........................................................................ [ 48%]
...........s................................................s...s.....s. [ 96%]
......                                                                   [100%]
=============================== warnings summary ===============================
tests/test_risk_models.py::test_semicovariance_benchmark
  $WORKSPACE/pypfopt-missing/pypfopt/risk_models.py:85: UserWarning: The covariance matrix is non positive semidefinite. Amending eigenvalues.
    warnings.warn(

tests/test_risk_models.py::test_semicovariance_benchmark
  $WORKSPACE/pypfopt-missing/pypfopt/risk_models.py:96: RuntimeWarning: divide by zero encountered in matmul
    fixed_matrix = V @ np.diag(q) @ V.T

tests/test_risk_models.py::test_semicovariance_benchmark
  $WORKSPACE/pypfopt-missing/pypfopt/risk_models.py:96: RuntimeWarning: overflow encountered in matmul
    fixed_matrix = V @ np.diag(q) @ V.T

tests/test_risk_models.py::test_semicovariance_benchmark
  $WORKSPACE/pypfopt-missing/pypfopt/risk_models.py:96: RuntimeWarning: invalid value encountered in matmul
    fixed_matrix = V @ np.diag(q) @ V.T

tests/test_risk_models.py::test_semicovariance_benchmark
  $WORKSPACE/pypfopt-missing/pypfopt/risk_models.py:104: UserWarning: Could not fix matrix. Please try a different risk model.
    warnings.warn(

tests/test_risk_models.py::test_ledoit_wolf_default
  $WORKSPACE/pypfopt-missing/tests/test_risk_models.py:261: UserWarning: Dropping 6230 incomplete return observations for shrinkage estimation
    shrunk_cov = cs.ledoit_wolf()

tests/test_risk_models.py::test_ledoit_wolf_single_index
tests/test_risk_models.py::test_risk_matrix_and_returns_data
tests/test_risk_models.py::test_risk_matrix_and_returns_data
tests/test_efficient_frontier.py::test_efficient_return_shrunk
  $WORKSPACE/pypfopt-missing/pypfopt/risk_models.py:552: UserWarning: Dropping 6230 incomplete return observations for shrinkage estimation
    shrunk_cov, self.delta = self._ledoit_wolf_single_factor()

tests/test_risk_models.py::test_ledoit_wolf_constant_correlation
tests/test_risk_models.py::test_risk_matrix_and_returns_data
tests/test_risk_models.py::test_risk_matrix_and_returns_data
tests/test_efficient_frontier.py::test_min_volatility_shrunk_L2_reg
  $WORKSPACE/pypfopt-missing/pypfopt/risk_models.py:554: UserWarning: Dropping 6230 incomplete return observations for shrinkage estimation
    shrunk_cov, self.delta = self._ledoit_wolf_constant_correlation()

tests/test_risk_models.py::test_oracle_approximating
  $WORKSPACE/pypfopt-missing/tests/test_risk_models.py:304: UserWarning: Dropping 6230 incomplete return observations for shrinkage estimation
    shrunk_cov = cs.oracle_approximating()

tests/test_risk_models.py::test_oracle_approximating
tests/test_risk_models.py::test_risk_matrix_and_returns_data
tests/test_risk_models.py::test_risk_matrix_and_returns_data
  $PYTHON_ENV/lib/python3.12/site-packages/scipy/linalg/_basic.py:1695: RuntimeWarning: divide by zero encountered in matmul
    B = (u * psigma_diag) @ u.conj().T

tests/test_risk_models.py::test_oracle_approximating
tests/test_risk_models.py::test_risk_matrix_and_returns_data
tests/test_risk_models.py::test_risk_matrix_and_returns_data
  $PYTHON_ENV/lib/python3.12/site-packages/scipy/linalg/_basic.py:1695: RuntimeWarning: overflow encountered in matmul
    B = (u * psigma_diag) @ u.conj().T

tests/test_risk_models.py::test_oracle_approximating
tests/test_risk_models.py::test_risk_matrix_and_returns_data
tests/test_risk_models.py::test_risk_matrix_and_returns_data
  $PYTHON_ENV/lib/python3.12/site-packages/scipy/linalg/_basic.py:1695: RuntimeWarning: invalid value encountered in matmul
    B = (u * psigma_diag) @ u.conj().T

tests/test_risk_models.py::test_risk_matrix_and_returns_data
tests/test_risk_models.py::test_risk_matrix_and_returns_data
  $WORKSPACE/pypfopt-missing/pypfopt/risk_models.py:167: UserWarning: Dropping 6230 incomplete return observations for shrinkage estimation
    return CovarianceShrinkage(prices, **kwargs).oracle_approximating()

tests/test_risk_models.py::test_risk_matrix_and_returns_data
tests/test_risk_models.py::test_risk_matrix_and_returns_data
tests/test_risk_models.py::test_risk_matrix_and_returns_data
tests/test_risk_models.py::test_risk_matrix_and_returns_data
  $WORKSPACE/pypfopt-missing/pypfopt/risk_models.py:157: UserWarning: Dropping 6230 incomplete return observations for shrinkage estimation
    return CovarianceShrinkage(prices, **kwargs).ledoit_wolf()

tests/test_black_litterman.py: 10 warnings
  $WORKSPACE/pypfopt-missing/pypfopt/black_litterman.py:276: UserWarning: Running Black-Litterman with no prior.
    warnings.warn("Running Black-Litterman with no prior.")

tests/test_black_litterman.py::test_input_errors
tests/test_black_litterman.py::test_dataframe_input
tests/test_black_litterman.py::test_cov_ndarray
tests/test_black_litterman.py::test_default_omega
tests/test_black_litterman.py::test_bl_returns_all_views
  $WORKSPACE/pypfopt-missing/pypfopt/black_litterman.py:377: RuntimeWarning: divide by zero encountered in matmul
    return np.diag(np.diag(tau * P @ cov_matrix @ P.T))

tests/test_black_litterman.py::test_input_errors
tests/test_black_litterman.py::test_dataframe_input
tests/test_black_litterman.py::test_cov_ndarray
tests/test_black_litterman.py::test_default_omega
tests/test_black_litterman.py::test_bl_returns_all_views
  $WORKSPACE/pypfopt-missing/pypfopt/black_litterman.py:377: RuntimeWarning: overflow encountered in matmul
    return np.diag(np.diag(tau * P @ cov_matrix @ P.T))

tests/test_black_litterman.py::test_input_errors
tests/test_black_litterman.py::test_dataframe_input
tests/test_black_litterman.py::test_cov_ndarray
tests/test_black_litterman.py::test_default_omega
tests/test_black_litterman.py::test_bl_returns_all_views
  $WORKSPACE/pypfopt-missing/pypfopt/black_litterman.py:377: RuntimeWarning: invalid value encountered in matmul
    return np.diag(np.diag(tau * P @ cov_matrix @ P.T))

tests/test_black_litterman.py::test_cov_ndarray
tests/test_black_litterman.py::test_bl_returns_all_views
  $WORKSPACE/pypfopt-missing/pypfopt/black_litterman.py:429: RuntimeWarning: divide by zero encountered in matmul
    self._tau_sigma_P = self.tau * self.cov_matrix @ self.P.T

tests/test_black_litterman.py::test_cov_ndarray
tests/test_black_litterman.py::test_bl_returns_all_views
  $WORKSPACE/pypfopt-missing/pypfopt/black_litterman.py:429: RuntimeWarning: overflow encountered in matmul
    self._tau_sigma_P = self.tau * self.cov_matrix @ self.P.T

tests/test_black_litterman.py::test_cov_ndarray
tests/test_black_litterman.py::test_bl_returns_all_views
  $WORKSPACE/pypfopt-missing/pypfopt/black_litterman.py:429: RuntimeWarning: invalid value encountered in matmul
    self._tau_sigma_P = self.tau * self.cov_matrix @ self.P.T

tests/test_black_litterman.py::test_cov_ndarray
tests/test_black_litterman.py::test_bl_returns_all_views
  $WORKSPACE/pypfopt-missing/pypfopt/black_litterman.py:433: RuntimeWarning: divide by zero encountered in matmul
    self._A = (self.P @ self._tau_sigma_P) + self.omega

tests/test_black_litterman.py::test_cov_ndarray
tests/test_black_litterman.py::test_bl_returns_all_views
  $WORKSPACE/pypfopt-missing/pypfopt/black_litterman.py:433: RuntimeWarning: overflow encountered in matmul
    self._A = (self.P @ self._tau_sigma_P) + self.omega

