[3293] | 1 | """Class Quantity - Implements values at each 1d element |
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| 2 | |
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| 3 | To create: |
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| 4 | |
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| 5 | Quantity(domain, vertex_values) |
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| 6 | |
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| 7 | domain: Associated domain structure. Required. |
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| 8 | |
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| 9 | vertex_values: N x 2 array of values at each vertex for each element. |
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| 10 | Default None |
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| 11 | |
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| 12 | If vertex_values are None Create array of zeros compatible with domain. |
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| 13 | Otherwise check that it is compatible with dimenions of domain. |
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| 14 | Otherwise raise an exception |
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| 15 | """ |
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| 16 | |
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| 17 | |
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| 18 | class Quantity: |
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| 19 | |
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| 20 | def __init__(self, domain, vertex_values=None): |
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| 21 | |
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| 22 | from domain import Domain |
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| 23 | from Numeric import array, zeros, Float |
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| 24 | |
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| 25 | msg = 'First argument in Quantity.__init__ ' |
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| 26 | msg += 'must be of class Domain (or a subclass thereof)' |
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| 27 | assert isinstance(domain, Domain), msg |
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| 28 | |
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| 29 | if vertex_values is None: |
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| 30 | N = domain.number_of_elements |
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| 31 | self.vertex_values = zeros((N, 2), Float) |
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| 32 | else: |
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| 33 | self.vertex_values = array(vertex_values, Float) |
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| 34 | |
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| 35 | N, V = self.vertex_values.shape |
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| 36 | assert V == 2,\ |
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| 37 | 'Two vertex values per element must be specified' |
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| 38 | |
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| 39 | |
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| 40 | msg = 'Number of vertex values (%d) must be consistent with'\ |
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| 41 | %N |
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| 42 | msg += 'number of elements in specified domain (%d).'\ |
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| 43 | %domain.number_of_elements |
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| 44 | |
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| 45 | assert N == domain.number_of_elements, msg |
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| 46 | |
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| 47 | self.domain = domain |
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| 48 | |
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| 49 | #Allocate space for other quantities |
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| 50 | self.centroid_values = zeros(N, Float) |
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| 51 | #self.edge_values = zeros((N, 2), Float) |
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| 52 | #edge values are values of the ends of each interval |
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| 53 | |
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| 54 | #does oe dimension need edge values??? |
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| 55 | |
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| 56 | #Intialise centroid values |
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| 57 | self.interpolate() |
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| 58 | |
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| 59 | #Methods for operator overloading |
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| 60 | def __len__(self): |
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| 61 | return self.centroid_values.shape[0] |
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| 62 | |
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| 63 | def interpolate(self): |
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| 64 | """Compute interpolated values at centroid |
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| 65 | Pre-condition: vertex_values have been set |
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| 66 | """ |
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| 67 | |
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| 68 | N = self.vertex_values.shape[0] |
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| 69 | for i in range(N): |
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| 70 | v0 = self.vertex_values[i, 0] |
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| 71 | v1 = self.vertex_values[i, 1] |
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| 72 | |
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| 73 | self.centroid_values[i] = (v0 + v1)/2 |
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| 74 | |
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| 75 | def set_values(self, X, location='vertices'): |
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| 76 | """Set values for quantity |
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| 77 | |
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| 78 | X: Compatible list, Numeric array (see below), constant or function |
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| 79 | location: Where values are to be stored. |
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| 80 | Permissible options are: vertices, centroid |
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| 81 | Default is "vertices" |
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| 82 | |
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| 83 | In case of location == 'centroid' the dimension values must |
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| 84 | be a list of a Numerical array of length N, N being the number |
