def GPDM_solver(self):
train_data = []
print(self.gene_data)
for key_gene in self.select_gene:
train_data.append(self.gene_data[key_gene])
self.train_data = np.array(train_data).T
output = GPLVM(self.train_data, self.latent_dim, init='PCA')
output.optimize(messages=True, max_iters=20)
return output
