Source code for safe.storage.utilities

"""**Utilities for storage module**
"""

import os
import re
import copy
import numpy
import math
from ast import literal_eval
from osgeo import ogr

from geometry import Polygon

from safe.common.numerics import ensure_numeric
from safe.common.utilities import verify
from safe.common.exceptions import BoundingBoxError, InaSAFEError


# Default attribute to assign to vector layers
DEFAULT_ATTRIBUTE = 'inapolygon'

# Spatial layer file extensions that are recognised in Risiko
# FIXME: Perhaps add '.gml', '.zip', ...
LAYER_TYPES = ['.shp', '.asc', '.tif', '.tiff', '.geotif', '.geotiff']

# Map between extensions and ORG drivers
DRIVER_MAP = {'.sqlite': 'SQLITE',
              '.shp': 'ESRI Shapefile',
              '.gml': 'GML',
              '.tif': 'GTiff',
              '.asc': 'AAIGrid'}

# Map between Python types and OGR field types
# FIXME (Ole): I can't find a double precision type for OGR
TYPE_MAP = {type(None): ogr.OFTString,  # What else should this be?
            type(''): ogr.OFTString,
            type(True): ogr.OFTInteger,
            type(0): ogr.OFTInteger,
            type(0.0): ogr.OFTReal,
            type(numpy.array([0.0])[0]): ogr.OFTReal,  # numpy.float64
            type(numpy.array([[0.0]])[0]): ogr.OFTReal}  # numpy.ndarray

# Map between verbose types and OGR geometry types
INVERSE_GEOMETRY_TYPE_MAP = {'point': ogr.wkbPoint,
                             'line': ogr.wkbLineString,
                             'polygon': ogr.wkbPolygon}


# Miscellaneous auxiliary functions
def _keywords_to_string(keywords, sublayer=None):
    """Create a string from a keywords dict.

    Args:
        * keywords: A required dictionary containing the keywords to stringify.
        * sublayer: str optional group marker for a sub layer.

    Returns:
        str: a String containing the rendered keywords list

    Raises:
        Any exceptions are propogated.

    .. note: Only simple keyword dicts should be passed here, not multilayer
       dicts.

    For example you pass a dict like this::

        {'datatype': 'osm',
         'category': 'exposure',
         'title': 'buildings_osm_4326',
         'subcategory': 'building',
         'purpose': 'dki'}

    and the following string would be returned:

        datatype: osm
        category: exposure
        title: buildings_osm_4326
        subcategory: building
        purpose: dki

    If sublayer is provided e.g. _keywords_to_string(keywords, sublayer='foo'),
    the following:

        [foo]
        datatype: osm
        category: exposure
        title: buildings_osm_4326
        subcategory: building
        purpose: dki
    """

    # Write
    result = ''
    if sublayer is not None:
        result = '[%s]\n' % sublayer
    for k, v in keywords.items():
        # Create key
        msg = ('Key in keywords dictionary must be a string. '
               'I got %s with type %s' % (k, str(type(k))[1:-1]))
        verify(isinstance(k, basestring), msg)

        key = k
        msg = ('Key in keywords dictionary must not contain the ":" '
               'character. I got "%s"' % key)
        verify(':' not in key, msg)

        # Create value
        msg = ('Value in keywords dictionary must be convertible to a string. '
               'For key %s, I got %s with type %s'
               % (k, v, str(type(v))[1:-1]))
        try:
            val = str(v)
        except:
            raise Exception(msg)

