tudataset's Issues
Feature description for ENZYMES is missing
I have been playing with ENZYMES dataset and found that there are no feature names for node features provided in README or anywhere else (or I need help finding them). While in the referenced paper (Bogwardt et al. 2005) it could be found that features AA length
, Total Waals
etc. I do not know which feature name corresponds to which feature value in tudataset
.
Please provide feature name for each feature dimension in the dataset. It would be a lot more easier to do anything with dataset, starting from data exploratory analysis, when features are stated in README, e.g., in MUTAG dataset.
Do you know how to write my own dataset or use TUDataset to process it into a trainable data format?
Hello blogger, I have made a preprocessing data set by myself and want to use TG for training. Do you know how to write your own dataset or use TUDataset to process it into a trainable data format? (72 graphs, 63 nodes each, with 2300 features for each node that is not hot-coded)>>>
How to represent a molecule with the same format as TUDataset from a molecular SMILES?
Hi,
I m trying to train a QSAR model some GNNs. But what I have is a list of molecular SMILES and the corresponding labels, for example:
x = ['CCCC', 'CCCO', 'CCCN' ...]
y = [1,1,0, ...]
Many of GNNs are taking your datasets as examples, which are preprocessed graph described by a list of files. But I did not find any way to convert to this format from molecular SMILES. Is there any function to convert molecular SMILES to the same format?
Thanks
how should I write the class code ?(for processing the data set so that it can be pytorch_geometric)
Analogous to the TUDataset, I have now understood and made the original format consistent with TUDataset, how should I write the class code ???(for processing the data set so that it can be pytorch_geometric)
I have prepared the raw data like this:
(1) XX_A.txt (m lines)
sparse (block diagonal) adjacency matrix for all graphs,
each line corresponds to (row, col) resp. (node_id, node_id)
(2) XX_graph_indicator.txt (n lines)
column vector of graph identifiers for all nodes of all graphs,
the value in the i-th line is the graph_id of the node with node_id i
(3) XX_graph_labels.txt (N lines)
class labels for all graphs in the dataset,
the value in the i-th line is the class label of the graph with graph_id i
(4) XX_node_attributes.txt (n lines)
matrix of node attributes,
the comma seperated values in the i-th line is the attribute vector of the node with node_id i
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