How to use create_variable method in autotest
Best Python code snippet using autotest_python
values_v2_test.py
Source:values_v2_test.py 
...32 # all defined. It verifies methods and properties that have the same code path33 # under different replicas/devices as well. It is not intended to verify34 # methods and properties that behave differently under different35 # replicas/devices; those should be covered separate tests.36 def create_variable(self, initial_value=1., **kwargs):37 raise NotImplementedError38 @property39 def devices(self):40 return ["CPU:0", "CPU:1"]41 # ==== Begin Variable interface ===42 # Please follow the same order as methods and properties defined in43 # tf.Variable.44 def testStringify(self):45 v = self.create_variable()46 self.assertIsInstance(v.__str__(), str)47 self.assertIsInstance(v.__repr__(), str)48 def testDenseRead(self):49 v = self.create_variable(1.)50 self.assertEqual(v.value(), 1.)51 self.assertEqual(v.read_value(), 1.)52 def testShape(self):53 v = self.create_variable([1.])54 self.assertEqual(v.shape, (1,))55 self.assertEqual(v.get_shape(), (1,))56 v.set_shape((1,))57 with self.assertRaisesRegex(ValueError, "not compatible"):58 v.set_shape((1, 1))59 @combinations.generate(combinations.combine(trainable=[True, False]))60 def testTrainable(self, trainable):61 v = self.create_variable(trainable=trainable)62 self.assertEqual(v.trainable, trainable)63 @combinations.generate(64 combinations.combine(synchronization=[65 variables_lib.VariableSynchronization.ON_READ,66 variables_lib.VariableSynchronization.ON_WRITE,67 variables_lib.VariableSynchronization.AUTO,68 variables_lib.VariableSynchronization.NONE,69 ]))70 def testSynchronization(self, synchronization):71 v = self.create_variable(synchronization=synchronization)72 self.assertEqual(v.synchronization, synchronization)73 @combinations.generate(74 combinations.combine(aggregation=[75 variables_lib.VariableAggregation.MEAN,76 variables_lib.VariableAggregation.SUM,77 variables_lib.VariableAggregation.ONLY_FIRST_REPLICA,78 variables_lib.VariableAggregation.NONE,79 ]))80 def testAggregation(self, aggregation):81 v = self.create_variable(aggregation=aggregation)82 self.assertEqual(v.aggregation, aggregation)83 @combinations.generate(combinations.combine(mode="graph"))84 def testEval(self):85 v = self.create_variable(1.)86 with self.cached_session():87 self.evaluate(variables_lib.global_variables_initializer())88 self.assertEqual(v.eval(), 1.)89 def testInitialValueEager(self):90 v = self.create_variable(1.)91 with self.assertRaises(RuntimeError):92 v.initial_value # pylint: disable=pointless-statement93 @combinations.generate(combinations.combine(mode="graph"))94 def testInitialValueGraph(self):95 v = self.create_variable(1.)96 self.assertEqual(self.evaluate(v.initial_value), 1.)97 def testConstraint(self):98 v = self.create_variable(constraint=lambda x: x + 1.)99 self.assertEqual(v.constraint(1.), 2.)100 def testDenseUpdate(self):101 v = self.create_variable(1.)102 self.assertEqual(103 v.assign(2., use_locking=True, name="assign", read_value=True), 2.)104 self.assertIsNone(v.assign(3., read_value=False))105 self.assertEqual(v, 3.)106 self.assertEqual(107 v.assign_add(1., use_locking=True, name="assign_add", read_value=True),108 4.)109 self.assertIsNone(v.assign_add(1., read_value=False))110 self.assertEqual(v, 5.)111 self.assertEqual(112 v.assign_sub(1., use_locking=True, name="assign_sub", read_value=True),113 4.)114 self.assertIsNone(v.assign_sub(1., read_value=False))115 self.assertEqual(v, 3.)116 @def_function.function117 def f():118 self.assertIsInstance(v.assign(1., read_value=False), ops.Operation)119 self.assertIsInstance(v.assign_add(1., read_value=False), ops.Operation)120 self.assertIsInstance(v.assign_sub(1., read_value=False), ops.Operation)121 f()122 def testSparseUpdate(self):123 v = self.create_variable([0., 0., 0.])124 self.assertAllEqual(125 v.scatter_add(126 _make_index_slices(values=[1., 2.], indices=[0, 2]),127 use_locking=True,128 name="add"), [1., 0., 2.])129 self.assertAllEqual(130 v.scatter_div(131 _make_index_slices(values=[4., 2.], indices=[0, 2]),132 use_locking=True,133 name="div"), [0.25, 0., 1.])134 self.assertAllEqual(135 v.scatter_max(136 _make_index_slices(values=[1., 0.5], indices=[1, 2]),137 use_locking=True,138 name="max"), [0.25, 1., 1.])139 self.assertAllEqual(140 v.scatter_min(141 _make_index_slices(values=[1., 0.5], indices=[0, 1]),142 use_locking=True,143 name="min"), [0.25, 0.5, 1.])144 self.assertAllEqual(145 v.scatter_mul(146 _make_index_slices(values=[2., 0.5], indices=[0, 1]),147 use_locking=True,148 name="mul"), [0.5, 0.25, 1.])149 self.assertAllEqual(150 v.scatter_sub(151 _make_index_slices(values=[2., 0.5], indices=[0, 1]),152 use_locking=True,153 name="sub"), [-1.5, -0.25, 1.])154 self.assertAllEqual(155 v.scatter_update(156 _make_index_slices(values=[2., 0.5], indices=[0, 1]),157 use_locking=True,158 name="update"), [2., 0.5, 1.])159 self.assertAllEqual(160 v.batch_scatter_update(161 _make_index_slices(values=[1., 1.5], indices=[0, 1]),162 use_locking=True,163 name="update"), [1., 1.5, 1.])164 def testSparseNdUpdate(self):165 v = self.create_variable([0., 0., 0., 0.])166 self.assertAllEqual(167 v.scatter_nd_sub([[3], [1]], [1., 2.], name="sub"), [0., -2., 0., -1.])168 self.assertAllEqual(169 v.scatter_nd_add([[2], [0]], [1., 2.], name="add"), [2., -2., 1., -1.])170 self.assertAllEqual(171 v.scatter_nd_update([[1], [3]], [3., 3.], name="update"),172 [2., 3., 1., 3.])173 def testSparseRead(self):174 v = self.create_variable([[1., 2.], [3., 4.]])175 self.assertAllEqual(176 v.sparse_read([1, 0], name="read"), [[3., 4.], [1., 2.]])177 self.assertAllEqual(178 v.gather_nd([[1, 0], [0, 1]], name="gather_nd"), [3., 2.])179 def testTensorConversion(self):180 v = self.create_variable([1.])181 self.assertEqual(ops.convert_to_tensor(v), [1.])182 def testHash(self):183 v = self.create_variable()184 w = self.create_variable()185 d = {}186 with self.assertRaises(TypeError):187 d[v] = 1188 d[v.ref()] = 1189 self.assertEqual(d[v.ref()], 1)190 self.assertNotIn(w.ref(), d)191 @combinations.generate(combinations.combine(mode="graph"))192 def testHashGraph(self):193 v = self.create_variable()194 w = self.create_variable()195 d = {v: 1}196 self.assertEqual(d[v], 1)197 self.assertNotIn(w, d)198 def testEquality(self):199 v = self.create_variable(1.)200 w = self.create_variable(2.)201 x = self.create_variable(1.)202 self.assertEqual(v, x)203 self.assertNotEqual(v, w)204 @combinations.generate(combinations.combine(mode="graph"))205 def testEqualityGraph(self):206 # In legacy graph mode, tensor equality is object equality207 v = self.create_variable(1.)208 w = self.create_variable(1.)209 self.assertNotEqual(v, w)210 self.assertEqual(v, v)211 def testIteration(self):212 v = self.create_variable([1.])213 self.assertEqual([1.], list(iter(v)))214 def testProperties(self):215 v = self.create_variable()216 self.assertIsInstance(v.name, str)217 # _shared_name is also part of the interface. E.g. it's used in optimizer to218 # determine slot variable key.219 