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| 85 | of elements in the mesh. Otherwise it must be of dimension Nx3 |
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| 86 | |
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| 87 | The values will be stored in elements following their |
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| 88 | internal ordering. |
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| 89 | |
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| 90 | If values are described a function, it will be evaluated at specified points |
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| 91 | |
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| 92 | If selected location is vertices, values for centroid and edges |
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| 93 | will be assigned interpolated values. |
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| 94 | In any other case, only values for the specified locations |
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| 95 | will be assigned and the others will be left undefined. |
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| 96 | """ |
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| 97 | |
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| 98 | if location not in ['vertices', 'centroids']:#, 'edges']: |
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| 99 | msg = 'Invalid location: %s, (possible choices vertices, centroids)' %location |
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| 100 | raise msg |
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| 101 | |
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| 102 | if X is None: |
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| 103 | msg = 'Given values are None' |
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| 104 | raise msg |
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| 105 | |
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| 106 | import types |
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| 107 | |
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| 108 | if callable(X): |
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| 109 | #Use function specific method |
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| 110 | self.set_function_values(X, location) |
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| 111 | elif type(X) in [types.FloatType, types.IntType, types.LongType]: |
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| 112 | if location == 'centroids': |
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| 113 | self.centroid_values[:] = X |
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| 114 | else: |
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| 115 | self.vertex_values[:] = X |
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| 116 | |
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| 117 | else: |
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| 118 | #Use array specific method |
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| 119 | self.set_array_values(X, location) |
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| 120 | |
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| 121 | if location == 'vertices': |
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| 122 | #Intialise centroid and edge values |
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| 123 | self.interpolate() |
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| 124 | |
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| 125 | |
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| 126 | |
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| 127 | |
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| 128 | def set_function_values(self, f, location='vertices'): |
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| 129 | """Set values for quantity using specified function |
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| 130 | |
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| 131 | f: x -> z Function where x and z are arrays |
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| 132 | location: Where values are to be stored. |
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| 133 | Permissible options are: vertices, centroid |
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| 134 | Default is "vertices" |
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| 135 | """ |
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[3295] | 136 | |
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[3293] | 137 | if location == 'centroids': |
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[3335] | 138 | |
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[3293] | 139 | P = self.domain.centroids |
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| 140 | self.set_values(f(P), location) |
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| 141 | else: |
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| 142 | #Vertices |
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| 143 | P = self.domain.get_vertices() |
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[3335] | 144 | |
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[3293] | 145 | for i in range(2): |
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[3335] | 146 | self.vertex_values[:,i] = f(P[:,i]) |
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[3293] | 147 | |
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| 148 | def set_array_values(self, values, location='vertices'): |
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| 149 | """Set values for quantity |
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| 150 | |
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| 151 | values: Numeric array |
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| 152 | location: Where values are to be stored. |
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| 153 | Permissible options are: vertices, centroid, edges |
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| 154 | Default is "vertices" |
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| 155 | |
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| 156 | In case of location == 'centroid' the dimension values must |
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| 157 | be a list of a Numerical array of length N, N being the number |
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| 158 | of elements in the mesh. Otherwise it must be of dimension Nx2 |
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| 159 | |
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| 160 | The values will be stored in elements following their |
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| 161 | internal ordering. |
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| 162 | |
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| 163 | If selected location is vertices, values for centroid |
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| 164 | will be assigned interpolated values. |
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| 165 | In any other case, only values for the specified locations |