tests/test_black_litterman.py::test_cov_ndarray
tests/test_black_litterman.py::test_bl_returns_all_views
  $WORKSPACE/pypfopt-missing/pypfopt/black_litterman.py:433: RuntimeWarning: invalid value encountered in matmul
    self._A = (self.P @ self._tau_sigma_P) + self.omega

tests/test_black_litterman.py::test_cov_ndarray
  $WORKSPACE/pypfopt-missing/pypfopt/black_litterman.py:470: RuntimeWarning: divide by zero encountered in matmul
    M = self.tau * self.cov_matrix - self._tau_sigma_P @ M_solution

tests/test_black_litterman.py::test_cov_ndarray
  $WORKSPACE/pypfopt-missing/pypfopt/black_litterman.py:470: RuntimeWarning: overflow encountered in matmul
    M = self.tau * self.cov_matrix - self._tau_sigma_P @ M_solution

tests/test_black_litterman.py::test_cov_ndarray
  $WORKSPACE/pypfopt-missing/pypfopt/black_litterman.py:470: RuntimeWarning: invalid value encountered in matmul
    M = self.tau * self.cov_matrix - self._tau_sigma_P @ M_solution

tests/test_black_litterman.py::test_bl_returns_all_views
  $WORKSPACE/pypfopt-missing/tests/test_black_litterman.py:169: UserWarning: Dropping 6230 incomplete return observations for shrinkage estimation
    S = risk_models.CovarianceShrinkage(df).ledoit_wolf()

tests/test_black_litterman.py::test_bl_relative_views
  $WORKSPACE/pypfopt-missing/tests/test_black_litterman.py:210: UserWarning: Dropping 6230 incomplete return observations for shrinkage estimation
    S = risk_models.CovarianceShrinkage(df).ledoit_wolf()

tests/test_black_litterman.py::test_bl_cov_default
  $WORKSPACE/pypfopt-missing/tests/test_black_litterman.py:233: UserWarning: Dropping 6230 incomplete return observations for shrinkage estimation
    cov_matrix = risk_models.CovarianceShrinkage(df).ledoit_wolf()

tests/test_efficient_frontier.py::test_min_volatility_sector_constraints
  $WORKSPACE/pypfopt-missing/pypfopt/base/_base_optimizer.py:429: UserWarning: Sector constraints may not produce reasonable results if shorts are allowed.
    warnings.warn(

tests/test_efficient_frontier.py::test_max_sharpe_long_only
  $WORKSPACE/pypfopt-missing/pypfopt/efficient_frontier/efficient_frontier.py:498: UserWarning: The risk_free_rate provided to portfolio_performance is different to the one used by max_sharpe. Using the previous value.
    warnings.warn(

tests/test_efficient_frontier.py::test_max_sharpe_L2_reg_different_gamma
tests/test_efficient_frontier.py::test_max_sharpe_L2_reg_different_gamma
tests/test_efficient_frontier.py::test_max_sharpe_L2_reg_reduces_sharpe
tests/test_efficient_frontier.py::test_max_sharpe_L2_reg_with_shorts
  $WORKSPACE/pypfopt-missing/pypfopt/efficient_frontier/efficient_frontier.py:281: UserWarning: max_sharpe transforms the optimization problem so additional objectives may not work as expected.
    warnings.warn(

tests/test_efficient_frontier.py: 17 warnings
  $PYTHON_ENV/lib/python3.12/site-packages/numpy/linalg/_linalg.py:3383: RuntimeWarning: divide by zero encountered in matmul
    return _core_matmul(x1, x2)

tests/test_efficient_frontier.py: 17 warnings
  $PYTHON_ENV/lib/python3.12/site-packages/numpy/linalg/_linalg.py:3383: RuntimeWarning: overflow encountered in matmul
    return _core_matmul(x1, x2)

tests/test_efficient_frontier.py: 17 warnings
  $PYTHON_ENV/lib/python3.12/site-packages/numpy/linalg/_linalg.py:3383: RuntimeWarning: invalid value encountered in matmul
    return _core_matmul(x1, x2)

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
146 passed, 4 skipped, 130 warnings in 5.45s