self.assertIsInstance(v._shared_name, str)220 self.assertIsNone(v.initializer)221 self.assertIsInstance(v.device, str)222 self.assertEqual(v.dtype, dtypes.float32)223 with self.assertRaises(AttributeError):224 v.op # pylint: disable=pointless-statement225 with self.assertRaises(AttributeError):226 v.graph # pylint: disable=pointless-statement227 @combinations.generate(combinations.combine(mode="graph"))228 def testPropertiesGraph(self):229 v = self.create_variable()230 self.assertIsInstance(v.initializer, ops.Operation)231 self.assertIsInstance(v.op, ops.Operation)232 self.assertIsInstance(v.graph, ops.Graph)233 def testProtoConversion(self):234 # to_proto and from_proto are not supported.235 v = self.create_variable([1, 2])236 with self.assertRaises(TypeError):237 v.to_proto()238 with self.assertRaises(TypeError):239 v.from_proto(variable_def=None)240 def testSaveSliceInfo(self):241 v = self.create_variable()242 slice_info = variables_lib.Variable.SaveSliceInfo()243 v._set_save_slice_info(slice_info)244 self.assertIs(v._get_save_slice_info(), slice_info)245 # Some code accesses _save_slice_info directly without using the getter.246 self.assertIs(v._save_slice_info, slice_info)247 def testOperatorOverride(self):248 v = self.create_variable(7)249 self.assertEqual(v + 1, 8)250 self.assertEqual(3 + v, 10)251 self.assertEqual(v + v, 14)252 self.assertEqual(v - 2, 5)253 self.assertEqual(13 - v, 6)254 self.assertEqual(v - v, 0)255 self.assertEqual(v * 2, 14)256 self.assertEqual(3 * v, 21)257 self.assertEqual(v * v, 49)258 self.assertEqual(v / 2, 3.5)259 self.assertEqual(14 / v, 2.)260 self.assertEqual(v // 2, 3)261 self.assertEqual(15 // v, 2)262 self.assertEqual(v % 2, 1)263 self.assertEqual(16 % v, 2)264 # pylint: disable=g-generic-assert265 self.assertTrue(v < 12)266 self.assertTrue(v <= 12)267 self.assertFalse(v > 12)268 self.assertFalse(v >= 12)269 self.assertFalse(12 < v)270 self.assertFalse(12 <= v)271 self.assertTrue(12 > v)272 self.assertTrue(12 >= v)273 # pylint: enable=g-generic-assert274 self.assertEqual(v & 3, 3)275 self.assertEqual(11 & v, 3)276 self.assertEqual(v | 8, 15)277 self.assertEqual(16 | v, 23)278 self.assertEqual(v ^ 3, 4)279 self.assertEqual(11 ^ v, 12)280 self.assertEqual(pow(v, 3), 343)281 # TODO(b/178748613): pow(v, 3, 10) fails.282 self.assertEqual(pow(2, v), 128)283 self.assertEqual(-v, -7)284 self.assertEqual(~v, ~7)285 self.assertEqual(abs(v), 7)286 def testSlice(self):287 v = self.create_variable([1., 2., 3.])288 self.assertEqual(v[1], 2.)289 v[2].assign(4.)290 self.assertAllEqual(v, [1., 2., 4.])291 # ==== End Variable interface ===292 # ==== Begin ResourceVariable interface ===293 def testHandle(self):294 v = self.create_variable()295 self.assertIsInstance(v.handle, ops.Tensor)296 self.assertEqual(v.handle.dtype, dtypes.resource)297 def testInGraphMode(self):298 # This is protected but used in a lot of places internally.299 v = self.create_variable()300 self.assertFalse(v._in_graph_mode)301 def testUniqueId(self):302 # This is used in optimizer as part of slot variable key.303 v = self.create_variable()304 w = self.create_variable()305 self.assertNotEqual(v._unique_id, w._unique_id)306 def testIsResourceVariable(self):307 v = self.create_variable()308 self.assertTrue(resource_variable_ops.is_resource_variable(v))309 # ==== End ResourceVariable interface ===310 @combinations.generate(combinations.combine(mode="graph"))311 def testAsGraphElement(self):312 g = ops.Graph()313 with g.as_default():314 v = self.create_variable(1.)315 g.finalize()316 self.evaluate(v.initializer)317 # _as_graph_element shouldn't create new operations.318 self.assertEqual(self.evaluate(v._as_graph_element()), 1.)319class DistributedVariableInterfaceTest(_VariableInterfaceTestBase):320 def create_variable(self, initial_value=1., **kwargs):321 variables = []322 for device in self.devices:323 with ops.device(device):324 variables.append(325 variables_lib.Variable(initial_value, **kwargs))326 return values_v2.DistributedVariable(variables)327# Prevent the base class from running.328del _VariableInterfaceTestBase329@combinations.generate(330 combinations.combine(331 strategy=[332 strategy_combinations.tpu_strategy,333 strategy_combinations.mirrored_strategy_with_two_cpus,334 strategy_combinations.mirrored_strategy_with_two_gpus,335 ],336 enable_packed_handle=[True, False],337 tf_function=[combinations.tf_function, combinations.no_tf_function]))338class DistributedVariableTest(test.TestCase, parameterized.TestCase):339 def create_variable(self, strategy, initial_value, enable_packed_handle,340 **kwargs):341 variables = []342 for device in strategy.extended.parameter_devices:343 with ops.device(device):344 variables.append(variables_lib.Variable(initial_value, **kwargs))345 return values_v2.DistributedVariable(346 variables, enable_packed_handle=enable_packed_handle)347 def assertReplica(self, distributed_var, values):348 for var, value in zip(distributed_var._variables, values):349 self.assertAllEqual(var, value)350 def testRead(self, strategy, enable_packed_handle, tf_function):351 v = self.create_variable(strategy, 0., enable_packed_handle)352 with ops.device(strategy.extended.parameter_devices[0]):353 v.assign(1.)354 with ops.device(strategy.extended.parameter_devices[1]):355 v.assign(2.)356 @tf_function357 def read_device0():358 with ops.device(strategy.extended.parameter_devices[0]):359 return v.read_value(), v.value()360 @tf_function361 def read_device1():362 with ops.device(strategy.extended.parameter_devices[1]):363 return v.read_value(), v.value()364 @tf_function365 def read_other_device():366 with ops.device("CPU:0"):367 return v.read_value(), v.value()368 self.assertAllEqual(read_device0(), [1., 1.])369 self.assertAllEqual(read_device1(), [2., 2.])370 self.assertAllEqual(read_other_device(), [1., 1.])371 def testAssign(self, strategy, enable_packed_handle, tf_function):372 v = self.create_variable(strategy, 0., enable_packed_handle)373 @tf_function374 def update_device0():375 with ops.device(strategy.extended.parameter_devices[0]):376 v.assign(1.)377 @tf_function378 def update_device1():379 with ops.device(strategy.extended.parameter_devices[1]):380 v.assign(2.)381 update_device0()382 update_device1()383 self.assertReplica(v, [1., 2.])384 with ops.device("CPU:0"):385 # Update the primary replica.386 v.assign(3.)387 self.assertReplica(v, [3., 2.])388 def testStrategyRun(self, strategy, enable_packed_handle, tf_function):389 if (test_util.is_tpu_strategy(strategy) and390 tf_function is combinations.no_tf_function):391 self.skipTest("tpu doesn't support eager")392 v = self.create_variable(strategy, 0., enable_packed_handle)393 @tf_function394 def update(per_replica):395 v.assign(per_replica)396 @tf_function397 def read():398 return v.read_value()399 strategy.run(400 update, args=(test_util.create_per_replica(strategy, [1., 2.]),))401 self.assertReplica(v, [1., 2.])402 self.assertAllEqual(403 test_util.gather(strategy, strategy.run(read)), [1., 2.])404def _make_index_slices(values, indices, dense_shape=None):405 if dense_shape:406 dense_shape = array_ops.identity(dense_shape)...