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| 166 | will be assigned and the others will be left undefined. |
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| 167 | """ |
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| 168 | |
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| 169 | from Numeric import array, Float |
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| 170 | |
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| 171 | values = array(values).astype(Float) |
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| 172 | |
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| 173 | N = self.centroid_values.shape[0] |
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| 174 | |
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| 175 | msg = 'Number of values must match number of elements' |
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| 176 | assert values.shape[0] == N, msg |
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| 177 | |
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| 178 | if location == 'centroids': |
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| 179 | assert len(values.shape) == 1, 'Values array must be 1d' |
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| 180 | self.centroid_values = values |
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| 181 | #elif location == 'edges': |
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| 182 | # assert len(values.shape) == 2, 'Values array must be 2d' |
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| 183 | # msg = 'Array must be N x 2' |
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| 184 | # self.edge_values = values |
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| 185 | else: |
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| 186 | assert len(values.shape) == 2, 'Values array must be 2d' |
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| 187 | msg = 'Array must be N x 2' |
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| 188 | assert values.shape[1] == 2, msg |
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| 189 | |
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| 190 | self.vertex_values = values |
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| 191 | |
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| 192 | |
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| 193 | def get_values(self, location='vertices', indices = None): |
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| 194 | """get values for quantity |
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| 195 | |
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| 196 | return X, Compatible list, Numeric array (see below) |
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| 197 | location: Where values are to be stored. |
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| 198 | Permissible options are: vertices, edges, centroid |
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| 199 | and unique vertices. Default is 'vertices' |
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| 200 | |
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| 201 | In case of location == 'centroids' the dimension values must |
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| 202 | be a list of a Numerical array of length N, N being the number |
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| 203 | of elements. Otherwise it must be of dimension Nx3 |
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| 204 | |
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| 205 | The returned values with be a list the length of indices |
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| 206 | (N if indices = None). Each value will be a list of the three |
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| 207 | vertex values for this quantity. |
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| 208 | |
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| 209 | Indices is the set of element ids that the operation applies to. |
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| 210 | |
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| 211 | """ |
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| 212 | from Numeric import take |
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| 213 | |
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| 214 | #if location not in ['vertices', 'centroids', 'edges', 'unique vertices']: |
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| 215 | if location not in ['vertices', 'centroids', 'unique vertices']: |
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| 216 | msg = 'Invalid location: %s' %location |
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| 217 | raise msg |
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| 218 | |
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| 219 | import types, Numeric |
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| 220 | assert type(indices) in [types.ListType, types.NoneType, |
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| 221 | Numeric.ArrayType],\ |
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| 222 | 'Indices must be a list or None' |
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| 223 | |
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| 224 | if location == 'centroids': |
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| 225 | if (indices == None): |
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| 226 | indices = range(len(self)) |
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| 227 | return take(self.centroid_values,indices) |
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| 228 | #elif location == 'edges': |
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| 229 | # if (indices == None): |
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| 230 | # indices = range(len(self)) |
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| 231 | # return take(self.edge_values,indices) |
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| 232 | elif location == 'unique vertices': |
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| 233 | if (indices == None): |
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| 234 | indices=range(self.domain.coordinates.shape[0]) |
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| 235 | vert_values = [] |
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| 236 | #Go through list of unique vertices |
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| 237 | for unique_vert_id in indices: |
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| 238 | triangles = self.domain.vertexlist[unique_vert_id] |
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| 239 | |
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| 240 | #In case there are unused points |
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| 241 | if triangles is None: |
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| 242 | msg = 'Unique vertex not associated with triangles' |
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| 243 | raise msg |
