def test_bigger(self):
"""test_bigger
test larger mesh
"""
points, vertices, boundary = rectangular(4, 4, 1, 1)
mesh = Mesh(points, vertices, boundary)
#Test that points are arranged in a counter clock wise order
mesh.check_integrity()
root = MeshQuadtree(mesh)
root.set_last_triangle()
for x in [[0.6, 0.3], [0.1, 0.2], [0.7,0.7],
[0.1,0.9], [0.4,0.6], [0.9,0.1],
[10, 3]]:
found, s0, s1, s2, k = root.search_fast(ensure_numeric(x))
if k >= 0:
V = mesh.get_vertex_coordinates(k) # nodes for triangle k
assert is_inside_polygon(x, V)
assert found is True
#print k, x
else:
assert found is False
def build_submesh(nodes, triangles, boundary, quantities,
triangles_per_proc, parameters = None):
# Temporarily build the mesh to find the neighbouring
# triangles and true boundary polygon\
mesh = Mesh(nodes, triangles, boundary)
boundary_polygon = mesh.get_boundary_polygon()
# Subdivide into non-overlapping partitions
submeshf = submesh_full(mesh, triangles_per_proc)
# Add any extra ghost boundary layer information
submeshg = submesh_ghost(submeshf, mesh, triangles_per_proc, parameters)
# Order the quantities information to be the same as the triangle
# information
submesh = submesh_quantities(submeshg, quantities, \
triangles_per_proc)
submesh["boundary_polygon"] = boundary_polygon
return submesh
def test_large(self):
"""test_larger mesh and different quad trees
"""
points, vertices, boundary = rectangular(10, 12, 1, 1)
mesh = Mesh(points, vertices, boundary)
#Test that points are arranged in a counter clock wise order
mesh.check_integrity()
root = MeshQuadtree(mesh)
root.set_last_triangle()
#print m, root.show()
for x in [[0.6, 0.3], [0.1, 0.2], [0.7,0.7],
[0.1,0.9], [0.4,0.6], [0.9,0.1],
[10, 3]]:
found, s0, s1, s2, k = root.search_fast(x)
if k >= 0:
V = mesh.get_vertex_coordinates(k) # nodes for triangle k
assert is_inside_triangle(x, V, closed=True)
assert is_inside_polygon(x, V)
assert found is True
else:
assert found is False
if k == 0: return
def get_matrix_A(fn, gauge_name):
# points to read information from
point_reader = reader(file(gauge_name))
points = []
point_name = []
for i, row in enumerate(point_reader):
if i == 0:
for j, value in enumerate(row):
if value.strip() == 'easting': easting = j
if value.strip() == 'northing': northing = j
if value.strip() == 'name': name = j
if value.strip() == 'elevation': elevation = j
else:
#points.append([float(row[easting]),float(row[northing])])
points.append([float(row[easting]), float(row[northing])])
point_name.append(row[name])
points_array = np.array(points, np.float)
dim_gauge = int(np.sqrt(points_array.shape[0]))
interpolation_points = ensure_absolute(points_array)
# read the sww file to extract something
fid = NetCDFFile(fn, netcdf_mode_r)
xllcorner = fid.xllcorner
yllcorner = fid.yllcorner
zone = fid.zone
x = fid.variables['x'][:]
y = fid.variables['y'][:]
triangles = fid.variables['volumes'][:]
x = np.reshape(x, (len(x), 1))
y = np.reshape(y, (len(y), 1))
vertex_coordinates = np.concatenate((x, y), axis=1)
ele = fid.variables['elevation'][:]
fid.close()
vertex_coordinates = ensure_absolute(vertex_coordinates)
triangles = ensure_numeric(triangles)
interpolation_points = ensure_numeric(interpolation_points)
interpolation_points[:, 0] -= xllcorner
interpolation_points[:, 1] -= yllcorner
mesh = Mesh(vertex_coordinates, triangles)
mesh_boundary_polygon = mesh.get_boundary_polygon()
indices = outside_polygon(interpolation_points, mesh_boundary_polygon)
interp = Interpolate(vertex_coordinates, triangles)
matrix_A, inside_poly_indices, outside_poly_indices, centroids = interp._build_interpolation_matrix_A(
interpolation_points, output_centroids=False, verbose=False)
ele = matrix_A * ele
ele = np.asarray(ele)
ele = ele.reshape((100, 100))
return ele, matrix_A
def test_small(self):
"""test_small: Two triangles
"""
points, vertices, boundary = rectangular(1, 1, 1, 1)
mesh = Mesh(points, vertices, boundary)
#Test that points are arranged in a counter clock wise order
mesh.check_integrity()
root = MeshQuadtree(mesh)
root.set_last_triangle()
x = [0.2, 0.7]
found, s0, s1, s2, k = root.search_fast(x)
assert k == 1 # Triangle one
assert found is True
def test_small(self):
"""test_small: Two triangles
"""
points, vertices, boundary = rectangular(1, 1, 1, 1)
mesh = Mesh(points, vertices, boundary)
#Test that points are arranged in a counter clock wise order
mesh.check_integrity()
root = MeshQuadtree(mesh)
root.set_last_triangle()
x = [0.2, 0.7]
found, s0, s1, s2, k = root.search_fast(x)
assert k == 1 # Triangle one
assert found is True
def test_off_and_boundary(self):
"""test_off: Test a point off the mesh
"""
points, vertices, boundary = rectangular(1, 1, 1, 1)
mesh = Mesh(points, vertices, boundary)
#Test that points are arranged in a counter clock wise order
mesh.check_integrity()
root = MeshQuadtree(mesh)
root.set_last_triangle()
found, s0, s1, s2, k = root.search_fast([-0.2, 10.7])
assert found is False
found, s0, s1, s2, k = root.search_fast([0, 0])
assert found is True
def test_off_and_boundary(self):
"""test_off: Test a point off the mesh
"""
points, vertices, boundary = rectangular(1, 1, 1, 1)
mesh = Mesh(points, vertices, boundary)
#Test that points are arranged in a counter clock wise order
mesh.check_integrity()
root = MeshQuadtree(mesh)
root.set_last_triangle()
found, s0, s1, s2, k = root.search_fast([-0.2, 10.7])
assert found is False
found, s0, s1, s2, k = root.search_fast([0, 0])
assert found is True
def test_underlying_function(self):
"""test_larger mesh and different quad trees
"""
return
points, vertices, boundary = rectangular(2, 2, 1, 1)
mesh = Mesh(points, vertices, boundary)
root = MeshQuadtree(mesh)
root.set_last_triangle()
# One point
x = ensure_numeric([0.5, 0.5])
found, sigma0, sigma1, sigma2, k = \
root._search_triangles_of_vertices(root.search(x), x)
if k >= 0:
V = mesh.get_vertex_coordinates(k) # nodes for triangle k
assert is_inside_polygon(x, V)
assert found is True
else:
assert found is False
# More points
for x in [[0.6, 0.3], [0.1, 0.2], [0.7,0.7],
[0.1,0.9], [0.4,0.6], [0.9,0.1],
[10, 3]]:
triangles = root.search(x)
#print x, candidate_vertices
found, sigma0, sigma1, sigma2, k = \
root._search_triangles_of_vertices(triangles,
ensure_numeric(x))
if k >= 0:
V = mesh.get_vertex_coordinates(k) # nodes for triangle k
assert is_inside_polygon(x, V)
assert found is True
else:
assert found is False
def test_underlying_function(self):
"""test_larger mesh and different quad trees
"""
return
points, vertices, boundary = rectangular(2, 2, 1, 1)
mesh = Mesh(points, vertices, boundary)
root = MeshQuadtree(mesh)
root.set_last_triangle()
# One point
x = ensure_numeric([0.5, 0.5])
found, sigma0, sigma1, sigma2, k = \
root._search_triangles_of_vertices(root.search(x), x)
if k >= 0:
V = mesh.get_vertex_coordinates(k) # nodes for triangle k
assert is_inside_polygon(x, V)
assert found is True
else:
assert found is False
# More points
for x in [[0.6, 0.3], [0.1, 0.2], [0.7,0.7],
[0.1,0.9], [0.4,0.6], [0.9,0.1],
[10, 3]]:
triangles = root.search(x)
#print x, candidate_vertices
found, sigma0, sigma1, sigma2, k = \
