InstrumentedPCA.fit() prints repetitive logs, specifically in _build_portfolio method

[TheephopWS]

Description

InstrumentedPCA.fit() prints repetitive logs, specifically in _build_portfolio method, when called repeatedly, which clutters notebook/terminal output.

Please also support quiet=True (or verbose=False) for _build_portfolio

Reproducible Code

from ipca import InstrumentedPCA

for k in range(1, 7):
    # unrestricted
    model_u = InstrumentedPCA(n_factors=k, intercept=True)
    model_u.fit(X=X, y=y)

    # restricted
    model_r = InstrumentedPCA(n_factors=k, intercept=False)
    model_r.fit(X=X, y=y)

Current Behavior

• fit() prints verbose _build_portfolio progress/log output each time it is called.
• Repeated fits produce large, noisy output.

Example Outputs

[========================================================================] 100%
The panel dimensions are:
n_samples: 23 , L: 37 , T: 142

[========================================================================] 100%
The panel dimensions are:
n_samples: 23 , L: 37 , T: 142

[========================================================================] 100%
The panel dimensions are:
n_samples: 23 , L: 37 , T: 142

[========================================================================] 100%
The panel dimensions are:
n_samples: 23 , L: 37 , T: 142

[========================================================================] 100%
The panel dimensions are:
n_samples: 23 , L: 37 , T: 142

[========================================================================] 100%
The panel dimensions are:
n_samples: 23 , L: 37 , T: 142

[========================================================================] 100%
The panel dimensions are:
n_samples: 23 , L: 37 , T: 142

[========================================================================] 100%
The panel dimensions are:
n_samples: 23 , L: 37 , T: 142

[========================================================================] 100%
The panel dimensions are:
n_samples: 23 , L: 37 , T: 142

[========================================================================] 100%
The panel dimensions are:
n_samples: 23 , L: 37 , T: 142

[========================================================================] 100%
The panel dimensions are:
n_samples: 23 , L: 37 , T: 142

[========================================================================] 100%
The panel dimensions are:
n_samples: 23 , L: 37 , T: 142

Environment

• OS: Windows
• Python: 3.12.0