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Contents:

  • HamGNN User Guide
    • HamGNN Introduction
      • Key Features
      • Application Areas
      • Latest Developments
    • Environment Configuration and Installation
      • Python Environment
      • Third-party DFT Tool Support
        • OpenMX
        • SIESTA/HONPAS
        • ABACUS
        • Compiling openmx_postprocess and read_openmx
      • HamGNN Installation Steps
        • Step One: Install Conda Environment
        • Step Two: Source Installation of HamGNN
    • Construction of graph_data.npz File
      • General Process
      • OpenMX Process
      • SIESTA/HONPAS Process
      • ABACUS Process
    • Model Training Process
      • Training Mode Classification
      • Training Command
      • Key Configuration Items
      • Training Monitoring
    • Model Prediction Operation
      • Preparation for Prediction
      • Execute Prediction
      • Output Results
    • Band Structure Calculation
      • Operation Process
      • Band Calculation for Large Systems
    • Uni-HamGNN Universal Model
      • Model Introduction
      • Input Requirements
      • Usage Process
      • Output Results
    • HamGNN Parameter Details
      • setup (Basic Settings)
      • profiler_params (Profiler Parameters)
      • dataset_params (Dataset Parameters)
      • losses_metrics (Loss Functions and Evaluation Metrics)
      • optim_params (Optimizer Parameters)
      • output_nets.HamGNN_out (Output Network Parameters)
      • representation_nets.HamGNN_pre (Representation Network Parameters)
      • Parameter Adjustment Recommendations
        • References
  • Model Structure
    • Base Model
      • get_radii_from_atomic_numbers()
      • neighbor_list_and_relative_vec()
      • find_matching_columns_of_A_in_B()
      • BaseModel
        • BaseModel.forward()
        • BaseModel.generate_graph()
        • BaseModel.num_params
    • HamGNN Convolution
      • LayerCheckpointModule
        • LayerCheckpointModule.forward()
      • HamGNNConvE3
        • HamGNNConvE3.forward()
    • HamGNN Transformer
      • HamGNNTransformer
        • HamGNNTransformer.forward()
    • HamGNN Output Head
      • HamLayer
        • HamLayer.forward()
      • HamGNNPlusPlusOut
        • HamGNNPlusPlusOut.merge_tensor_components()
        • HamGNNPlusPlusOut.merge_rank2_tensor_components()
        • HamGNNPlusPlusOut.merge_rank0_tensor_components()
        • HamGNNPlusPlusOut.construct_j_coupling_matrix()
        • HamGNNPlusPlusOut.construct_k_coupling_matrix()
        • HamGNNPlusPlusOut.reorder_matrix()
        • HamGNNPlusPlusOut.construct_molecular_hamiltonian()
        • HamGNNPlusPlusOut.concatenate_hamiltonians_by_crystal()
        • HamGNNPlusPlusOut.symmetrize_hamiltonian()
        • HamGNNPlusPlusOut.symmetrize_onsite_hamiltonian()
        • HamGNNPlusPlusOut.symmetrize_offsite_hamiltonian()
        • HamGNNPlusPlusOut.symmetrize_onsite_hamiltonian_soc()
        • HamGNNPlusPlusOut.symmetrize_offsite_hamiltonian_soc()
        • HamGNNPlusPlusOut.calculate_band_energies_with_overlap()
        • HamGNNPlusPlusOut.calculate_band_energies()
        • HamGNNPlusPlusOut.calculate_band_energies_with_spin_orbit_coupling()
        • HamGNNPlusPlusOut.apply_orbital_masks_to_hamiltonians()
        • HamGNNPlusPlusOut.symmetrize_orbital_coefficients()
        • HamGNNPlusPlusOut.create_cell_index_mapping()
        • HamGNNPlusPlusOut.extract_unique_cell_vectors()
        • HamGNNPlusPlusOut.build_edge_lookup_structures()
        • HamGNNPlusPlusOut.create_orbital_validity_mask()
        • HamGNNPlusPlusOut.build_interaction_masks()
        • HamGNNPlusPlusOut.build_column_wise_interaction_masks()
        • HamGNNPlusPlusOut.build_spin_orbit_interaction_masks()
        • HamGNNPlusPlusOut.calculate_sparsity_ratio()
        • HamGNNPlusPlusOut.validate_elements_in_basis_def()
        • HamGNNPlusPlusOut.forward()
    • Main Model Implementation
      • Model
        • Model.calculate_loss()
        • Model.training_step()
        • Model.validation_step()
        • Model.validation_epoch_end()
        • Model.test_step()
        • Model.test_epoch_end()
        • Model.forward()
        • Model.log_metrics()
        • Model.configure_optimizers()
  • GNN Core Layers
    • Message Passing
      • Message Pack Blocks
        • MessagePackBlock
        • MessagePackBlockV2
    • Attention Mechanisms
      • Attention Layers
        • AttentionAggregationV2
        • AttentionAggregation
        • AttentionBlockE3
