Metadata-Version: 2.1
Name: pycudacov
Version: 0.0.28
Summary: A PyCuda Covariance Matrix Parallel Implementation
Home-page: https://github.com/Ivanrs297/pycuda-covariance-matrix
Author: Ivan Reyes
Author-email: ivanrs297@gmail.com
License: UNKNOWN
Description: # PyCUDACov - A PyCuda Covariance Matrix Parallel Implementation
        
        [![MIT License](https://img.shields.io/apm/l/atomic-design-ui.svg?)](https://github.com/tterb/atomic-design-ui/blob/master/LICENSEs)
        
        ## Usage and Installation
        
        Requires CUDA enviroment, _nvcc_ > 8.
        
        ```python
        from sklearn.datasets import make_blobs
        from sklearn.preprocessing import StandardScaler
        from pandas import DataFrame
        import numpy as np
        from pycudacov import get_cov
        
        # Generate test dataset
        rows, cols = 16384, 1024 # samples, features
        X, y = make_blobs(n_samples = rows, centers = 2, n_features = cols)
        X_std = StandardScaler().fit_transform(X) # Optional
        df = DataFrame(X_std)
        df = df.astype(np.float32)
        
        # Call to PyCUDA Kernel
        covariance_matrix = get_cov(df.values)
        
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
