epyr.baseline.correction

Core baseline correction algorithms for EPR data.

This module contains the main baseline correction functions that work directly with data from epyr.eprload().

Functions

baseline_bi_exponential_1d(x, y[, params, ...])

Bi-exponential baseline correction for 1D EPR data.

baseline_polynomial_1d(x, y[, params, ...])

Polynomial baseline correction for 1D EPR data.

baseline_polynomial_2d(x, y[, params, ...])

Polynomial baseline correction for 2D EPR data.

baseline_stretched_exponential_1d(x, y[, ...])

Stretched-exponential baseline correction for 1D EPR data.
epyr.baseline.correction.baseline_polynomial_1d(x, y, params=None, order=2, exclude_center=True, center_fraction=0.3, manual_regions=None, region_mode='exclude', interactive=False)[source]

Polynomial baseline correction for 1D EPR data.

Fits a polynomial to selected baseline regions and subtracts it from the full dataset. Suited to CW EPR spectra with smooth drift.

Parameters:

  • x (np.ndarray or None) – Field axis from epyr.eprload(). If None or length mismatch, falls back to point indices.

  • y (np.ndarray) – 1D spectrum from epyr.eprload().

  • params (dict, optional) – Parameter dictionary from epyr.eprload() (unused for the fit itself; reserved for future axis-aware extensions).

  • order (int, optional) – Polynomial order. Typical range 1-4. Default 2.

  • exclude_center (bool, optional) – Exclude a centred fraction of the data from fitting (where the signal is expected). Default True.

  • center_fraction (float, optional) – Width of the excluded central window, as a fraction of the data. Default 0.3.

  • manual_regions (list of (float, float), optional) – Explicit (x_low, x_high) regions. Combined with region_mode.

  • region_mode ({'exclude', 'include'}, optional) – 'exclude' removes manual_regions from the fit; 'include' keeps only those regions. Default 'exclude'.

  • interactive (bool, optional) – Launch the matplotlib region selector. Requires an interactive backend. Default False.

Returns:

  • corrected (np.ndarray) – Baseline-subtracted spectrum.

  • baseline (np.ndarray) – Fitted polynomial evaluated on the full axis.

Return type:

Tuple[ndarray, ndarray]

Examples

>>> from epyr import eprload, baseline_polynomial_1d
>>> x, y, params, _ = eprload("examples/data/130406SB_CaWO4_Er_CW_5K_20.DSC")
>>> corrected, baseline = baseline_polynomial_1d(x, y, params, order=3)
>>> corrected.shape == y.shape
True

Fit only on user-defined wings (exclude resonance region):

>>> wings = [(3300, 3400), (3550, 3700)]
>>> corrected, _ = baseline_polynomial_1d(
...     x, y, params, order=2,
...     manual_regions=wings, region_mode="include",
... )
epyr.baseline.correction.baseline_polynomial_2d(x, y, params=None, order=1, exclude_center=True, center_fraction=0.3, manual_regions=None, region_mode='exclude', interactive=False, use_real_part=False)[source]

Polynomial baseline correction for 2D EPR data.

Fits a 2D polynomial surface to selected regions and subtracts it from the full dataset. Useful for 2D experiments (DEER, Rabi 2D, etc.).

Parameters:

  • x (np.ndarray, list of np.ndarray, or None) – Axis data from epyr.eprload(). A two-element list [xa, ya] sets both axes. None falls back to indices.

  • y (np.ndarray) – 2D spectrum, shape (ny, nx).

  • params (dict, optional) – Parameter dictionary from epyr.eprload().

  • order (int or (int, int), optional) – Polynomial order. int applies the same order to both axes; a tuple sets (order_x, order_y) independently. Default 1.

  • exclude_center (bool, optional) – Exclude a centred rectangular block of the data from the fit. Default True.

  • center_fraction (float, optional) – Width of that block along each axis, as a fraction. Default 0.3.

  • manual_regions (list of ((x1, x2), (y1, y2)), optional) – Explicit rectangular regions.

  • region_mode ({'exclude', 'include'}, optional) – How to combine manual_regions with the fit mask. Default 'exclude'.

  • interactive (bool, optional) – Launch the matplotlib 2D region selector. Default False.

  • use_real_part (bool, optional) – For complex data, fit on y.real. Default False.

Returns:

  • corrected (np.ndarray) – Baseline-subtracted surface.

  • baseline (np.ndarray) – Fitted polynomial evaluated on the full grid.