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| 244 | |
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| 245 | # Go through all triangle, vertex pairs |
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| 246 | # Average the values |
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| 247 | sum = 0 |
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| 248 | for triangle_id, vertex_id in triangles: |
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| 249 | sum += self.vertex_values[triangle_id, vertex_id] |
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| 250 | vert_values.append(sum/len(triangles)) |
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| 251 | return Numeric.array(vert_values) |
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| 252 | else: |
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| 253 | if (indices == None): |
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| 254 | indices = range(len(self)) |
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| 255 | return take(self.vertex_values,indices) |
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| 256 | |
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| 257 | #Method for outputting model results |
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| 258 | #FIXME: Split up into geometric and numeric stuff. |
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| 259 | #FIXME: Geometric (X,Y,V) should live in mesh.py |
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| 260 | #FIXME: STill remember to move XY to mesh |
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| 261 | def get_vertex_values(self, |
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| 262 | #xy=True, |
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| 263 | x=True, |
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| 264 | smooth = None, |
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| 265 | precision = None, |
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| 266 | reduction = None): |
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| 267 | """Return vertex values like an OBJ format |
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| 268 | |
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| 269 | The vertex values are returned as one sequence in the 1D float array A. |
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| 270 | If requested the coordinates will be returned in 1D arrays X and Y. |
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| 271 | |
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| 272 | The connectivity is represented as an integer array, V, of dimension |
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| 273 | M x 3, where M is the number of volumes. Each row has three indices |
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| 274 | into the X, Y, A arrays defining the triangle. |
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| 275 | |
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| 276 | if smooth is True, vertex values corresponding to one common |
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| 277 | coordinate set will be smoothed according to the given |
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| 278 | reduction operator. In this case vertex coordinates will be |
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| 279 | de-duplicated. |
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| 280 | |
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| 281 | If no smoothings is required, vertex coordinates and values will |
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| 282 | be aggregated as a concatenation of values at |
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| 283 | vertices 0, vertices 1 and vertices 2 |
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| 284 | |
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| 285 | |
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| 286 | Calling convention |
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| 287 | if xy is True: |
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| 288 | X,Y,A,V = get_vertex_values |
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| 289 | else: |
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| 290 | A,V = get_vertex_values |
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| 291 | |
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| 292 | """ |
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| 293 | |
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| 294 | from Numeric import concatenate, zeros, Float, Int, array, reshape |
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| 295 | |
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| 296 | |
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| 297 | if smooth is None: |
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| 298 | smooth = self.domain.smooth |
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| 299 | |
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| 300 | if precision is None: |
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| 301 | precision = Float |
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| 302 | |
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| 303 | if reduction is None: |
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| 304 | reduction = self.domain.reduction |
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| 305 | |
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| 306 | #Create connectivity |
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| 307 | |
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| 308 | if smooth == True: |
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| 309 | |
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| 310 | V = self.domain.get_vertices() |
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| 311 | N = len(self.domain.vertexlist) |
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| 312 | #N = len(self.domain.vertices) |
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| 313 | A = zeros(N, precision) |
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| 314 | |
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| 315 | #Smoothing loop |
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| 316 | for k in range(N): |
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| 317 | L = self.domain.vertexlist[k] |
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| 318 | #L = self.domain.vertices[k] |
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| 319 | |
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| 320 | #Go through all triangle, vertex pairs |
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| 321 | #contributing to vertex k and register vertex value |
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| 322 | |
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| 323 | if L is None: continue #In case there are unused points |
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| 324 | |
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| 325 | contributions = [] |
