graphinglib.FitFromExponential.__init__#

FitFromExponential.__init__(curve_to_be_fit: Curve | Scatter, label: str | None = None, guesses: ArrayLike | None = None, color: str = 'default', line_width: int | