Functions — github.com/Litianyu141/Finite-Volume-Graph-Network

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Functions256 in github.com/Litianyu141/Finite-Volume-Graph-Network

⨍ Functions 256◇ Types & classes 28

↓ 1 callersMethodsave_checkpoint

( self, path=None, optimizer=None, scheduler=None, trian_time_steps: n

FVGN-src/main/FVGN_model/FVGN.py:376

↓ 1 callersMethodsave_state

saves state of model and optimizer :model: model to save (if list: save multiple models) :optimizer: optimizer (if list: save

FVGN-src/main/utils/Logger.py:190

↓ 1 callersFunctionseprate_cells

(mesh_pos, cells, node_type, density, pressure, velocity, index)

FVGN-src/main/Extract_mesh/parse_tfrecord_refactor.py:1153

↓ 1 callersFunctionserialize_example

MGN-src/main/run_model.py:90

↓ 1 callersFunctionsplit_dataset

(dataset_path, no_split_dataset=True)

FVGN-src/main/Extract_mesh/parse_comsol.py:400

↓ 1 callersFunctionstastic

MGN-src/main/meshgraphnets/parse_tfrecord_refactor.py:271

↓ 1 callersFunctionstastic_nodeface_type

MGN-src/main/meshgraphnets/parse_tfrecord_refactor.py:243

↓ 1 callersMethodstep_ReduceLROnPlateau

(self, metrics, epoch=None)

FVGN-src/main/utils/scheduler.py:93

↓ 1 callersMethodtrain_datapreprocessing

(self, graph_list, dual_edge=False)

FVGN-src/main/dataset/Load_mesh.py:983

↓ 1 callersFunctiontransform_to_cell_center_traj

(trajectory,cylinder_node_mask,cylinder_face_mask,cylinder_cell_mask,rollout_index)

MGN-src/main/meshgraphnets/parse_tfrecord_refactor.py:709

↓ 1 callersFunctiontriangles_to_faces

Computes mesh edges from triangles.

FVGN-src/main/utils/write_tec.py:38

↓ 1 callersFunctiontriangles_to_faces

Computes mesh edges from triangles.

MGN-src/main/meshgraphnets/parse_tfrecord_refactor.py:1098

↓ 1 callersFunctionvalidate_loop

( fluid_model=None, validation_datasets=None, params=None, training_round=None, logger=Non

FVGN-src/main/validate.py:45

↓ 1 callersMethodvelocity_to_accelation

(self, noised_frames, next_cell_attr)

FVGN-src/main/FVGN_model/FVGN.py:142

↓ 1 callersFunctionwrite_cell_index

(Cells, writer)

FVGN-src/main/utils/write_tec.py:169

↓ 1 callersFunctionwrite_tecplot_ascii_nodal

(raw_data, is_tfrecord, pkl_path, saving_path)

FVGN-src/main/utils/write_tec.py:318

↓ 1 callersFunctionwrite_tfrecord_mp

(tfrecord_path_1,tfrecord_path_2,records)

MGN-src/main/meshgraphnets/parse_tfrecord_refactor.py:435

↓ 1 callersFunctionwrite_tfrecord_one_with_writer

(writer, records, mode)

FVGN-src/main/Extract_mesh/parse_tfrecord_refactor.py:293

↓ 1 callersFunctionwrite_tfrecord_one_with_writer

(writer,records,mode)

MGN-src/main/meshgraphnets/parse_tfrecord_refactor.py:423

( self, optimizer, multiplier, milestone: list, gamma, after_s

FVGN-src/main/utils/scheduler.py:19

( self, optimizer, decay_steps=10000, gamma=0.4, min_lr=1e-7, last_epoch=-1 )

FVGN-src/main/utils/scheduler.py:149

( self, optimizer, start_lr, drop_lr, total_epochs, gamma,

FVGN-src/main/utils/scheduler.py:179

Logger logs metrics to CSV files / tensorboard :name: logging name (e.g. model name / dataset name / ...) :datetime: date and

FVGN-src/main/utils/Logger.py:18

Online normalization module size: feature dimension max_accumulation: maximum number of batches epsilon: std cutoff