      • Attention Utilities
        • VectorToAttentionHeads
        • AttentionHeadsToVector
    • Convolution Layers
      • Graph Convolution Operations
        • ConvBlockE3
    • Tensor Operations
      • Tensor Products
        • LinearScaleWithWeights
        • TensorProductWithMemoryOptimizationWithWeight
        • TensorProductWithScalarComponents
        • ConcatenatedIrrepsTensorProduct
    • Interaction Blocks
      • Neural Network Interaction Components
        • PairInteractionBlock
        • CorrProductBlock
        • ResidualBlock
    • Physics Tools
      • Clebsch-Gordan Coefficients
        • ClebschGordanCoefficients
      • K-Points
        • kpoints_generator
        • compute_reciprocal_lattice_vectors()
        • generate_kpoint_grid()
      • Matrix Operations
        • HamLayer
        • TensorExpansion
        • OverlapExpand
        • TensorMerge
  • Model Components
    • Embeddings
      • RadialBasisEdgeEncoding
        • RadialBasisEdgeEncoding.out_field
        • RadialBasisEdgeEncoding.forward()
      • EdgeScalarEmbedding
        • EdgeScalarEmbedding.forward()
      • LocalEnvironmentEmbedding
        • LocalEnvironmentEmbedding.forward()
      • PairInteractionEmbeddingBlock
        • PairInteractionEmbeddingBlock.create_linear()
        • PairInteractionEmbeddingBlock.create_tensor_product()
        • PairInteractionEmbeddingBlock.init_weight_generator()
        • PairInteractionEmbeddingBlock.forward()
      • Embedding
        • Embedding.reset_parameters()
        • Embedding.forward()
    • Electron Configurations
    • MLP Utilities
      • linear_bn_act()
      • denseLayer
        • denseLayer.forward()
      • Dense
        • Dense.reset_parameters()
        • Dense.forward()
    • Activation Functions
      • shifted_softplus()
      • switch_function()
      • softplus_inverse()
      • SoftUnitStepCutoff
        • SoftUnitStepCutoff.cutoff
        • SoftUnitStepCutoff.cut_param
        • SoftUnitStepCutoff.forward()
      • swish()
      • SSP
        • SSP.forward()
        • SSP.extra_repr()
      • SWISH
        • SWISH.forward()
      • get_activation()
    • Basis Functions
      • BernsteinRadialBasisFunctions
        • BernsteinRadialBasisFunctions.reset_parameters()
        • BernsteinRadialBasisFunctions.forward()
      • ExponentialBernsteinRadialBasisFunctions
        • ExponentialBernsteinRadialBasisFunctions.reset_parameters()
        • ExponentialBernsteinRadialBasisFunctions.forward()
      • ExponentialGaussianRadialBasisFunctions
        • ExponentialGaussianRadialBasisFunctions.reset_parameters()
        • ExponentialGaussianRadialBasisFunctions.forward()
      • GaussianRadialBasisFunctions
        • GaussianRadialBasisFunctions.reset_parameters()
        • GaussianRadialBasisFunctions.forward()
      • OverlapBernsteinRadialBasisFunctions
        • OverlapBernsteinRadialBasisFunctions.reset_parameters()
        • OverlapBernsteinRadialBasisFunctions.forward()
      • sph_harm_layer
        • sph_harm_layer.forward()
      • BesselBasis
        • BesselBasis.forward()
      • GaussianSmearing
        • GaussianSmearing.forward()
    • Cutoff Functions
      • cutoff_function()
      • cuttoff_envelope
        • cuttoff_envelope.forward()
      • CosineCutoff
        • CosineCutoff.forward()
      • SoftUnitStepCutoff
        • SoftUnitStepCutoff.cutoff
        • SoftUnitStepCutoff.cut_param
        • SoftUnitStepCutoff.forward()
    • Regression Layers
      • denseRegression
        • denseRegression.forward()
      • MLPRegression
        • MLPRegression.forward()
    • Hyperparameter Configuration
      • get_hparam_dict()
  • Data Processing
    • Graph Data
  • Configuration
    • Config Parsing
      • config_default
      • recursive_update()
      • load_config()
  • Utilities
    • Irreps Utilities
      • extract_scalar_irreps()
      • irreps2gate()
      • scale_irreps()
      • filter_and_split_irreps()
    • Triplets
      • triplets()
    • Math Utilities
      • count_neighbors_per_node()
      • prod()
      • blockwise_2x2_concat()
      • extract_elements_above_threshold()
      • upgrade_tensor_precision()
    • Loss Functions
      • cosine_similarity_loss
        • cosine_similarity_loss.forward()
      • sum_zero_loss
        • sum_zero_loss.forward()
      • Euclidean_loss
        • Euclidean_loss.forward()
      • RMSELoss
        • RMSELoss.forward()
      • parse_metric_func()
    • Visualization
      • scatter_plot()
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