        # Store
        result += '%s: %s\n' % (key, val)
    return result


[docs]def write_keywords(keywords, filename, sublayer=None): """Write keywords dictonary to file Args: * keywords: Dictionary of keyword, value pairs * filename: Name of keywords file. Extension expected to be .keywords * sublayer: str Optional sublayer applicable only to multilayer formats such as sqlite or netcdf which can potentially hold more than one layer. The string should map to the layer group as per the example below. **If the keywords file contains sublayer definitions but no sublayer was defined, keywords file content will be removed and replaced with only the keywords provided here.** Returns: None Raises: None A keyword file with sublayers may look like this: [osm_buildings] datatype: osm category: exposure subcategory: building purpose: dki title: buildings_osm_4326 [osm_flood] datatype: flood category: hazard subcategory: building title: flood_osm_4326 Keys must be strings not containing the ":" character Values can be anything that can be converted to a string (using Python's str function) Surrounding whitespace is removed from values, but keys are unmodified The reason being that keys must always be valid for the dictionary they came from. For values we have decided to be flexible and treat entries like 'unit:m' the same as 'unit: m', or indeed 'unit: m '. Otherwise, unintentional whitespace in values would lead to surprising errors in the application. """ # Input checks basename, ext = os.path.splitext(filename) msg = ('Unknown extension for file %s. ' 'Expected %s.keywords' % (filename, basename)) verify(ext == '.keywords', msg) # First read any keywords out of the file so that we can retain # keywords for other sublayers existing_keywords = read_keywords(filename, all_blocks=True) first_value = None if len(existing_keywords) > 0: first_value = existing_keywords[existing_keywords.keys()[0]] multilayer_flag = type(first_value) == dict handle = file(filename, 'wt') if multilayer_flag: if sublayer is not None and sublayer != '': #replace existing keywords / add new for this layer existing_keywords[sublayer] = keywords for key, value in existing_keywords.iteritems(): handle.write(_keywords_to_string(value, sublayer=key)) handle.write('\n') else: # It is currently a multilayer but we will replace it with # a single keyword block since the user passed no sublayer handle.write(_keywords_to_string(keywords)) else: #currently a simple layer so replace it with our content handle.write(_keywords_to_string(keywords, sublayer=sublayer)) handle.close()
[docs]def read_keywords(filename, sublayer=None, all_blocks=False): """Read keywords dictionary from file Args: * filename: Name of keywords file. Extension expected to be .keywords The format of one line is expected to be either string: string or string * sublayer: str Optional sublayer applicable only to multilayer formats such as sqlite or netcdf which can potentially hold more than one layer. The string should map to the layer group as per the example below. If the keywords file contains sublayer definitions but no sublayer was defined, the first layer group will be returned. * all_blocks: bool Optional, defaults to False. If True will return a dict of dicts, where the top level dict entries each represent a sublayer, and the values of that dict will be dicts of keyword entries. Returns: keywords: Dictionary of keyword, value pairs Raises: None A keyword layer with sublayers may look like this: [osm_buildings] datatype: osm category: exposure subcategory: building purpose: dki title: buildings_osm_4326 [osm_flood] datatype: flood category: hazard subcategory: building title: flood_osm_4326 Wheras a simple keywords file would look like this datatype: flood category: hazard subcategory: building title: flood_osm_4326 If filename does not exist, an empty dictionary is returned Blank lines are ignored Surrounding whitespace is removed from values, but keys are unmodified If there are no ':', then the keyword is treated as a key with no value """ # Input checks basename, ext = os.path.splitext(filename) msg = ('Unknown extension for file %s. ' 'Expected %s.keywords' % (filename, basename)) verify(ext == '.keywords', msg) if not os.path.isfile(filename): return {} # Read all entries blocks = {} keywords = {} fid = open(filename, 'r') current_block = None first_keywords = None for line in fid.readlines(): # Remove trailing (but not preceeding!) whitespace # FIXME: Can be removed altogether text = line.rstrip() # Ignore blank lines if text == '': continue # Check if it is an ini style group header block_flag = re.search(r'^\[.