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| 326 | for volume_id, vertex_id in L: |
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| 327 | v = self.vertex_values[volume_id, vertex_id] |
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| 328 | contributions.append(v) |
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| 329 | |
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| 330 | A[k] = reduction(contributions) |
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| 331 | |
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| 332 | |
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| 333 | #if xy is True: |
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| 334 | if x is True: |
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| 335 | #X = self.domain.coordinates[:,0].astype(precision) |
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| 336 | X = self.domain.coordinates[:].astype(precision) |
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| 337 | #Y = self.domain.coordinates[:,1].astype(precision) |
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| 338 | |
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| 339 | #return X, Y, A, V |
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| 340 | return X, A, V |
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| 341 | |
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| 342 | #else: |
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| 343 | return A, V |
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| 344 | else: |
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| 345 | #Don't smooth |
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| 346 | #obj machinery moved to general_mesh |
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| 347 | |
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| 348 | # Create a V like [[0 1 2], [3 4 5]....[3*m-2 3*m-1 3*m]] |
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| 349 | # These vert_id's will relate to the verts created below |
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| 350 | #m = len(self.domain) #Number of volumes |
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| 351 | #M = 3*m #Total number of unique vertices |
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| 352 | #V = reshape(array(range(M)).astype(Int), (m,3)) |
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| 353 | |
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| 354 | #V = self.domain.get_triangles(obj=True) |
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| 355 | V = self.domain.get_vertices |
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| 356 | #FIXME use get_vertices, when ready |
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| 357 | |
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| 358 | A = self.vertex_values.flat |
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| 359 | |
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| 360 | #Do vertex coordinates |
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| 361 | #if xy is True: |
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| 362 | if x is True: |
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| 363 | C = self.domain.get_vertex_coordinates() |
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| 364 | |
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| 365 | X = C[:,0:6:2].copy() |
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| 366 | Y = C[:,1:6:2].copy() |
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| 367 | |
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| 368 | return X.flat, Y.flat, A, V |
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| 369 | else: |
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| 370 | return A, V |
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| 371 | |
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| 372 | |
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| 373 | class Conserved_quantity(Quantity): |
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| 374 | """Class conserved quantity adds to Quantity: |
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| 375 | |
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| 376 | storage and method for updating, and |
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| 377 | methods for extrapolation from centropid to vertices inluding |
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| 378 | gradients and limiters |
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| 379 | """ |
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| 380 | |
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| 381 | def __init__(self, domain, vertex_values=None): |
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| 382 | Quantity.__init__(self, domain, vertex_values) |
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| 383 | |
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| 384 | from Numeric import zeros, Float |
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| 385 | |
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| 386 | #Allocate space for boundary values |
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| 387 | #L = len(domain.boundary) |
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| 388 | self.boundary_values = zeros(2, Float) #assumes no parrellism |
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| 389 | |
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| 390 | #Allocate space for updates of conserved quantities by |
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| 391 | #flux calculations and forcing functions |
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| 392 | |
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| 393 | N = domain.number_of_elements |
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| 394 | self.explicit_update = zeros(N, Float ) |
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| 395 | self.semi_implicit_update = zeros(N, Float ) |
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| 396 | |
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| 397 | self.gradients = zeros(N, Float) |
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| 398 | self.qmax = zeros(self.centroid_values.shape, Float) |
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| 399 | self.qmin = zeros(self.centroid_values.shape, Float) |
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| 400 | |
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| 401 | self.beta = domain.beta |
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| 402 | |
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| 403 | |
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| 404 | def update(self, timestep): |
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| 405 | """Update centroid values based on values stored in |
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| 406 | explicit_update and semi_implicit_update as well as given timestep |
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| 407 | """ |
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| 408 | |
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| 409 | from Numeric import sum, equal, ones, Float |
