Cleaner check for existence of modules

CLUEstering/CLUEstering.py

@@ -14,24 +14,21 @@
 import pandas as pd
 from sklearn.datasets import make_blobs
 from sklearn.preprocessing import StandardScaler
-from os.path import dirname, join
+from os.path import dirname, exists, join
 path = dirname(__file__)
 import sys
 sys.path.insert(1, join(path, 'lib'))
 import CLUE_Convolutional_Kernels as clue_kernels
 import CLUE_CPU_Serial as cpu_serial
-tbb_found = False
-if len(glob(join(path, 'lib/CLUE_CPU_TBB*.so'))) != 0:
+tbb_found = exists(*glob(join(path, 'lib/CLUE_CPU_TBB*.so')))
+if tbb_found:
     import CLUE_CPU_TBB as cpu_tbb
-    tbb_found = True
-cuda_found = False
-if len(glob(join(path, 'lib/CLUE_GPU_CUDA*.so'))) != 0:
+cuda_found = exists(*glob(join(path, 'lib/CLUE_CPU_TBB*.so')))
+if cuda_found:
     import CLUE_GPU_CUDA as gpu_cuda
-    cuda_found = True
-hip_found = False
-if len(glob(join(path, 'lib/CLUE_GPU_HIP*.so'))) != 0:
+hip_found = exists(*glob(join(path, 'lib/CLUE_CPU_TBB*.so')))
+if hip_found:
     import CLUE_GPU_HIP as gpu_hip
-    hip_found = True
 
 def test_blobs(n_samples: int, n_dim: int , n_blobs: int = 4, mean: float = 0,
                sigma: float = 0.5, x_max: float = 30, y_max: float = 30) -> pd.DataFrame: