How to use the molgrid.MGrid1f function in molgrid

To help you get started, we’ve selected a few molgrid examples, based on popular ways it is used in public projects.

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gnina / libmolgrid / test / test_torch.py View on Github

types.data[...] = 0
    types.data[:,10] = 1

    batch_radii = torch.tensor(np.tile(radii, (batch_size, 1)), dtype=torch.float32,  device='cuda')    

    grid_gen = c2grid(coords.unsqueeze(0), types.unsqueeze(0)[:,:,:-1], batch_radii)
    
    assert float(grid_gen[0][10].sum()) == approx(float(grid_gen.sum()))
    assert grid_gen.sum() > 0
    
    target = torch.zeros_like(grid_gen)
    target[0,:,24,24,24] = 1000.0
        
    grad_coords = molgrid.MGrid2f(n_atoms,3)
    grad_types = molgrid.MGrid2f(n_atoms,n_types)
    r = molgrid.MGrid1f(len(radii))
    r.copyFrom(radii)
    
    grid_loss = F.mse_loss(target, grid_gen)
    grid_loss.backward()
    print(grid_loss)
    print(coords.grad.detach().cpu().numpy())

gnina / libmolgrid / test / test_example_provider.py View on Github

e = molgrid.ExampleProvider(data_root=datadir+"/structs")
    e.populate(fname)

    batch_size = 100
    batch = e.next_batch(batch_size)
    #extract labels
    nlabels = e.num_labels()
    assert nlabels == 3
    labels = molgrid.MGrid2f(batch_size,nlabels)
    gpulabels = molgrid.MGrid2f(batch_size,nlabels)

    batch.extract_labels(labels.cpu())
    batch.extract_labels(gpulabels.gpu())
    assert np.array_equal(labels.tonumpy(), gpulabels.tonumpy())
    label0 = molgrid.MGrid1f(batch_size)
    label1 = molgrid.MGrid1f(batch_size)
    label2 = molgrid.MGrid1f(batch_size)
    batch.extract_label(0, label0.cpu())
    batch.extract_label(1, label1.cpu())
    batch.extract_label(2, label2.gpu())

    assert label0[0] == 1
    assert label1[0] == approx(6.05)
    assert label2[0] == approx(0.162643)
    assert labels[0,0] == 1
    assert labels[0][1] == approx(6.05)
    assert labels[0][2] == approx(0.162643)

    for i in range(nlabels):
        assert label0[i] == labels[i][0]
        assert label1[i] == labels[i][1]
        assert label2[i] == labels[i][2]

gnina / libmolgrid / test / test_example_provider.py View on Github

fname = datadir+"/small.types"
    e = molgrid.ExampleProvider(data_root=datadir+"/structs")
    e.populate(fname)

    batch_size = 100
    batch = e.next_batch(batch_size)
    #extract labels
    nlabels = e.num_labels()
    assert nlabels == 3
    labels = molgrid.MGrid2f(batch_size,nlabels)
    gpulabels = molgrid.MGrid2f(batch_size,nlabels)

    batch.extract_labels(labels.cpu())
    batch.extract_labels(gpulabels.gpu())
    assert np.array_equal(labels.tonumpy(), gpulabels.tonumpy())
    label0 = molgrid.MGrid1f(batch_size)
    label1 = molgrid.MGrid1f(batch_size)
    label2 = molgrid.MGrid1f(batch_size)
    batch.extract_label(0, label0.cpu())
    batch.extract_label(1, label1.cpu())
    batch.extract_label(2, label2.gpu())

    assert label0[0] == 1
    assert label1[0] == approx(6.05)
    assert label2[0] == approx(0.162643)
    assert labels[0,0] == 1
    assert labels[0][1] == approx(6.05)
    assert labels[0][2] == approx(0.162643)

    for i in range(nlabels):
        assert label0[i] == labels[i][0]
        assert label1[i] == labels[i][1]

gnina / libmolgrid / test / test_example_provider.py View on Github

fname = datadir+"/small.types"
    e = molgrid.ExampleProvider(ligmolcache=datadir+'/lig.molcache2',recmolcache=datadir+'/rec.molcache2')
    e.populate(fname)

    batch_size = 100
    batch = e.next_batch(batch_size)
    #extract labels
    nlabels = e.num_labels()
    assert nlabels == 3
    labels = molgrid.MGrid2f(batch_size,nlabels)
    gpulabels = molgrid.MGrid2f(batch_size,nlabels)

    batch.extract_labels(labels.cpu())
    batch.extract_labels(gpulabels.gpu())
    assert np.array_equal(labels.tonumpy(), gpulabels.tonumpy())
    label0 = molgrid.MGrid1f(batch_size)
    label1 = molgrid.MGrid1f(batch_size)
    label2 = molgrid.MGrid1f(batch_size)
    batch.extract_label(0, label0.cpu())
    batch.extract_label(1, label1.cpu())
    batch.extract_label(2, label2.gpu())

    assert label0[0] == 1
    assert label1[0] == approx(6.05)
    assert label2[0] == approx(0.162643)
    assert labels[0,0] == 1
    assert labels[0][1] == approx(6.05)
    assert labels[0][2] == approx(0.162643)

    for i in range(nlabels):
        assert label0[i] == labels[i][0]
        assert label1[i] == labels[i][1]

gnina / libmolgrid / test / test_example_provider.py View on Github

e.populate(fname)

    batch_size = 100
    batch = e.next_batch(batch_size)
    #extract labels
    nlabels = e.num_labels()
    assert nlabels == 3
    labels = molgrid.MGrid2f(batch_size,nlabels)
    gpulabels = molgrid.MGrid2f(batch_size,nlabels)

    batch.extract_labels(labels.cpu())
    batch.extract_labels(gpulabels.gpu())
    assert np.array_equal(labels.tonumpy(), gpulabels.tonumpy())
    label0 = molgrid.MGrid1f(batch_size)
    label1 = molgrid.MGrid1f(batch_size)
    label2 = molgrid.MGrid1f(batch_size)
    batch.extract_label(0, label0.cpu())
    batch.extract_label(1, label1.cpu())
    batch.extract_label(2, label2.gpu())

    assert label0[0] == 1
    assert label1[0] == approx(6.05)
    assert label2[0] == approx(0.162643)
    assert labels[0,0] == 1
    assert labels[0][1] == approx(6.05)
    assert labels[0][2] == approx(0.162643)

    for i in range(nlabels):
        assert label0[i] == labels[i][0]
        assert label1[i] == labels[i][1]
        assert label2[i] == labels[i][2]

gnina / libmolgrid / test / test_example_provider.py View on Github

e.populate(fname)

    batch_size = 100
    batch = e.next_batch(batch_size)
    #extract labels
    nlabels = e.num_labels()
    assert nlabels == 3
    labels = molgrid.MGrid2f(batch_size,nlabels)
    gpulabels = molgrid.MGrid2f(batch_size,nlabels)

    batch.extract_labels(labels.cpu())
    batch.extract_labels(gpulabels.gpu())
    assert np.array_equal(labels.tonumpy(), gpulabels.tonumpy())
    label0 = molgrid.MGrid1f(batch_size)
    label1 = molgrid.MGrid1f(batch_size)
    label2 = molgrid.MGrid1f(batch_size)
    batch.extract_label(0, label0.cpu())
    batch.extract_label(1, label1.cpu())
    batch.extract_label(2, label2.gpu())

    assert label0[0] == 1
    assert label1[0] == approx(6.05)
    assert label2[0] == approx(0.162643)
    assert labels[0,0] == 1
    assert labels[0][1] == approx(6.05)
    assert labels[0][2] == approx(0.162643)

    for i in range(nlabels):
        assert label0[i] == labels[i][0]
        assert label1[i] == labels[i][1]
        assert label2[i] == labels[i][2]

gnina / libmolgrid / test / test_example_provider.py View on Github

e = molgrid.ExampleProvider(ligmolcache=datadir+'/lig.molcache2',recmolcache=datadir+'/rec.molcache2')
    e.populate(fname)

    batch_size = 100
    batch = e.next_batch(batch_size)
    #extract labels
    nlabels = e.num_labels()
    assert nlabels == 3
    labels = molgrid.MGrid2f(batch_size,nlabels)
    gpulabels = molgrid.MGrid2f(batch_size,nlabels)

    batch.extract_labels(labels.cpu())
    batch.extract_labels(gpulabels.gpu())
    assert np.array_equal(labels.tonumpy(), gpulabels.tonumpy())
    label0 = molgrid.MGrid1f(batch_size)
    label1 = molgrid.MGrid1f(batch_size)
    label2 = molgrid.MGrid1f(batch_size)
    batch.extract_label(0, label0.cpu())
    batch.extract_label(1, label1.cpu())
    batch.extract_label(2, label2.gpu())

    assert label0[0] == 1
    assert label1[0] == approx(6.05)
    assert label2[0] == approx(0.162643)
    assert labels[0,0] == 1
    assert labels[0][1] == approx(6.05)
    assert labels[0][2] == approx(0.162643)

    for i in range(nlabels):
        assert label0[i] == labels[i][0]
        assert label1[i] == labels[i][1]
        assert label2[i] == labels[i][2]

How to use the molgrid.MGrid1f function in molgrid

To help you get started, we’ve selected a few molgrid examples, based on popular ways it is used in public projects.

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