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| 410 | |
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| 411 | N = self.centroid_values.shape[0] |
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| 412 | |
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| 413 | #Explicit updates |
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| 414 | self.centroid_values += timestep*self.explicit_update |
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| 415 | |
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[3424] | 416 | ## #Semi implicit updates |
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| 417 | ## denominator = ones(N, Float)-timestep*self.semi_implicit_update |
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[3293] | 418 | |
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[3424] | 419 | ## if sum(equal(denominator, 0.0)) > 0.0: |
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| 420 | ## msg = 'Zero division in semi implicit update. Call Stephen :-)' |
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| 421 | ## raise msg |
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| 422 | ## else: |
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| 423 | ## #Update conserved_quantities from semi implicit updates |
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| 424 | ## self.centroid_values /= denominator |
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[3293] | 425 | |
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| 426 | |
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| 427 | def compute_gradients(self): |
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| 428 | """Compute gradients of piecewise linear function defined by centroids of |
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| 429 | neighbouring volumes. |
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| 430 | """ |
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| 431 | |
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| 432 | |
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| 433 | from Numeric import array, zeros, Float |
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| 434 | |
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| 435 | N = self.centroid_values.shape[0] |
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| 436 | |
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| 437 | |
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| 438 | G = self.gradients |
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| 439 | Q = self.centroid_values |
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| 440 | X = self.domain.centroids |
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| 441 | |
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| 442 | for k in range(N): |
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| 443 | |
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| 444 | # first and last elements have boundaries |
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| 445 | |
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| 446 | if k == 0: |
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| 447 | |
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| 448 | #Get data |
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| 449 | k0 = k |
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| 450 | k1 = k+1 |
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| 451 | |
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| 452 | q0 = Q[k0] |
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| 453 | q1 = Q[k1] |
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| 454 | |
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| 455 | x0 = X[k0] #V0 centroid |
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| 456 | x1 = X[k1] #V1 centroid |
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| 457 | |
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| 458 | #Gradient |
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| 459 | G[k] = (q1 - q0)/(x1 - x0) |
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| 460 | |
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| 461 | elif k == N-1: |
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| 462 | |
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| 463 | #Get data |
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| 464 | k0 = k |
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| 465 | k1 = k-1 |
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| 466 | |
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| 467 | q0 = Q[k0] |
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| 468 | q1 = Q[k1] |
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| 469 | |
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| 470 | x0 = X[k0] #V0 centroid |
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| 471 | x1 = X[k1] #V1 centroid |
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| 472 | |
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| 473 | #Gradient |
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| 474 | G[k] = (q1 - q0)/(x1 - x0) |
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| 475 | |
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| 476 | else: |
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| 477 | #Interior Volume (2 neighbours) |
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| 478 | |
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| 479 | #Get data |
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| 480 | k0 = k-1 |
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| 481 | k2 = k+1 |
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| 482 | |
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| 483 | q0 = Q[k0] |
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| 484 | q1 = Q[k] |
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| 485 | q2 = Q[k2] |
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| 486 | |
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| 487 | x0 = X[k0] #V0 centroid |
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[3370] | 488 | x1 = X[k] #V1 centroid (Self) |
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[3293] | 489 | x2 = X[k2] #V2 centroid |
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| 490 | |
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| 491 | #Gradient |
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[3370] | 492 | #G[k] = (q2-q0)/(x2-x0) |
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[3293] | 493 | G[k] = ((q0-q1)/(x0-x1)*(x2-x1) - (q2-q1)/(x2-x1)*(x0-x1))/(x2-x0) |
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| 494 | |
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| 495 | |
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[3424] | 496 | def compute_minmod_gradients(self): |
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| 497 | """Compute gradients of piecewise linear function defined by centroids of |
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| 498 | neighbouring volumes. |
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| 499 | """ |