*]$', text, re.M | re.I) if block_flag: # Write the old block if it exists - must have a current # block to prevent orphans if len(keywords) > 0 and current_block is not None: blocks[current_block] = keywords if first_keywords is None and len(keywords) > 0: first_keywords = keywords # Now set up for a new block current_block = text[1:-1] # Reset the keywords each time we encounter a new block # until we know we are on the desired one keywords = {} continue if ':' not in text: key = text.strip() val = None else: # Get splitting point idx = text.find(':') # Take key as everything up to the first ':' key = text[:idx] # Take value as everything after the first ':' textval = text[idx + 1:].strip() try: # Take care of python structures like # booleans, None, lists, dicts etc val = literal_eval(textval) except (ValueError, SyntaxError): val = textval # Add entry to dictionary keywords[key] = val fid.close() # Write our any unfinalised block data if len(keywords) > 0 and current_block is not None: blocks[current_block] = keywords if first_keywords is None: first_keywords = keywords # Ok we have generated a structure that looks like this: # blocks = {{ 'foo' : { 'a': 'b', 'c': 'd'}, # { 'bar' : { 'd': 'e', 'f': 'g'}} # where foo and bar are sublayers and their dicts are the sublayer keywords if all_blocks: return blocks if sublayer is not None: if sublayer in blocks: return blocks[sublayer] else: return first_keywords
[docs]def check_geotransform(geotransform): """Check that geotransform is valid Args * geotransform: GDAL geotransform (6-tuple). (top left x, w-e pixel resolution, rotation, top left y, rotation, n-s pixel resolution). See e.g. http://www.gdal.org/gdal_tutorial.html Note This assumes that the spatial reference uses geographic coordinaties, so will not work for projected coordinate systems. """ msg = ('Supplied geotransform must be a tuple with ' '6 numbers. I got %s' % str(geotransform)) verify(len(geotransform) == 6, msg) for x in geotransform: try: float(x) except TypeError: raise InaSAFEError(msg) # Check longitude msg = ('Element in 0 (first) geotransform must be a valid ' 'longitude. I got %s' % geotransform[0]) verify(-180 <= geotransform[0] <= 180, msg) # Check latitude msg = ('Element 3 (fourth) in geotransform must be a valid ' 'latitude. I got %s' % geotransform[3]) verify(-90 <= geotransform[3] <= 90, msg) # Check cell size msg = ('Element 1 (second) in geotransform must be a positive ' 'number. I got %s' % geotransform[1]) verify(geotransform[1] > 0, msg) msg = ('Element 5 (sixth) in geotransform must be a negative ' 'number. I got %s' % geotransform[1]) verify(geotransform[5] < 0, msg)
[docs]def geotransform2bbox(geotransform, columns, rows): """Convert geotransform to bounding box Args : * geotransform: GDAL geotransform (6-tuple). (top left x, w-e pixel resolution, rotation, top left y, rotation, n-s pixel resolution). See e.g. http://www.gdal.org/gdal_tutorial.html * columns: Number of columns in grid * rows: Number of rows in grid Returns: * bbox: Bounding box as a list of geographic coordinates [west, south, east, north] Note: Rows and columns are needed to determine eastern and northern bounds. FIXME: Not sure if the pixel vs gridline registration issue is observed correctly here. Need to check against gdal > v1.7 """ x_origin = geotransform[0] # top left x y_origin = geotransform[3] # top left y x_res = geotransform[1] # w-e pixel resolution y_res = geotransform[5] # n-s pixel resolution x_pix = columns y_pix = rows minx = x_origin maxx = x_origin + (x_pix * x_res) miny = y_origin + (y_pix * y_res) maxy = y_origin return [minx, miny, maxx, maxy]