root._search_triangles_of_vertices(triangles,
ensure_numeric(x))
if k >= 0:
V = mesh.get_vertex_coordinates(k) # nodes for triangle k
assert is_inside_polygon(x, V)
assert found is True
else:
assert found is False
def expanding_search(self):
"""test_larger mesh and different quad trees
"""
p0 = [2,1]
p1 = [4,1]
p2 = [4.,4]
p3 = [2,4]
p4 = [5,4]
p5 = [-1,-1]
p6 = [1,-1]
p7 = [1,1]
p8 = [-1,1]
points = [p0,p1,p2, p3,p4,p5,p6,p7,p8]
#
vertices = [[0,1,2],[0,2,3],[1,4,2],[5,6,7], [5,7,8]]
mesh = Mesh(points, vertices)
# Don't do this, want to control the max and mins
#root = build_quadtree(mesh, max_points_per_cell=4)
root = Cell(-3, 9, -3, 9,
max_points_per_cell = 4)
#Insert indices of all vertices
root.insert( list(range(mesh.number_of_nodes)) )
#Build quad tree and return
root.split()
# One point
#x = [3.5, 1.5]
x = [2.5, 1.5]
element_found, sigma0, sigma1, sigma2, k = root.search_fast(x)
# One point
x = [3.00005, 2.999994]
element_found, sigma0, sigma1, sigma2, k = root.search_fast(x)
assert element_found is True
assert k == 1
def _fit_to_mesh(point_coordinates,
vertex_coordinates=None,
triangles=None,
mesh=None,
point_attributes=None,
alpha=DEFAULT_ALPHA,
verbose=False,
mesh_origin=None,
data_origin=None,
max_read_lines=None,
attribute_name=None,
cg_precon='Jacobi',
use_c_cg=True):
"""
Fit a smooth surface to a triangulation,
given data points with attributes.
Inputs:
vertex_coordinates: List of coordinate pairs [xi, eta] of
points constituting a mesh (or an m x 2 numeric array or
a geospatial object)
Points may appear multiple times
(e.g. if vertices have discontinuities)
triangles: List of 3-tuples (or a numeric array) of
integers representing indices of all vertices in the mesh.
point_coordinates: List of coordinate pairs [x, y] of data points
(or an nx2 numeric array). This can also be a .csv/.txt/.pts
file name.
alpha: Smoothing parameter.
mesh_origin: A geo_reference object or 3-tuples consisting of
UTM zone, easting and northing.
If specified vertex coordinates are assumed to be
relative to their respective origins.
point_attributes: Vector or array of data at the
point_coordinates.
"""
if mesh is None:
# FIXME(DSG): Throw errors if triangles or vertex_coordinates
# are None
#Convert input to numeric arrays
triangles = ensure_numeric(triangles, num.int)
vertex_coordinates = ensure_absolute(vertex_coordinates,
geo_reference=mesh_origin)
if verbose:
log.critical('_fit_to_mesh: Building mesh')
mesh = Mesh(vertex_coordinates, triangles)
# Don't need this as we have just created the mesh
#mesh.check_integrity()
interp = Fit(mesh=mesh,
verbose=verbose,
alpha=alpha,
cg_precon=cg_precon,
use_c_cg=use_c_cg)
vertex_attributes = interp.fit(point_coordinates,
point_attributes,
point_origin=data_origin,
max_read_lines=max_read_lines,
attribute_name=attribute_name,
verbose=verbose)
# Add the value checking stuff that's in least squares.
# Maybe this stuff should get pushed down into Fit.
# at least be a method of Fit.
# Or intigrate it into the fit method, saving teh max and min's
# as att's.
return vertex_attributes
def __init__(self,
time,
quantities,
quantity_names=None,
vertex_coordinates=None,
triangles=None,
interpolation_points=None,
time_thinning=1,
verbose=False,
gauge_neighbour_id=None,
output_centroids=False):
"""Initialise object and build spatial interpolation if required
Time_thinning_number controls how many timesteps to use. Only timesteps
with index%time_thinning_number == 0 will used, or in other words a
value of 3, say, will cause the algorithm to use every third time step.