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| 500 | |
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| 501 | from Numeric import array, zeros, Float,sign |
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| 502 | |
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| 503 | def xmin(a,b): |
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| 504 | return 0.5*(sign(a)+sign(b))*min(abs(a),abs(b)) |
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| 505 | |
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| 506 | def xmic(t,a,b): |
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| 507 | return xmin(t*xmin(a,b), 0.50*(a+b) ) |
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| 508 | |
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| 509 | |
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| 510 | |
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| 511 | N = self.centroid_values.shape[0] |
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| 512 | |
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| 513 | |
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| 514 | G = self.gradients |
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| 515 | Q = self.centroid_values |
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| 516 | X = self.domain.centroids |
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| 517 | |
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| 518 | for k in range(N): |
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| 519 | |
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| 520 | # first and last elements have boundaries |
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| 521 | |
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| 522 | if k == 0: |
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| 523 | |
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| 524 | #Get data |
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| 525 | k0 = k |
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| 526 | k1 = k+1 |
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| 527 | |
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| 528 | q0 = Q[k0] |
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| 529 | q1 = Q[k1] |
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| 530 | |
---|
| 531 | x0 = X[k0] #V0 centroid |
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| 532 | x1 = X[k1] #V1 centroid |
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| 533 | |
---|
| 534 | #Gradient |
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| 535 | G[k] = (q1 - q0)/(x1 - x0) |
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| 536 | |
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| 537 | elif k == N-1: |
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| 538 | |
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| 539 | #Get data |
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| 540 | k0 = k |
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| 541 | k1 = k-1 |
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| 542 | |
---|
| 543 | q0 = Q[k0] |
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| 544 | q1 = Q[k1] |
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| 545 | |
---|
| 546 | x0 = X[k0] #V0 centroid |
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| 547 | x1 = X[k1] #V1 centroid |
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| 548 | |
---|
| 549 | #Gradient |
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| 550 | G[k] = (q1 - q0)/(x1 - x0) |
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| 551 | |
---|
| 552 | else: |
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| 553 | #Interior Volume (2 neighbours) |
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| 554 | |
---|
| 555 | #Get data |
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| 556 | k0 = k-1 |
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| 557 | k2 = k+1 |
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| 558 | |
---|
| 559 | q0 = Q[k0] |
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| 560 | q1 = Q[k] |
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| 561 | q2 = Q[k2] |
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| 562 | |
---|
| 563 | x0 = X[k0] #V0 centroid |
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| 564 | x1 = X[k] #V1 centroid (Self) |
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| 565 | x2 = X[k2] #V2 centroid |
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| 566 | |
---|
| 567 | # assuming uniform grid |
---|
| 568 | d1 = (q1 - q0)/(x1-x0) |
---|
| 569 | d2 = (q2 - q1)/(x2-x1) |
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| 570 | |
---|
| 571 | #Gradient |
---|
| 572 | #G[k] = (d1+d2)*0.5 |
---|
| 573 | #G[k] = (d1*(x2-x1) - d2*(x0-x1))/(x2-x0) |
---|
[3425] | 574 | G[k] = xmic( self.domain.beta, d1, d2 ) |
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[3424] | 575 | |
---|
| 576 | |
---|
[3293] | 577 | def extrapolate_first_order(self): |
---|
| 578 | """Extrapolate conserved quantities from centroid to |
---|
| 579 | vertices for each volume using |
---|
| 580 | first order scheme. |
---|
| 581 | """ |
---|
| 582 | |
---|
| 583 | qc = self.centroid_values |
---|
| 584 | qv = self.vertex_values |
---|
| 585 | |
---|
| 586 | for i in range(2): |
---|
| 587 | qv[:,i] = qc |
---|
| 588 | |
---|
| 589 | |
---|
| 590 | def extrapolate_second_order(self): |
---|
| 591 | """Extrapolate conserved quantities from centroid to |
---|
| 592 | vertices for each volume using |
---|
| 593 | second order scheme. |
---|
| 594 | """ |
---|
| 595 | |
---|
[3362] | 596 | Z = self.gradients |
---|
| 597 | #print "gradients 1",Z |
---|
| 598 | |
---|
[3424] | 599 | self.compute_minmod_gradients() |
---|
[3362] | 600 | #print "gradients 2", Z |
---|
[3293] | 601 | |
---|
| 602 | G = self.gradients |
---|
| 603 | V = self.domain.vertices |
---|
[3424] | 604 | qc = self.centroid_values |
---|
| 605 | qv = self.vertex_values |
---|
[3293] | 606 | |
---|
| 607 | #Check each triangle |
---|
| 608 | for k in range(self.domain.number_of_elements): |
---|
| 609 | #Centroid coordinates |
---|
| 610 | x = self.domain.centroids[k] |
---|
| 611 | |
---|
| 612 | #vertex coordinates |
---|
| 613 | x0, x1 = V[k,:] |
---|
[3362] | 614 | |
---|
[3293] | 615 | #Extrapolate |
---|
[3424] | 616 | qv[k,0] = qc[k] + G[k]*(x0-x) |
---|
| 617 | qv[k,1] = qc[k] + G[k]*(x1-x) |
---|
[3293] | 618 | |
---|
[3362] | 619 | """ def limit(self): |
---|
| 620 | Limit slopes for each volume to eliminate artificial variance |
---|
[3293] | 621 | introduced by e.g. second order extrapolator |
---|
| 622 | |
---|
| 623 | This is an unsophisticated limiter as it does not take into |
---|
| 624 | account dependencies among quantities. |
---|
| 625 | |
---|
| 626 | precondition: |
---|
| 627 | vertex values are estimated from gradient |
---|
| 628 | postcondition: |
---|
| 629 | vertex values are updated |
---|
[3362] | 630 | |
---|
[3335] | 631 | print "in Q.limit" |
---|
[3293] | 632 | from Numeric import zeros, Float |
---|
| 633 | |
---|
| 634 | N = self.domain.number_of_elements |
---|
| 635 | beta = self.beta |
---|