zebra.py
Source:zebra.py
...191 variable.set_domain(domain)192 solution = reduced_problem.domain_splitting() #recursive call193 if solution: #if the solution is None (cf base case 1), this is False194 return solution195def create_variable(name, id):196 return Variable(name, id, Domain([1, 2, 3, 4, 5]))197#create variables198country1 = "Spain"199country2 = "Ukraine"200country3 = "Japan"201country4 = "Norway"202country5 = "England"203norvegian = create_variable("Norvegian", country4)204spaniard = create_variable("Spain", country1)205englishdude = create_variable("England", country5)206ukrainian = create_variable("Ukraine", country2)207japanese = create_variable("Japan", country3)208country_list = [norvegian, spaniard, englishdude, ukrainian, japanese]209color1 = "blue"210color2 = "green"211color3 = "ivory"212color4 = "red"213color5 = "yellow"214blue = create_variable("blue", color1)215green = create_variable("green", color2)216ivory = create_variable("ivory", color3)217red = create_variable("red", color4)218yellow = create_variable("yellow", color5)219color_list = [blue, green, ivory, red, yellow]220pet1 = "dog"221pet2 = "snails"222pet3 = "fox"223pet4 = "horse"224pet5 = "zebra"225dog = create_variable("dog", pet1)226snail = create_variable("snails", pet2)227fox = create_variable("fox", pet3)228horse = create_variable("horse", pet4)229zebra = create_variable("zebra", pet5)230pet_list = [dog, snail, fox, horse, zebra]231bev1 = "coffee"232bev2 = "milk"233bev3 = "tea"234bev4 = "orange"235bev5 = "water"236coffee = create_variable("coffee", bev1)237milk = create_variable("milk", bev2)238tea = create_variable("tea", bev3)239orange = create_variable("orange", bev4)240water = create_variable("water", bev5)241bev_list = [coffee, milk, tea, orange, water]242game1 = 'Snakes and Ladders'243game2 = 'Cluedo'244game3 = 'Pictionary'245game4 = 'Travel the World'246game5 = 'Backgammon'247snakes_and_ladders = create_variable("Snakes and Ladders", game1)248cluedo = create_variable("Cluedo", game2)249pictionary = create_variable("Pictionary", game3)250travel_the_world = create_variable("Travel the World", game4)251backgammon = create_variable("Backgammon", game5)252game_list = [snakes_and_ladders, cluedo, pictionary, travel_the_world, backgammon]253#create constraints254constraint_list = [Constraint_equality_var_var(englishdude, red),255 Constraint_equality_var_var(spaniard, dog),256 Constraint_equality_var_var(coffee, green),257 Constraint_equality_var_var(ukrainian, tea),258 Constraint_equality_var_plus_cons(green, ivory, 1),259 Constraint_equality_var_var(snakes_and_ladders, snail),260 Constraint_equality_var_var(cluedo, yellow),261 Constraint_equality_var_cons(milk, 3),262 Constraint_equality_var_cons(norvegian, 1),263 Constraint_equality_plus_minus_cons(pictionary, fox, 1),264 Constraint_equality_plus_minus_cons(cluedo, horse, 1),265 Constraint_equality_var_var(travel_the_world, orange),...
Output.py
Source:Output.py
...138 # Append priors139 append_variables(priors, dataset)140 # Append river type as NA and assign fill value to invalid reaches141 if not valid:142 create_variable(dataset["node"], "river_type", "Brinkerhoff_class_number", "NA", priors["river_type"])143 dataset["reach/Qhat"].assignValue(Output.FILL_VALUE)144 dataset["reach/Qsd"].assignValue(Output.FILL_VALUE)145 else:146 # Create nx dimension and coordinate variable and append vector 147 create_nx(np.shape(priors["river_type"]), dataset)148 append_river_type(priors, dataset)149 # Set global attribute flag for validity150 dataset.valid = np.uint32(1) if valid else np.uint32(0)151 # Close NetCDF4 dataset152 dataset.close()153def append_variables(priors, dataset):154 """ Appends NetCDF4 variables for geoBAM priors to reach group."""155 # Retrieve reach group156 reach_grp = dataset["reach"]157 # Create variables for each prior158 create_variable(reach_grp, "lowerbound_A0", "Median_area_min", "m^2", priors["lowerbound_A0"])159 create_variable(reach_grp, "upperbound_A0", "Median_area_max", "m^2", priors["upperbound_A0"])160 create_variable(reach_grp, "lowerbound_logn", "Mannings_n_min", "NA", priors["lowerbound_logn"])161 