"""
from anuga.config import time_format
if verbose is True:
log.critical('Interpolation_function: input checks')
# Check temporal info
time = ensure_numeric(time)
if not num.alltrue(time[1:] - time[:-1] >= 0):
# This message is time consuming to form due to the conversion of
msg = 'Time must be a monotonuosly increasing sequence %s' % time
raise Exception(msg)
# Check if quantities is a single array only
if not isinstance(quantities, dict):
quantities = ensure_numeric(quantities)
quantity_names = ['Attribute']
# Make it a dictionary
quantities = {quantity_names[0]: quantities}
# Use keys if no names are specified
if quantity_names is None:
quantity_names = list(quantities.keys())
# Check spatial info
if vertex_coordinates is None:
self.spatial = False
else:
# FIXME (Ole): Try ensure_numeric here -
# this function knows nothing about georefering.
vertex_coordinates = ensure_absolute(vertex_coordinates)
if triangles is not None:
triangles = ensure_numeric(triangles)
self.spatial = True
if verbose is True:
log.critical('Interpolation_function: thinning by %d' %
time_thinning)
# Thin timesteps if needed
# Note array() is used to make the thinned arrays contiguous in memory
self.time = num.array(time[::time_thinning])
for name in quantity_names:
if len(quantities[name].shape) == 2:
quantities[name] = num.array(
quantities[name][::time_thinning, :])
if verbose is True:
log.critical('Interpolation_function: precomputing')
# Save for use with statistics
self.quantities_range = {}
for name in quantity_names:
q = quantities[name][:].flatten()
self.quantities_range[name] = [min(q), max(q)]
self.quantity_names = quantity_names
self.vertex_coordinates = vertex_coordinates
self.interpolation_points = interpolation_points
self.index = 0 # Initial time index
self.precomputed_values = {}
self.centroids = []
# Precomputed spatial interpolation if requested
if interpolation_points is not None:
#no longer true. sts files have spatial = True but
#if self.spatial is False:
# raise Exception('Triangles and vertex_coordinates must be specified')
#
try:
self.interpolation_points = \
interpolation_points = ensure_numeric(interpolation_points)
except:
msg = 'Interpolation points must be an N x 2 numeric array ' \
'or a list of points\n'
msg += 'Got: %s.' % (str(self.interpolation_points)[:60] +
'...')
raise Exception(msg)
# Ensure 'mesh_boundary_polygon' is defined
mesh_boundary_polygon = None
if triangles is not None and vertex_coordinates is not None:
# Check that all interpolation points fall within
# mesh boundary as defined by triangles and vertex_coordinates.
from anuga.abstract_2d_finite_volumes.neighbour_mesh import Mesh
from anuga.geometry.polygon import outside_polygon
# Create temporary mesh object from mesh info passed
# into this function.
mesh = Mesh(vertex_coordinates, triangles)
mesh_boundary_polygon = mesh.get_boundary_polygon()
indices = outside_polygon(interpolation_points,
mesh_boundary_polygon)
# Record result
#self.mesh_boundary_polygon = mesh_boundary_polygon
self.indices_outside_mesh = indices
# Report
if len(indices) > 0:
msg = 'Interpolation points in Interpolation function fall '
msg += 'outside specified mesh. Offending points:\n'
out_interp_pts = []
for i in indices:
msg += '%d: %s\n' % (i, interpolation_points[i])
out_interp_pts.append(
ensure_numeric(interpolation_points[i]))
if verbose is True:
import sys
from anuga.geometry.polygon import plot_polygons
title = ('Interpolation points fall '
'outside specified mesh')
plot_polygons([
mesh_boundary_polygon, interpolation_points,
out_interp_pts
], ['line', 'point', 'outside'],
figname='points_boundary_out',
label=title)
# Joaquim Luis suggested this as an Exception, so
# that the user can now what the problem is rather than
# looking for NaN's. However, NANs are handy as they can
# be ignored leaving good points for continued processing.
if verbose:
log.critical(msg)
#raise Exception(msg)
elif triangles is None and vertex_coordinates is not None: #jj
#Dealing with sts file
pass
else:
raise Exception(
'Sww file function requires both triangles and '
'vertex_coordinates. sts file file function '
'requires the latter.')