Return type:

Tuple[ndarray, ndarray]

Examples

>>> from epyr import eprload, baseline_polynomial_2d
>>> x, y, params, _ = eprload("examples/data/Rabi2D_GdCaWO4_13dB_3057G.DSC")
>>> corrected, baseline = baseline_polynomial_2d(x, y, params, order=(2, 1))
>>> corrected.shape == y.shape
True
epyr.baseline.correction.baseline_stretched_exponential_1d(x, y, params=None, use_real_part=True, exclude_initial=0, exclude_final=0, manual_regions=None, region_mode='exclude', interactive=False, beta_range=(0.01, 5.0), initial_guess=None)[source]

Stretched-exponential baseline correction for 1D EPR data.

Fits and removes a baseline of the form

\[b(x) = \mathrm{offset} + A \exp\!\left[-(x/\tau)^{\beta}\right]\]

Typical use: T2 echo decay envelope removal before peak analysis.

Parameters:

  • x (np.ndarray or None) – Time axis from epyr.eprload(). Falls back to indices if None or length mismatch.

  • y (np.ndarray) – 1D signal from epyr.eprload().

  • params (dict, optional) – Parameter dictionary from epyr.eprload().

  • use_real_part (bool, optional) – For complex y, fit on y.real. Default True.

  • exclude_initial (int, optional) – Drop the first / last N points from the fit. Default 0.

  • exclude_final (int, optional) – Drop the first / last N points from the fit. Default 0.

  • manual_regions (list of (float, float), optional) – Explicit (x_low, x_high) windows.

  • region_mode ({'exclude', 'include'}, optional) – Combine manual_regions with the fit mask. Default 'exclude'.

  • interactive (bool, optional) – Launch the matplotlib region selector. Default False.

  • beta_range ((float, float), optional) – Bounds on the stretching exponent. Default (0.01, 5.0).

  • initial_guess (dict, optional) – Seed values, any subset of {'A', 'tau', 'beta', 'offset'}.

Returns:

  • corrected (np.ndarray) – Baseline-subtracted signal.

  • baseline (np.ndarray) – Fitted baseline on the full axis.

Return type:

Tuple[ndarray, ndarray]

Examples

>>> from epyr import eprload, baseline_stretched_exponential_1d
>>> path = "examples/data/ESEdecay_2D_rotgon_035_07.3K_h80_9.73687GHz_B3.DSC"
>>> x, y, params, _ = eprload(path)
>>> # take a single trace from the 2D dataset
>>> trace = y[0]
>>> corrected, baseline = baseline_stretched_exponential_1d(
...     x[0], trace, params, exclude_initial=5,
... )
>>> corrected.shape == trace.shape
True
epyr.baseline.correction.baseline_bi_exponential_1d(x, y, params=None, use_real_part=True, exclude_initial=0, exclude_final=0, manual_regions=None, region_mode='exclude', interactive=False, tau_ratio_min=2.5, initial_guess=None)[source]

Bi-exponential baseline correction for 1D EPR data.

Fits and removes a baseline of the form

\[b(x) = \mathrm{offset} + A_1 e^{-x/\tau_1} + A_2 e^{-x/\tau_2}\]

Suited to decays with two well-separated relaxation channels.

Parameters:

  • x (np.ndarray or None) – Time axis from epyr.eprload(). Falls back to indices if None.

  • y (np.ndarray) – 1D signal from epyr.eprload().

  • params (dict, optional) – Parameter dictionary from epyr.eprload().

  • use_real_part (bool, optional) – For complex y, fit on y.real. Default True.

  • exclude_initial (int, optional) – Drop the first / last N points from the fit. Default 0.

  • exclude_final (int, optional) – Drop the first / last N points from the fit. Default 0.

  • manual_regions (list of (float, float), optional) – Explicit (x_low, x_high) windows.

  • region_mode ({'exclude', 'include'}, optional) – How to combine manual_regions with the fit mask.

  • interactive (bool, optional) – Launch the matplotlib region selector. Default False.

  • tau_ratio_min (float, optional) – Minimum ratio tau2 / tau1 enforced during fitting to keep the two components separable. Default 2.5.

  • initial_guess (dict, optional) – Seed values, any subset of {'A1', 'tau1', 'A2', 'tau2', 'offset'}.

Returns:

  • corrected (np.ndarray) – Baseline-subtracted signal.

  • baseline (np.ndarray) – Fitted baseline on the full axis.

Return type:

Tuple[ndarray, ndarray]

Examples

>>> from epyr import eprload, baseline_bi_exponential_1d
>>> path = "examples/data/ESEdecay_2D_rotgon_035_07.3K_h80_9.73687GHz_B3.DSC"
>>> x, y, params, _ = eprload(path)
>>> trace = y[0]
>>> corrected, baseline = baseline_bi_exponential_1d(
...     x[0], trace, params, tau_ratio_min=3.0,
... )
>>> corrected.shape == trace.shape
True