[docs]def geotransform2resolution(geotransform, isotropic=False): """Convert geotransform to resolution Args: * geotransform: GDAL geotransform (6-tuple). (top left x, w-e pixel resolution, rotation, top left y, rotation, n-s pixel resolution). See e.g. http://www.gdal.org/gdal_tutorial.html * isotropic: If True, return the average (dx + dy) / 2 Returns: * resolution: grid spacing (resx, resy) in (positive) decimal degrees ordered as longitude first, then latitude. or (resx + resy) / 2 (if isotropic is True) """ resx = geotransform[1] # w-e pixel resolution resy = -geotransform[5] # n-s pixel resolution (always negative) if isotropic: return (resx + resy) / 2 else: return resx, resy
[docs]def raster_geometry2geotransform(longitudes, latitudes): """Convert vectors of longitudes and latitudes to geotransform Note: This is the inverse operation of Raster.get_geometry(). Args: * longitudes, latitudes: Vectors of geographic coordinates Returns: * geotransform: 6-tuple (top left x, w-e pixel resolution, rotation, top left y, rotation, n-s pixel resolution) """ nx = len(longitudes) ny = len(latitudes) msg = ('You must specify more than 1 longitude to make geotransform: ' 'I got %s' % str(longitudes)) verify(nx > 1, msg) msg = ('You must specify more than 1 latitude to make geotransform: ' 'I got %s' % str(latitudes)) verify(ny > 1, msg) dx = float(longitudes[1] - longitudes[0]) # Longitudinal resolution dy = float(latitudes[0] - latitudes[1]) # Latitudinal resolution (neg) # Define pixel centers along each directions # This is to achieve pixel registration rather # than gridline registration dx2 = dx / 2 dy2 = dy / 2 geotransform = (longitudes[0] - dx2, # Longitude of upper left corner dx, # w-e pixel resolution 0, # rotation latitudes[-1] - dy2, # Latitude of upper left corner 0, # rotation dy) # n-s pixel resolution return geotransform
[docs]def bbox_intersection(*args): """Compute intersection between two or more bounding boxes Args: * args: two or more bounding boxes. Each is assumed to be a list or a tuple with four coordinates (W, S, E, N) Returns: * result: The minimal common bounding box """ msg = 'Function bbox_intersection must take at least 2 arguments.' verify(len(args) > 1, msg) result = [-180, -90, 180, 90] for a in args: if a is None: continue msg = ('Bounding box expected to be a list of the ' 'form [W, S, E, N]. ' 'Instead i got "%s"' % str(a)) try: box = list(a) except: raise Exception(msg) if not len(box) == 4: raise BoundingBoxError(msg) msg = ('Western boundary must be less than or equal to eastern. ' 'I got %s' % box) if not box[0] <= box[2]: raise BoundingBoxError(msg) msg = ('Southern boundary must be less than or equal to northern. ' 'I got %s' % box) if not box[1] <= box[3]: raise BoundingBoxError(msg) # Compute intersection # West and South for i in [0, 1]: result[i] = max(result[i], box[i]) # East and North for i in [2, 3]: result[i] = min(result[i], box[i]) # Check validity and return if result[0] <= result[2] and result[1] <= result[3]: return result else: return None
[docs]def minimal_bounding_box(bbox, min_res, eps=1.0e-6): """Grow bounding box to exceed specified resolution if needed Args: * bbox: Bounding box with format [W, S, E, N] * min_res: Minimal acceptable resolution to exceed * eps: Optional tolerance that will be applied to 'buffer' result Returns: * Adjusted bounding box guaranteed to exceed specified resolution """ # FIXME (Ole): Probably obsolete now bbox = copy.copy(list(bbox)) delta_x = bbox[2] - bbox[0] delta_y = bbox[3] - bbox[1] if delta_x < min_res: dx = (min_res - delta_x) / 2 + eps bbox[0] -= dx bbox[2] += dx if delta_y < min_res: dy = (min_res - delta_y) / 2 + eps bbox[1] -= dy bbox[3] += dy return bbox