# Plot boundary and interpolation points,
# but only if if 'mesh_boundary_polygon' has data.
if verbose is True and mesh_boundary_polygon is not None:
import sys
if sys.platform == 'win32':
from anuga.geometry.polygon import plot_polygons
title = ('Interpolation function: '
'Polygon and interpolation points')
plot_polygons(
[mesh_boundary_polygon, interpolation_points],
['line', 'point'],
figname='points_boundary',
label=title)
m = len(self.interpolation_points)
p = len(self.time)
for name in quantity_names:
self.precomputed_values[name] = num.zeros((p, m), num.float)
if verbose is True:
log.critical('Build interpolator')
# Build interpolator
if triangles is not None and vertex_coordinates is not None:
if verbose:
msg = 'Building interpolation matrix from source mesh '
msg += '(%d vertices, %d triangles)' \
% (vertex_coordinates.shape[0],
triangles.shape[0])
log.critical(msg)
# This one is no longer needed for STS files
interpol = Interpolate(vertex_coordinates,
triangles,
verbose=verbose)
elif triangles is None and vertex_coordinates is not None:
if verbose:
log.critical('Interpolation from STS file')
if verbose:
log.critical(
'Interpolating (%d interpolation points, %d timesteps).' %
(self.interpolation_points.shape[0], self.time.shape[0]))
if time_thinning > 1:
log.critical('Timesteps were thinned by a factor of %d' %
time_thinning)
else:
log.critical()
for i, t in enumerate(self.time):
# Interpolate quantities at this timestep
#if verbose and i%((p+10)/10) == 0:
if verbose:
log.critical(' time step %d of %d' % (i, p))
for name in quantity_names:
if len(quantities[name].shape) == 2:
Q = quantities[name][i, :] # Quantities at timestep i
else:
Q = quantities[name][:] # No time dependency
#if verbose and i%((p+10)/10) == 0:
if verbose:
log.critical(' quantity %s, size=%d' %
(name, len(Q)))
# Interpolate
if triangles is not None and vertex_coordinates is not None:
result = interpol.interpolate(Q,
point_coordinates=\
self.interpolation_points,
verbose=False,
output_centroids=output_centroids)
self.centroids = interpol.centroids
elif triangles is None and vertex_coordinates is not None:
result = interpolate_polyline(Q,
vertex_coordinates,
gauge_neighbour_id,
interpolation_points=\
self.interpolation_points)
#assert len(result), len(interpolation_points)
self.precomputed_values[name][i, :] = result
# Report
if verbose:
log.critical(self.statistics())
else:
# Store quantitites as is
for name in quantity_names:
self.precomputed_values[name] = quantities[name]
def __init__(self,
time,
quantities,
quantity_names=None,
vertex_coordinates=None,
triangles=None,
interpolation_points=None,
time_thinning=1,
verbose=False,
gauge_neighbour_id=None,
output_centroids=False):
"""Initialise object and build spatial interpolation if required
Time_thinning_number controls how many timesteps to use. Only timesteps
with index%time_thinning_number == 0 will used, or in other words a
value of 3, say, will cause the algorithm to use every third time step.
"""
from anuga.config import time_format
if verbose is True:
log.critical('Interpolation_function: input checks')
# Check temporal info
time = ensure_numeric(time)
if not num.alltrue(time[1:] - time[:-1] >= 0):
# This message is time consuming to form due to the conversion of
msg = 'Time must be a monotonuosly increasing sequence %s' % time
raise Exception(msg)
# Check if quantities is a single array only
if not isinstance(quantities, dict):
quantities = ensure_numeric(quantities)
quantity_names = ['Attribute']
# Make it a dictionary
quantities = {quantity_names[0]: quantities}
# Use keys if no names are specified
if quantity_names is None:
quantity_names = quantities.keys()
# Check spatial info
if vertex_coordinates is None:
self.spatial = False
else:
