def load_datasets(dataset_name, save_path="data/", url=None):
if dataset_name == "synthetic":
gene_dataset = SyntheticDataset()
elif dataset_name == "cortex":
gene_dataset = CortexDataset()
elif dataset_name == "brain_large":
gene_dataset = BrainLargeDataset(save_path=save_path)
elif dataset_name == "retina":
gene_dataset = RetinaDataset(save_path=save_path)
elif dataset_name == "cbmc":
gene_dataset = CbmcDataset(save_path=save_path)
elif dataset_name == "brain_small":
gene_dataset = BrainSmallDataset(save_path=save_path)
elif dataset_name == "hemato":
gene_dataset = HematoDataset(save_path="data/HEMATO/")
elif dataset_name == "pbmc":
gene_dataset = PbmcDataset(save_path=save_path)
elif dataset_name[-5:] == ".loom":
gene_dataset = LoomDataset(filename=dataset_name, save_path=save_path, url=url)
elif dataset_name[-5:] == ".h5ad":
gene_dataset = AnnDataset(dataset_name, save_path=save_path, url=url)
elif ".csv" in dataset_name:
gene_dataset = CsvDataset(dataset_name, save_path=save_path)
else:
raise Exception("No such dataset available")
return gene_dataset
def load_datasets(dataset_name, save_path='data/', url=None):
if dataset_name == 'synthetic':
gene_dataset = SyntheticDataset()
elif dataset_name == 'cortex':
gene_dataset = CortexDataset()
elif dataset_name == 'brain_large':
gene_dataset = BrainLargeDataset(save_path=save_path)
elif dataset_name == 'retina':
gene_dataset = RetinaDataset(save_path=save_path)
elif dataset_name == 'cbmc':
gene_dataset = CbmcDataset(save_path=save_path)
elif dataset_name == 'brain_small':
gene_dataset = BrainSmallDataset(save_path=save_path)
elif dataset_name == 'hemato':
gene_dataset = HematoDataset(save_path='data/HEMATO/')
elif dataset_name == 'pbmc':
gene_dataset = PbmcDataset(save_path=save_path)
elif dataset_name[-5:] == ".loom":
gene_dataset = LoomDataset(filename=dataset_name,
save_path=save_path,
url=url)
elif dataset_name[-5:] == ".h5ad":
gene_dataset = AnnDataset(dataset_name, save_path=save_path, url=url)
elif ".csv" in dataset_name:
gene_dataset = CsvDataset(dataset_name, save_path=save_path)
else:
raise "No such dataset available"
return gene_dataset
def test_anndata():
ann_dataset = AnnDataset("TM_droplet_mat.h5ad", save_path='tests/data/')
base_benchmark(ann_dataset)
def test_anndata(save_path):
ann_dataset = AnnDataset("TM_droplet_mat.h5ad", save_path=save_path)
base_benchmark(ann_dataset)
def test_anndata(save_path):
ann_dataset = AnnDataset("TM_droplet_mat.h5ad", save_path=save_path)
base_benchmark(ann_dataset)
AnnDataset(anndata.AnnData(np.random.randint(1, 10, (10, 10))))