[docs]def buffered_bounding_box(bbox, resolution): """Grow bounding box with one unit of resolution in each direction Note: This will ensure there is enough pixels to robustly provide interpolated values without having to painstakingly deal with all corner cases such as 1 x 1, 1 x 2 and 2 x 1 arrays. The border will also make sure that points that would otherwise fall outside the domain (as defined by a tight bounding box) get assigned values. Args: * bbox: Bounding box with format [W, S, E, N] * resolution: (resx, resy) - Raster resolution in each direction. res - Raster resolution in either direction If resolution is None bbox is returned unchanged. Returns: * Adjusted bounding box Note: Case in point: Interpolation point O would fall outside this domain even though there are enough grid points to support it -------------- | | | * * | * * | O| | | | * * | * * -------------- """ bbox = copy.copy(list(bbox)) if resolution is None: return bbox try: resx, resy = resolution except TypeError: resx = resy = resolution bbox[0] -= resx bbox[1] -= resy bbox[2] += resx bbox[3] += resy return bbox
[docs]def get_geometry_type(geometry, geometry_type): """Determine geometry type based on data Args: * geometry: A list of either point coordinates [lon, lat] or polygons which are assumed to be numpy arrays of coordinates * geometry_type: Optional type - 'point', 'line', 'polygon' or None Returns: * geometry_type: Either ogr.wkbPoint, ogr.wkbLineString or ogr.wkbPolygon Note: If geometry type cannot be determined an Exception is raised. There is no consistency check across all entries of the geometry list, only the first element is used in this determination. """ # FIXME (Ole): Perhaps use OGR's own symbols msg = ('Argument geometry_type must be either "point", "line", ' '"polygon" or None') verify(geometry_type is None or geometry_type in [1, 2, 3] or geometry_type.lower() in ['point', 'line', 'polygon'], msg) if geometry_type is not None: if isinstance(geometry_type, basestring): return INVERSE_GEOMETRY_TYPE_MAP[geometry_type.lower()] else: return geometry_type # FIXME (Ole): Should add some additional checks to see if choice # makes sense msg = 'Argument geometry must be a sequence. I got %s ' % type(geometry) verify(is_sequence(geometry), msg) if len(geometry) == 0: # Default to point if there is no data return ogr.wkbPoint msg = ('The first element in geometry must be a sequence of length > 2. ' 'I got %s ' % str(geometry[0])) verify(is_sequence(geometry[0]), msg) verify(len(geometry[0]) >= 2, msg) if len(geometry[0]) == 2: try: float(geometry[0][0]) float(geometry[0][1]) except (ValueError, TypeError, IndexError): pass else: # This geometry appears to be point data geometry_type = ogr.wkbPoint elif len(geometry[0]) > 2: try: x = numpy.array(geometry[0]) except ValueError: pass else: # This geometry appears to be polygon data if x.shape[0] > 2 and x.shape[1] == 2: geometry_type = ogr.wkbPolygon if geometry_type is None: msg = 'Could not determine geometry type' raise Exception(msg) return geometry_type
[docs]def is_sequence(x): """Determine if x behaves like a true sequence but not a string Note: This will for example return True for lists, tuples and numpy arrays but False for strings and dictionaries. """ if isinstance(x, basestring): return False try: list(x) except TypeError: return False else: return True
[docs]def array2line(A, geometry_type=ogr.wkbLinearRing): """Convert coordinates to linear_ring Args: * A: Nx2 Array of coordinates representing either a polygon or a line. A can be either a numpy array or a list of coordinates. * geometry_type: A valid OGR geometry type. Default: ogr.wkbLinearRing Other options include ogr.wkbLineString Returns: * ring: OGR line geometry Note: Based on http://www.packtpub.com/article/working-geospatial-data-python """ try: A = ensure_numeric(A, numpy.float) except Exception, e: msg = ('Array (%s) could not be converted to numeric array. ' 'I got type %s. Error message: %s' % (A, str(type(A)), e)) raise Exception(msg) msg = 'Array must be a 2d array of vertices. I got %s' % (str(A.shape)) verify(len(A.shape) == 2, msg) msg = 'A array must have two columns. I got %s' % (str(A.shape[0])) verify(A.shape[1] == 2, msg) N = A.shape[0] # Number of vertices line = ogr.Geometry(geometry_type) for i in range(N): line.AddPoint(A[i, 0], A[i, 1]) return line