# FIXME (Ole): Try ensure_numeric here -
# this function knows nothing about georefering.
vertex_coordinates = ensure_absolute(vertex_coordinates)
if triangles is not None:
triangles = ensure_numeric(triangles)
self.spatial = True
if verbose is True:
log.critical('Interpolation_function: thinning by %d'
% time_thinning)
# Thin timesteps if needed
# Note array() is used to make the thinned arrays contiguous in memory
self.time = num.array(time[::time_thinning])
for name in quantity_names:
if len(quantities[name].shape) == 2:
quantities[name] = num.array(quantities[name][::time_thinning,:])
if verbose is True:
log.critical('Interpolation_function: precomputing')
# Save for use with statistics
self.quantities_range = {}
for name in quantity_names:
q = quantities[name][:].flatten()
self.quantities_range[name] = [min(q), max(q)]
self.quantity_names = quantity_names
self.vertex_coordinates = vertex_coordinates
self.interpolation_points = interpolation_points
self.index = 0 # Initial time index
self.precomputed_values = {}
self.centroids = []
# Precomputed spatial interpolation if requested
if interpolation_points is not None:
#no longer true. sts files have spatial = True but
#if self.spatial is False:
# raise Exception('Triangles and vertex_coordinates must be specified')
#
try:
self.interpolation_points = \
interpolation_points = ensure_numeric(interpolation_points)
except:
msg = 'Interpolation points must be an N x 2 numeric array ' \
'or a list of points\n'
msg += 'Got: %s.' %(str(self.interpolation_points)[:60] + '...')
raise Exception(msg)
# Ensure 'mesh_boundary_polygon' is defined
mesh_boundary_polygon = None
if triangles is not None and vertex_coordinates is not None:
# Check that all interpolation points fall within
# mesh boundary as defined by triangles and vertex_coordinates.
from anuga.abstract_2d_finite_volumes.neighbour_mesh import Mesh
from anuga.geometry.polygon import outside_polygon
# Create temporary mesh object from mesh info passed
# into this function.
mesh = Mesh(vertex_coordinates, triangles)
mesh_boundary_polygon = mesh.get_boundary_polygon()
indices = outside_polygon(interpolation_points,
mesh_boundary_polygon)
# Record result
#self.mesh_boundary_polygon = mesh_boundary_polygon
self.indices_outside_mesh = indices
# Report
if len(indices) > 0:
msg = 'Interpolation points in Interpolation function fall '
msg += 'outside specified mesh. Offending points:\n'
out_interp_pts = []
for i in indices:
msg += '%d: %s\n' % (i, interpolation_points[i])
out_interp_pts.append(
ensure_numeric(interpolation_points[i]))
if verbose is True:
import sys
from anuga.geometry.polygon import plot_polygons
title = ('Interpolation points fall '
'outside specified mesh')
plot_polygons([mesh_boundary_polygon,
interpolation_points,
out_interp_pts],
['line', 'point', 'outside'],
figname='points_boundary_out',
label=title)
# Joaquim Luis suggested this as an Exception, so
# that the user can now what the problem is rather than
# looking for NaN's. However, NANs are handy as they can
# be ignored leaving good points for continued processing.
if verbose:
log.critical(msg)
#raise Exception(msg)
elif triangles is None and vertex_coordinates is not None: #jj
#Dealing with sts file
pass
else:
raise Exception('Sww file function requires both triangles and '
'vertex_coordinates. sts file file function '
'requires the latter.')
# Plot boundary and interpolation points,
# but only if if 'mesh_boundary_polygon' has data.
if verbose is True and mesh_boundary_polygon is not None:
import sys
if sys.platform == 'win32':
from anuga.geometry.polygon import plot_polygons
title = ('Interpolation function: '
'Polygon and interpolation points')
plot_polygons([mesh_boundary_polygon,
interpolation_points],
['line', 'point'],
figname='points_boundary',
label=title)
m = len(self.interpolation_points)
p = len(self.time)
for name in quantity_names:
self.precomputed_values[name] = num.zeros((p, m), num.float)
if verbose is True:
log.critical('Build interpolator')
# Build interpolator
if triangles is not None and vertex_coordinates is not None:
if verbose:
msg = 'Building interpolation matrix from source mesh '
msg += '(%d vertices, %d triangles)' \
% (vertex_coordinates.shape[0],
triangles.shape[0])
log.critical(msg)
# This one is no longer needed for STS files
interpol = Interpolate(vertex_coordinates,
triangles,
verbose=verbose)
elif triangles is None and vertex_coordinates is not None:
if verbose:
log.critical('Interpolation from STS file')
if verbose:
log.critical('Interpolating (%d interpolation points, %d timesteps).'
