def __init__()

in benchmarks/run_benchmarks.py [0:0]

• 46 lines of code
• 11 McCabe index (conditional complexity)

    def __init__(self, config, random_state=0):
        self.config = config
        self.problems = config.problems
        self.operator_modes = config.operator_modes
        self.algo_modes = config.algo_modes
        self.accel_params = config.accel_params
        self.solvers = config.solvers
        self.sparse_formats = config.sparse_formats
        self.sketch_sizes = config.sketch_sizes
        self.kernel_parameters = config.kernel_parameters
        self.random_state = random_state
        np.random.seed(seed=random_state)

        density = config.density  # make a for loop here
        larger_dimension, smaller_dimension = (
            config.larger_dimension,
            config.smaller_dimension,
        )

        # Setting data to sparse random matrices if required
        if "primal_random" in self.problems:
            if "csc" in self.sparse_formats:
                self.X_primal_csc_random = sprandom(
                    larger_dimension, smaller_dimension, density=density, format="csc",
                )
            if "csr" in self.sparse_formats:
                self.X_primal_csr_random = sprandom(
                    larger_dimension, smaller_dimension, density=density, format="csr"
                )
            if "dense" in self.sparse_formats:
                self.X_primal_dense_random = np.random.rand(
                    larger_dimension, smaller_dimension
                )
            self.y_primal_random = np.random.rand(larger_dimension, 1)
        if "dual_random" in self.problems:
            if "csc" in self.sparse_formats:
                self.X_dual_csc_random = sprandom(
                    smaller_dimension, larger_dimension, density=density, format="csc"
                )
            if "csr" in self.sparse_formats:
                self.X_dual_csr_random = sprandom(
                    smaller_dimension, larger_dimension, density=density, format="csr"
                )
            if "dense" in self.sparse_formats:
                self.X_dual_dense_random = np.random.rand(
                    smaller_dimension, larger_dimension
                )
            self.y_dual_random = np.random.rand(smaller_dimension, 1)

        self.times_df, self.residual_norms_df = None, None