[docs]def rings_equal(x, y, rtol=1.0e-6, atol=1.0e-8): """Compares to linear rings as numpy arrays Args * x, y: Nx2 numpy arrays Returns: * True if x == y or x' == y (up to the specified tolerance) where x' is x reversed in the first dimension. This corresponds to linear rings being seen as equal irrespective of whether they are organised in clock wise or counter clock wise order """ x = ensure_numeric(x, numpy.float) y = ensure_numeric(y, numpy.float) msg = 'Arrays must a 2d arrays of vertices. I got %s and %s' % (x, y) verify(len(x.shape) == 2 and len(y.shape) == 2, msg) msg = 'Arrays must have two columns. I got %s and %s' % (x, y) verify(x.shape[1] == 2 and y.shape[1] == 2, msg) if (numpy.allclose(x, y, rtol=rtol, atol=atol) or numpy.allclose(x, y[::-1], rtol=rtol, atol=atol)): return True else: return False # FIXME (Ole): We can retire this messy function now # Positive: Delete it :-)
[docs]def array2wkt(A, geom_type='POLYGON'): """Convert coordinates to wkt format Args: * A: Nx2 Array of coordinates representing either a polygon or a line. A can be either a numpy array or a list of coordinates. * geom_type: Determines output keyword 'POLYGON' or 'LINESTRING' Returns: * wkt: geometry in the format known to ogr: Examples Note: POLYGON((1020 1030,1020 1045,1050 1045,1050 1030,1020 1030)) LINESTRING(1000 1000, 1100 1050) """ try: A = ensure_numeric(A, numpy.float) except Exception, e: msg = ('Array (%s) could not be converted to numeric array. ' 'I got type %s. Error message: %s' % (geom_type, str(type(A)), e)) raise Exception(msg) msg = 'Array must be a 2d array of vertices. I got %s' % (str(A.shape)) verify(len(A.shape) == 2, msg) msg = 'A array must have two columns. I got %s' % (str(A.shape[0])) verify(A.shape[1] == 2, msg) if geom_type == 'LINESTRING': # One bracket n = 1 elif geom_type == 'POLYGON': # Two brackets (tsk tsk) n = 2 else: msg = 'Unknown geom_type: %s' % geom_type raise Exception(msg) wkt_string = geom_type + '(' * n N = len(A) for i in range(N): # Works for both lists and arrays wkt_string += '%f %f, ' % tuple(A[i]) return wkt_string[:-2] + ')' * n # Map of ogr numerical geometry types to their textual representation # FIXME (Ole): Some of them don't exist, even though they show up # when doing dir(ogr) - Why?:
geometry_type_map = {ogr.wkbPoint: 'Point', ogr.wkbPoint25D: 'Point25D', ogr.wkbPolygon: 'Polygon', ogr.wkbPolygon25D: 'Polygon25D', #ogr.wkbLinePoint: 'LinePoint', # ?? ogr.wkbGeometryCollection: 'GeometryCollection', ogr.wkbGeometryCollection25D: 'GeometryCollection25D', ogr.wkbLineString: 'LineString', ogr.wkbLineString25D: 'LineString25D', ogr.wkbLinearRing: 'LinearRing', ogr.wkbMultiLineString: 'MultiLineString', ogr.wkbMultiLineString25D: 'MultiLineString25D', ogr.wkbMultiPoint: 'MultiPoint', ogr.wkbMultiPoint25D: 'MultiPoint25D', ogr.wkbMultiPolygon: 'MultiPolygon', ogr.wkbMultiPolygon25D: 'MultiPolygon25D', ogr.wkbNDR: 'NDR', ogr.wkbNone: 'None', ogr.wkbUnknown: 'Unknown'}
[docs]def geometrytype2string(g_type): """Provides string representation of numeric geometry types FIXME (Ole): I can't find anything like this in ORG. Why? """ if g_type in geometry_type_map: return geometry_type_map[g_type] elif g_type is None: return 'No geometry type assigned' else: return 'Unknown geometry type: %s' % str(g_type) # FIXME: Move to common numerics area along with polygon.py
[docs]def calculate_polygon_area(polygon, signed=False): """Calculate the signed area of non-self-intersecting polygon Args: * polygon: Numeric array of points (longitude, latitude). It is assumed to be closed, i.e. first and last points are identical * signed: Optional flag deciding whether returned area retains its sign: If points are ordered counter clockwise, the signed area will be positive. If points are ordered clockwise, it will be negative Default is False which means that the area is always positive. Returns: * area: Area of polygon (subject to the value of argument signed) Note: Sources http://paulbourke.net/geometry/polyarea/ http://en.wikipedia.org/wiki/Centroid """ # Make sure it is numeric P = numpy.array(polygon) msg = ('Polygon is assumed to consist of coordinate pairs. ' 'I got second dimension %i instead of 2' % P.shape[1]) verify(P.shape[1] == 2, msg) x = P[:, 0] y = P[:, 1] # Calculate 0.5 sum_{i=0}^{N-1} (x_i y_{i+1} - x_{i+1} y_i) a = x[:-1] * y[1:] b = y[:-1] * x[1:] A = numpy.sum(a - b) / 2. if signed: return A else: return abs(A)