create_variable(reach_grp, "upperbound_logn", "Mannings_n_max", "NA", priors["upperbound_logn"])162 create_variable(reach_grp, "lowerbound_b", "AHG_b_min", "NA", priors["lowerbound_b"])163 create_variable(reach_grp, "upperbound_b", "AHG_b_max", "NA", priors["upperbound_b"])164 create_variable(reach_grp, "lowerbound_logWb", "Bankfull_width_min", "m", priors["lowerbound_logWb"])165 create_variable(reach_grp, "upperbound_logWb", "Bankfull_width_max", "m", priors["upperbound_logWb"])166 create_variable(reach_grp, "lowerbound_logDb", "Bankfull_depth_min", "m", priors["lowerbound_logDb"])167 create_variable(reach_grp, "upperbound_logDb", "Bankfull_depth_max", "m", priors["upperbound_logDb"])168 create_variable(reach_grp, "lowerbound_logr", "Dingman_shape_min", "NA", priors["lowerbound_logr"])169 create_variable(reach_grp, "upperbound_logr", "Dingman_shape_max", "NA", priors["upperbound_logr"])170 create_variable(reach_grp, "logA0_hat", "Median_area_mean", "m^2", priors["logA0_hat"])171 create_variable(reach_grp, "logn_hat", "Mannings_n_mean", "NA", priors["logn_hat"])172 create_variable(reach_grp, "b_hat", "AHG_b_mean", "NA", priors["b_hat"])173 create_variable(reach_grp, "logWb_hat", "Bankfull_width_mean", "m", priors["logWb_hat"])174 create_variable(reach_grp, "logDb_hat", "Bankfull_depth_mean", "m", priors["logDb_hat"])175 create_variable(reach_grp, "logr_hat", "Dingman_shape_mean", "NA", priors["logr_hat"])176 create_variable(reach_grp, "logA0_sd", "Median_area_sd", "m^2", priors["logA0_sd"])177 create_variable(reach_grp, "logn_sd", "Mannings_n_sd", "NA", priors["logn_sd"])178 create_variable(reach_grp, "b_sd", "AHG_b_sd", "NA", priors["b_sd"])179 create_variable(reach_grp, "logWb_sd", "Bankfull_width_sd", "m", priors["logWb_sd"])180 create_variable(reach_grp, "logDb_sd", "Bankfull_depth_sd", "m", priors["logDb_sd"])181 create_variable(reach_grp, "logr_sd", "Dingman_shape_sd", "NA", priors["logr_sd"])182 create_variable(reach_grp, "lowerbound_logQ", "Discharge_min", "m^3/s", priors["lowerbound_logQ"])183 create_variable(reach_grp, "upperbound_logQ", "Discharge_max", "m^3/s", priors["upperbound_logQ"])184 create_variable(reach_grp, "lowerbound_logWc", "AMHG_wc_min", "m", priors["lowerbound_logWc"])185 create_variable(reach_grp, "upperbound_logWc", "AMHG_wc_min", "m", priors["upperbound_logWc"])186 create_variable(reach_grp, "lowerbound_logQc", "AMHG_Qc_min", "m^3/s", priors["lowerbound_logQc"])187 create_variable(reach_grp, "upperbound_logQc", "AMHG_Qc_max", "m^3/s", priors["upperbound_logQc"])188 create_variable(reach_grp, "logWc_hat", "AMHG_wc_mean", "m", priors["logWc_hat"])189 create_variable(reach_grp, "logQc_hat", "AMHG_Qc_mean", "m^3/s", priors["logQc_hat"])190 create_variable(reach_grp, "logQ_sd", "Discharge_sd", "m^3/s", priors["logQ_sd"])191 create_variable(reach_grp, "logWc_sd", "AMHG_wc_sd", "m", priors["logWc_sd"])192 create_variable(reach_grp, "logQc_sd", "AMHG_qc_min", "m^3/s", priors["logQc_sd"])193 create_variable(reach_grp, "Werr_sd", "Width_measurement_error", "m", priors["Werr_sd"])194 create_variable(reach_grp, "Serr_sd", "Slope_measurement_error", "m/m", priors["Serr_sd"])195 create_variable(reach_grp, "dAerr_sd", "d_Area_measurement_error", "m", priors["dAerr_sd"])196 create_variable(reach_grp, "sigma_man", "Manning_structural_error", "NA", priors["sigma_man"])197 create_variable(reach_grp, "sigma_amhg", "AMHG_structural_error", "NA", priors["sigma_amhg"])198def create_variable(group, name, long_name, units, value):199 """Create NetCDF4 variable and assign data to it."""200 netcdf_var = group.createVariable(name, "f8", fill_value = Output.FILL_VALUE)201 netcdf_var.long_name = long_name202 netcdf_var.units = units203 if np.isnan(value) or value is rinterface.NA_Integer or value is rinterface.NA_Logical:204 value = Output.FILL_VALUE205 netcdf_var.assignValue(value)206def create_nx(length, dataset):207 """Create node dimension and coordinate variable."""208 209 dataset.createDimension("nx", length[0])210 nx = dataset.createVariable("nx", "i4", ("nx",))211 nx.units = "node"212 nx.long_name = "nx"...
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