FVGN-src/main/utils/normalization.py:6

( self, mesh_file, data_file, tf_writer=None, h5_writer=None,

FVGN-src/main/Extract_mesh/parse_comsol.py:22

( self, params, path, split, description=description, max_epoc

FVGN-src/main/dataset/Load_mesh.py:66

( self, params, path, split, description=description, max_epoc

FVGN-src/main/dataset/Load_mesh.py:207

( self, hidden_size=128, drop_out=False, mp_times=2, MultiHead=1,

FVGN-src/main/FVGN_model/EncoderProcesserDecoder.py:81

( self, edge_hidden_size=128, cell_hidden_size=128, edge_output_size=7,

FVGN-src/main/FVGN_model/EncoderProcesserDecoder.py:129

( self, message_passing_num, cell_input_size, edge_input_size, cell_ou

FVGN-src/main/FVGN_model/EncoderProcesserDecoder.py:174

( self, edge_input_size=7, cell_input_size=2, cell_output_size=2, loss_cont=0 )

FVGN-src/main/FVGN_model/EncoderProcesserDecoder.py:242

( self, input_size, attention_size, mp_times=2, MultiHead=1, c

FVGN-src/main/FVGN_model/GN_blocks.py:59

(self, device=None, model_dir=None, params=None)

FVGN-src/main/FVGN_model/FVGN.py:19

(self, learned_model, dual_edge, name='Model')

MGN-src/main/meshgraphnets/cfd_model.py:30

(self, learned_model, name='Model')

MGN-src/main/meshgraphnets/cloth_model.py:30

( self, output_size, latent_size, num_layers, message_passing_steps,

MGN-src/main/meshgraphnets/core_model.py:97

(self, size, max_accumulations=10**6, std_epsilon=1e-8, name='Normalizer')

MGN-src/main/meshgraphnets/normalization.py:26

FVGN-src/main/dataset/Load_mesh.py:97

MGN-src/main/meshgraphnets/cfd_model.py:66

MGN-src/main/meshgraphnets/cloth_model.py:69

Applies GraphNetBlock and returns updated MultiGraph.

MGN-src/main/meshgraphnets/core_model.py:71

Encodes and processes a multigraph, and returns node features.

MGN-src/main/meshgraphnets/core_model.py:137

Normalizes input data and accumulates statistics.

MGN-src/main/meshgraphnets/normalization.py:39

Method_build_graph

FVGN-src/main/dataset/Load_mesh.py:282

Function_bytes_feature

Returns a bytes_list from a string / byte.

FVGN-src/main/Extract_mesh/parse_tfrecord_refactor.py:258

Function_bytes_feature

Returns a bytes_list from a string / byte.

MGN-src/main/meshgraphnets/parse_tfrecord_refactor.py:342

Method_debug_time_steps

FVGN-src/main/dataset/Load_mesh.py:448

Function_float_feature

Returns a float_list from a float / double.

FVGN-src/main/Extract_mesh/parse_tfrecord_refactor.py:265

Function_float_feature

Returns a float_list from a float / double.

MGN-src/main/meshgraphnets/parse_tfrecord_refactor.py:348

Function_int64_feature

Returns an int64_list from a bool / enum / int / uint.

FVGN-src/main/Extract_mesh/parse_tfrecord_refactor.py:270

Function_int64_feature

Returns an int64_list from a bool / enum / int / uint.

MGN-src/main/meshgraphnets/parse_tfrecord_refactor.py:352

Parses a trajectory from tf.Example.

FVGN-src/main/Extract_mesh/parse_tfrecord_refactor.py:78

Parses a trajectory from tf.Example.

MGN-src/main/meshgraphnets/dataset.py:28

Parses a trajectory from tf.Example.

MGN-src/main/meshgraphnets/parse_tfrecord_refactor.py:206

Method_set_epoch

FVGN-src/main/dataset/Load_mesh.py:398

Method_set_fetch_time_steps

FVGN-src/main/dataset/Load_mesh.py:401

Method_set_time_step_list

(self, new_time_step_list: np.ndarray)

FVGN-src/main/dataset/Load_mesh.py:407

Functionadd_noise

MGN-src/main/meshgraphnets/dataset.py:75

Functionadd_targets

Adds target and optionally history fields to dataframe.