[docs]def calculate_polygon_centroid(polygon): """Calculate the centroid of non-self-intersecting polygon Args: * polygon: Numeric array of points (longitude, latitude). It is assumed to be closed, i.e. first and last points are identical Note: Sources http://paulbourke.net/geometry/polyarea/ http://en.wikipedia.org/wiki/Centroid """ # Make sure it is numeric P = numpy.array(polygon) # Normalise to ensure numerical accurracy. # This requirement in backed by tests in test_io.py and without it # centroids at building footprint level may get shifted outside the # polygon! P_origin = numpy.amin(P, axis=0) P = P - P_origin # Get area. This calculation could be incorporated to save time # if necessary as the two formulas are very similar. A = calculate_polygon_area(polygon, signed=True) x = P[:, 0] y = P[:, 1] # Calculate # Cx = sum_{i=0}^{N-1} (x_i + x_{i+1})(x_i y_{i+1} - x_{i+1} y_i)/(6A) # Cy = sum_{i=0}^{N-1} (y_i + y_{i+1})(x_i y_{i+1} - x_{i+1} y_i)/(6A) a = x[:-1] * y[1:] b = y[:-1] * x[1:] cx = x[:-1] + x[1:] cy = y[:-1] + y[1:] Cx = numpy.sum(cx * (a - b)) / (6. * A) Cy = numpy.sum(cy * (a - b)) / (6. * A) # Translate back to real location C = numpy.array([Cx, Cy]) + P_origin return C
[docs]def points_between_points(point1, point2, delta): """Creates an array of points between two points given a delta Note: u = (x1-x0, y1-y0)/L, where L=sqrt( (x1-x0)^2 + (y1-y0)^2). If r is the resolution, then the points will be given by (x0, y0) + u * n * r for n = 1, 2, .... while len(n*u*r) < L """ x0, y0 = point1 x1, y1 = point2 L = math.sqrt(math.pow((x1 - x0), 2) + math.pow((y1 - y0), 2)) pieces = int(L / delta) uu = numpy.array([x1 - x0, y1 - y0]) / L points = [point1] for nn in range(pieces): point = point1 + uu * (nn + 1) * delta points.append(point) return numpy.array(points)
[docs]def points_along_line(line, delta): """Calculate a list of points along a line with a given delta Args: * line: Numeric array of points (longitude, latitude). * delta: Decimal number to be used as step Returns: * V: Numeric array of points (longitude, latitude). Note: Sources http://paulbourke.net/geometry/polyarea/ http://en.wikipedia.org/wiki/Centroid """ # Make sure it is numeric P = numpy.array(line) points = [] for i in range(len(P) - 1): pts = points_between_points(P[i], P[i + 1], delta) # If the first point of this list is the same # as the last one recorded, do not use it if len(points) > 0: if numpy.allclose(points[-1], pts[0]): pts = pts[1:] points.extend(pts) C = numpy.array(points) return C
[docs]def combine_polygon_and_point_layers(layers): """Combine polygon and point layers Args: layers: List of vector layers of type polygon or point Returns: One point layer with all input point layers and centroids from all input polygon layers. Raises: IneSAFEError in case a0ttribute names are not the same. """ # This is to implement issue #276 print layers
[docs]def get_ringdata(ring): """Extract coordinates from OGR ring object Args * OGR ring object Returns * Nx2 numpy array of vertex coordinates (lon, lat) """ N = ring.GetPointCount() A = numpy.zeros((N, 2), dtype='d') # FIXME (Ole): Is there any way to get the entire data vectors? for j in range(N): A[j, :] = ring.GetX(j), ring.GetY(j) # Return ring as an Nx2 numpy array return A
[docs]def get_polygondata(G): """Extract polygon data from OGR geometry :param G: OGR polygon geometry :return: List of InaSAFE polygon instances """ # Get outer ring, then inner rings # http://osgeo-org.1560.n6.nabble.com/ # gdal-dev-Polygon-topology-td3745761.html number_of_rings = G.GetGeometryCount() # Get outer ring outer_ring = get_ringdata(G.GetGeometryRef(0)) # Get inner rings if any inner_rings = [] if number_of_rings > 1: for i in range(1, number_of_rings): inner_ring = get_ringdata(G.GetGeometryRef(i)) inner_rings.append(inner_ring) # Return Polygon instance return Polygon(outer_ring=outer_ring, inner_rings=inner_rings)