_KEY][:] = grid_column_by_point
dataset_object.createVariable(PANEL_ROW_BY_POINT_KEY,
datatype=numpy.int32,
dimensions=POINT_DIMENSION_KEY)
dataset_object.variables[PANEL_ROW_BY_POINT_KEY][:] = panel_row_by_point
dataset_object.createVariable(PANEL_COLUMN_BY_POINT_KEY,
datatype=numpy.int32,
dimensions=POINT_DIMENSION_KEY)
dataset_object.variables[
PANEL_COLUMN_BY_POINT_KEY][:] = panel_column_by_point
dataset_object.close()
def pixel_columns_to_grid_columns(pixel_column_by_vertex, num_pixel_columns,
num_panel_columns, num_grid_columns,
assert_same_panel):
"""Converts pixel columns to grid columns.
V = number of vertices in object
:param pixel_column_by_vertex: length-V numpy array with column coordinates
of vertices in pixel space.
:param num_pixel_columns: Total number of pixel columns in image.
:param num_panel_columns: Total number of panel columns in image.
:param num_grid_columns: Total number of columns in grid (one grid per
panel).
:param assert_same_panel: Boolean flag. If True, all vertices must be in
the same panel.
:return: grid_column_by_vertex: length-V numpy array with column coordinates
(floats) of vertices in grid space.
:return: panel_column_by_vertex: length-V numpy array with column
coordinates (integers) of vertices in panel space.
"""
error_checking.assert_is_integer(num_pixel_columns)
error_checking.assert_is_greater(num_pixel_columns, 0)
error_checking.assert_is_integer(num_panel_columns)
error_checking.assert_is_greater(num_panel_columns, 0)
error_checking.assert_is_integer(num_grid_columns)
error_checking.assert_is_greater(num_grid_columns, 0)
error_checking.assert_is_boolean(assert_same_panel)
error_checking.assert_is_numpy_array(pixel_column_by_vertex,
num_dimensions=1)
pixel_column_by_vertex += 0.5
error_checking.assert_is_geq_numpy_array(pixel_column_by_vertex, 0.)
error_checking.assert_is_leq_numpy_array(pixel_column_by_vertex,
num_pixel_columns)
panel_column_to_first_px_column = {}
for j in range(num_panel_columns):
panel_column_to_first_px_column[j] = (j * float(num_pixel_columns) /
num_panel_columns)
panel_column_by_vertex = numpy.floor(pixel_column_by_vertex *
float(num_panel_columns) /
num_pixel_columns).astype(int)
panel_column_by_vertex[panel_column_by_vertex ==
num_panel_columns] = num_panel_columns - 1
if assert_same_panel and len(numpy.unique(panel_column_by_vertex)) > 1:
error_string = (
'Object is in multiple panels. Panel columns listed below.\n{0:s}'
).format(str(panel_column_by_vertex))
raise ValueError(error_string)
num_vertices = len(pixel_column_by_vertex)
for i in range(num_vertices):
pixel_column_by_vertex[i] = (
pixel_column_by_vertex[i] -
panel_column_to_first_px_column[panel_column_by_vertex[i]])
grid_column_by_vertex = -0.5 + (pixel_column_by_vertex * float(
num_grid_columns * num_panel_columns) / num_pixel_columns)
return grid_column_by_vertex, panel_column_by_vertex
def test_assert_is_non_negative_numpy_array_mixed_sign(self):
"""assert_is_geq_numpy_array; base_value = 0, inputs mixed sign."""
with self.assertRaises(ValueError):
error_checking.assert_is_geq_numpy_array(MIXED_SIGN_NUMPY_ARRAY, 0)
def test_assert_is_non_negative_numpy_array_non_positive(self):
"""Checks assert_is_geq_numpy_array; base_value = 0, inputs <= 0."""
with self.assertRaises(ValueError):
error_checking.assert_is_geq_numpy_array(NON_POSITIVE_NUMPY_ARRAY,
0)
def test_assert_is_non_negative_numpy_array_positive(self):
"""Checks assert_is_geq_numpy_array; base_value = 0, inputs > 0."""
error_checking.assert_is_geq_numpy_array(POSITIVE_NUMPY_ARRAY, 0)