MGN-src/main/meshgraphnets/dataset.py:59

Functionanimate

FVGN-src/main/Extract_mesh/parse_tfrecord_refactor.py:1893

Functionanimate

MGN-src/main/meshgraphnets/plot_cloth.py:48

Functionanimate

MGN-src/main/meshgraphnets/plot_cfd.py:47

Functionanimate

MGN-src/main/meshgraphnets/parse_tfrecord_refactor.py:1320

Functionbatch_accumulate

MGN-src/main/meshgraphnets/dataset.py:101

Functionbatch_dataset

Batches input datasets.

MGN-src/main/meshgraphnets/dataset.py:92

Functioncalc_edge_unv

(edge_index, mesh_pos, centroid)

FVGN-src/main/utils/write_tec.py:467

(self, batch_list)

FVGN-src/main/dataset/Load_mesh.py:234

(self, batch_list)

FVGN-src/main/dataset/Load_mesh.py:697

Functioncollate_fn

FVGN-src/main/dataset/Load_mesh.py:1149

Functionconvert_to_tensors

FVGN-src/main/Extract_mesh/parse_tfrecord_refactor.py:331

Functiondirect_decode_loss

( params, graph_cell, graph_edge, mask_face_interior, predicted_edge_attr, target_face

FVGN-src/main/utils/loss_compute.py:5

Functiondirection_bias

FVGN-src/main/Extract_mesh/parse_tfrecord_refactor.py:1545

Functiondirection_bias

MGN-src/main/meshgraphnets/parse_tfrecord_refactor.py:1173

Methodenforce_boundary_condition

( self, predicted_cell_attr=None, bc=None, edge_neighbour_index=None,

FVGN-src/main/dataset/Load_mesh.py:816

Functionevaluate

Performs model rollouts and create stats.

MGN-src/main/meshgraphnets/cloth_eval.py:46

Functionevaluate

Performs model rollouts and create stats.

MGN-src/main/meshgraphnets/cfd_eval.py:49

Functionfind_max_distance

FVGN-src/main/Extract_mesh/parse_tfrecord_refactor.py:1025

Functionfind_pos

(mesh_point, mesh_pos_sp1)

FVGN-src/main/Extract_mesh/parse_tfrecord_refactor.py:323

Functionfind_pos

(mesh_point,mesh_pos_sp1)

MGN-src/main/meshgraphnets/parse_tfrecord_refactor.py:451

MGN-src/main/meshgraphnets/dataset.py:61

FVGN-src/main/utils/scheduler.py:244

Updates mean/standard deviation and normalizes input data batched_data: batch of data accumulate: if True, update accumulati

FVGN-src/main/utils/normalization.py:33

FVGN-src/main/FVGN_model/EncoderProcesserDecoder.py:65

(self, graph, graph_node)

FVGN-src/main/FVGN_model/EncoderProcesserDecoder.py:112

(self, graph=None, features=None, cell_features=None)

FVGN-src/main/FVGN_model/EncoderProcesserDecoder.py:161

(self, graph, graph_node)

FVGN-src/main/FVGN_model/EncoderProcesserDecoder.py:224

( self, uv_face=0, p_face=0, flux_D=0, unv=None, rho=None,

FVGN-src/main/FVGN_model/EncoderProcesserDecoder.py:251

FVGN-src/main/FVGN_model/GN_blocks.py:16

(self, graph, graph_node)

FVGN-src/main/FVGN_model/GN_blocks.py:78

( self, graph: Data = None, graph_edge: Data = None, graph_node: Data = None,

FVGN-src/main/FVGN_model/FVGN.py:147

FVGN-src/main/utils/scheduler.py:65

FVGN-src/main/utils/scheduler.py:169

FVGN-src/main/utils/scheduler.py:196

Functionget_noise_on_edge

(graph, noise_std, outchannel, device)

FVGN-src/main/utils/noise.py:29

Functionget_v_noise_on_cell

(graph, noise_std, outchannel, device)

FVGN-src/main/utils/noise.py:13

Functionget_v_noise_on_node

(graph, noise_std, outchannel, device)

FVGN-src/main/utils/noise.py:44

Methodignore_files_and_folders

(self, dir_name, names)

FVGN-src/main/utils/Logger.py:70

Functionis_between

Determine if a value x is between two other values a and b. Parameters: - a (float or int): The lower bound. - b (float or int): The

FVGN-src/main/Extract_mesh/parse_tfrecord_refactor.py:1938

FVGN-src/main/dataset/Load_mesh.py:464

Functionload_dataset

MGN-src/main/meshgraphnets/dataset.py:49

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