| 636 | |
---|
| 637 | qc = self.centroid_values |
---|
| 638 | qv = self.vertex_values |
---|
| 639 | |
---|
| 640 | #Find min and max of this and neighbour's centroid values |
---|
| 641 | qmax = self.qmax |
---|
| 642 | qmin = self.qmin |
---|
| 643 | |
---|
| 644 | for k in range(N): |
---|
| 645 | qmax[k] = qmin[k] = qc[k] |
---|
| 646 | |
---|
| 647 | for i in [-1,1]: |
---|
| 648 | n = k+i |
---|
| 649 | if (n >= 0) & (n <= N-1): |
---|
| 650 | qn = qc[n] #Neighbour's centroid value |
---|
| 651 | |
---|
| 652 | qmin[k] = min(qmin[k], qn) |
---|
| 653 | qmax[k] = max(qmax[k], qn) |
---|
| 654 | |
---|
| 655 | #Phi limiter |
---|
| 656 | for k in range(N): |
---|
| 657 | |
---|
| 658 | #Diffences between centroids and maxima/minima |
---|
| 659 | dqmax = qmax[k] - qc[k] |
---|
| 660 | dqmin = qmin[k] - qc[k] |
---|
| 661 | |
---|
| 662 | #Deltas between vertex and centroid values |
---|
| 663 | dq = [0.0, 0.0] |
---|
| 664 | for i in range(2): |
---|
| 665 | dq[i] = qv[k,i] - qc[k] |
---|
| 666 | |
---|
| 667 | #Find the gradient limiter (phi) across vertices |
---|
| 668 | phi = 1.0 |
---|
| 669 | for i in range(2): |
---|
| 670 | r = 1.0 |
---|
| 671 | if (dq[i] > 0): r = dqmax/dq[i] |
---|
| 672 | if (dq[i] < 0): r = dqmin/dq[i] |
---|
| 673 | |
---|
| 674 | phi = min( min(r*beta, 1), phi ) |
---|
| 675 | |
---|
| 676 | #Then update using phi limiter |
---|
| 677 | for i in range(2): |
---|
| 678 | qv[k,i] = qc[k] + phi*dq[i] |
---|
[3362] | 679 | """ |
---|
[3293] | 680 | |
---|
[3362] | 681 | def limit(self): |
---|
| 682 | """Limit slopes for each volume to eliminate artificial variance |
---|
| 683 | introduced by e.g. second order extrapolator |
---|
[3293] | 684 | |
---|
[3362] | 685 | This is an unsophisticated limiter as it does not take into |
---|
| 686 | account dependencies among quantities. |
---|
| 687 | |
---|
| 688 | precondition: |
---|
| 689 | vertex values are estimated from gradient |
---|
| 690 | postcondition: |
---|
| 691 | vertex values are updated |
---|
| 692 | """ |
---|
| 693 | |
---|
| 694 | from Numeric import zeros, Float |
---|
| 695 | |
---|
| 696 | N = self.domain.number_of_elements |
---|
[3370] | 697 | #beta = self.beta |
---|
| 698 | beta = 0.8 |
---|
[3362] | 699 | |
---|
| 700 | qc = self.centroid_values |
---|
| 701 | qv = self.vertex_values |
---|
| 702 | |
---|
| 703 | #Find min and max of this and neighbour's centroid values |
---|
| 704 | qmax = self.qmax |
---|
| 705 | qmin = self.qmin |
---|
| 706 | |
---|
| 707 | for k in range(N): |
---|
| 708 | qmax[k] = qmin[k] = qc[k] |
---|
| 709 | for i in range(2): |
---|
| 710 | n = self.domain.neighbours[k,i] |
---|
| 711 | if n >= 0: |
---|
| 712 | qn = qc[n] #Neighbour's centroid value |
---|
| 713 | |
---|
| 714 | qmin[k] = min(qmin[k], qn) |
---|
| 715 | qmax[k] = max(qmax[k], qn) |
---|
| 716 | |
---|
| 717 | |
---|
| 718 | #Diffences between centroids and maxima/minima |
---|
| 719 | dqmax = qmax - qc |
---|
| 720 | dqmin = qmin - qc |
---|
| 721 | |
---|
| 722 | #Deltas between vertex and centroid values |
---|
| 723 | dq = zeros(qv.shape, Float) |
---|
| 724 | for i in range(2): |
---|
| 725 | dq[:,i] = qv[:,i] - qc |
---|
| 726 | |
---|
| 727 | #Phi limiter |
---|
| 728 | for k in range(N): |
---|
| 729 | |
---|
| 730 | #Find the gradient limiter (phi) across vertices |
---|
| 731 | phi = 1.0 |
---|
| 732 | for i in range(2): |
---|
| 733 | r = 1.0 |
---|
| 734 | if (dq[k,i] > 0): r = dqmax[k]/dq[k,i] |
---|
| 735 | if (dq[k,i] < 0): r = dqmin[k]/dq[k,i] |
---|
| 736 | |
---|
| 737 | phi = min( min(r*beta, 1), phi ) |
---|
| 738 | |
---|
| 739 | #Then update using phi limiter |
---|
| 740 | for i in range(2): |
---|
| 741 | qv[k,i] = qc[k] + phi*dq[k,i] |
---|
| 742 | |
---|
| 743 | |
---|
| 744 | |
---|
[3322] | 745 | def newLinePlot(title='Simple Plot'): |
---|
| 746 | import Gnuplot |
---|
| 747 | g = Gnuplot.Gnuplot() |
---|
| 748 | g.title(title) |
---|
| 749 | g('set data style linespoints') |
---|
| 750 | g.xlabel('x') |
---|
| 751 | g.ylabel('y') |
---|
| 752 | return g |
---|
[3293] | 753 | |
---|
[3322] | 754 | def linePlot(g,x,y): |
---|
| 755 | import Gnuplot |
---|
| 756 | g.plot(Gnuplot.PlotItems.Data(x.flat,y.flat)) |
---|
| 757 | |
---|
| 758 | |
---|
| 759 | |
---|
| 760 | |
---|
| 761 | |
---|
[3293] | 762 | if __name__ == "__main__": |
---|
| 763 | from domain import Domain |
---|
[3322] | 764 | from Numeric import arange |
---|
| 765 | |
---|
[3293] | 766 | points1 = [0.0, 1.0, 2.0, 3.0] |
---|
| 767 | vertex_values = [[1.0,2.0],[4.0,5.0],[-1.0,2.0]] |
---|
| 768 | |
---|
| 769 | D1 = Domain(points1) |
---|
| 770 | |
---|
| 771 | Q1 = Conserved_quantity(D1, vertex_values) |
---|
| 772 | |
---|
| 773 | print Q1.vertex_values |
---|
| 774 | print Q1.centroid_values |
---|
| 775 | |
---|
| 776 | new_vertex_values = [[2.0,1.0],[3.0,4.0],[-2.0,4.0]] |
---|
| 777 | |
---|
| 778 | Q1.set_values(new_vertex_values) |
---|
| 779 | |
---|
| 780 | print Q1.vertex_values |
---|
| 781 | print Q1.centroid_values |
---|
| 782 | |
---|
| 783 | new_centroid_values = [20,30,40] |
---|
| 784 | Q1.set_values(new_centroid_values,'centroids') |
---|
| 785 | |
---|
| 786 | print Q1.vertex_values |
---|
| 787 | print Q1.centroid_values |
---|
| 788 | |
---|
[3322] | 789 | class FunClass: |
---|
| 790 | def __init__(self,value): |
---|
| 791 | self.value = value |
---|
[3293] | 792 | |
---|
[3322] | 793 | def __call__(self,x): |
---|
| 794 | return self.value*(x**2) |
---|
| 795 | |
---|
| 796 | |
---|
| 797 | fun = FunClass(1.0) |
---|
[3293] | 798 | Q1.set_values(fun,'vertices') |
---|
| 799 | |
---|
| 800 | print Q1.vertex_values |
---|
| 801 | print Q1.centroid_values |
---|
| 802 | |
---|
| 803 | Xc = Q1.domain.vertices |
---|
| 804 | Qc = Q1.vertex_values |
---|
| 805 | print Xc |
---|
| 806 | print Qc |
---|
| 807 | |
---|
| 808 | Qc[1,0] = 3 |
---|
| 809 | |
---|
| 810 | Q1.beta = 1.0 |
---|
| 811 | Q1.extrapolate_second_order() |
---|
| 812 | Q1.limit() |
---|
| 813 | |
---|
[3322] | 814 | g1 = newLinePlot('plot 1') |
---|
| 815 | linePlot(g1,Xc,Qc) |
---|
[3293] | 816 | |
---|
| 817 | points2 = arange(10) |
---|
| 818 | D2 = Domain(points2) |
---|
| 819 | |
---|
| 820 | Q2 = Conserved_quantity(D2) |
---|
| 821 | Q2.set_values(fun,'vertices') |
---|
| 822 | Xc = Q2.domain.vertices |
---|
| 823 | Qc = Q2.vertex_values |
---|
| 824 | |
---|
[3322] | 825 | g2 = newLinePlot('plot 2') |
---|
| 826 | linePlot(g2,Xc,Qc) |
---|
| 827 | |
---|
| 828 | |
---|
| 829 | |
---|
[3293] | 830 | Q2.extrapolate_second_order() |
---|
| 831 | Q2.limit() |
---|
| 832 | Xc = Q2.domain.vertices |
---|
| 833 | Qc = Q2.vertex_values |
---|
| 834 | |
---|
| 835 | print Q2.centroid_values |
---|
| 836 | print Qc |
---|
[3335] | 837 | raw_input('press_return') |
---|
| 838 | |
---|
[3322] | 839 | g3 = newLinePlot('plot 3') |
---|
| 840 | linePlot(g3,Xc,Qc) |
---|
| 841 | raw_input('press return') |
---|
[3293] | 842 | |
---|
| 843 | |
---|
[3322] | 844 | for i in range(10): |
---|
| 845 | fun = FunClass(i/10.0) |
---|
| 846 | Q2.set_values(fun,'vertices') |
---|
| 847 | Qc = Q2.vertex_values |
---|
| 848 | linePlot(g3,Xc,Qc) |
---|
[3293] | 849 | |
---|
[3322] | 850 | raw_input('press return') |
---|
[3293] | 851 | |
---|