% (self.interpolation_points.shape[0], self.time.shape[0]))
if time_thinning > 1:
log.critical('Timesteps were thinned by a factor of %d'
% time_thinning)
else:
log.critical()
for i, t in enumerate(self.time):
# Interpolate quantities at this timestep
#if verbose and i%((p+10)/10) == 0:
if verbose:
log.critical(' time step %d of %d' % (i, p))
for name in quantity_names:
if len(quantities[name].shape) == 2:
Q = quantities[name][i,:] # Quantities at timestep i
else:
Q = quantities[name][:] # No time dependency
#if verbose and i%((p+10)/10) == 0:
if verbose:
log.critical(' quantity %s, size=%d' % (name, len(Q)))
# Interpolate
if triangles is not None and vertex_coordinates is not None:
result = interpol.interpolate(Q,
point_coordinates=\
self.interpolation_points,
verbose=False,
output_centroids=output_centroids)
self.centroids = interpol.centroids
elif triangles is None and vertex_coordinates is not None:
result = interpolate_polyline(Q,
vertex_coordinates,
gauge_neighbour_id,
interpolation_points=\
self.interpolation_points)
#assert len(result), len(interpolation_points)
self.precomputed_values[name][i, :] = result
# Report
if verbose:
log.critical(self.statistics())
else:
# Store quantitites as is
for name in quantity_names:
self.precomputed_values[name] = quantities[name]
def __init__(self,
vertex_coordinates=None,
triangles=None,
mesh=None,
mesh_origin=None,
verbose=False):
""" Build interpolation matrix mapping from
function values at vertices to function values at data points
Pass in a mesh instance or vertex_coordinates and triangles
and optionally mesh_origin
Inputs:
vertex_coordinates: List of coordinate pairs [xi, eta] of
points constituting a mesh (or an m x 2 numeric array or
a geospatial object)
Points may appear multiple times
(e.g. if vertices have discontinuities)
triangles: List of 3-tuples (or a numeric array) of
integers representing indices of all vertices in the mesh.
mesh: A mesh instance describing the mesh.
mesh_origin: A geo_reference object or 3-tuples consisting of
UTM zone, easting and northing.
If specified vertex coordinates are assumed to be
relative to their respective origins.
Note: Don't supply a vertex coords as a geospatial object and
a mesh origin, since geospatial has its own mesh origin.
"""
# NOTE PADARN: The Fit_Interpolate class now uses a the c based
# quad tree to store triangles, rather than the python based tree.
# The tree is still stored at self.root. However, the subtrees of
# the new quad tree can not be directly accessed by python as
# was previously possible.
# Most of the previous functionality has been preserved.
global build_quadtree_time
if mesh is None:
if vertex_coordinates is not None and triangles is not None:
# Fixme (DSG) Throw errors if triangles or vertex_coordinates
# are None
# Convert input to numeric arrays
triangles = ensure_numeric(triangles, num.int)
vertex_coordinates = ensure_absolute(vertex_coordinates,
geo_reference=mesh_origin)
if verbose:
log.critical('FitInterpolate: Building mesh')
self.mesh = Mesh(vertex_coordinates, triangles)
#self.mesh.check_integrity() # Time consuming
else:
self.mesh = None
else:
self.mesh = mesh
if self.mesh is not None:
if verbose:
log.critical('FitInterpolate: Building quad tree')
#This stores indices of vertices
t0 = time.time()
self.root = MeshQuadtree(self.mesh, verbose=verbose)
build_quadtree_time = time.time() - t0
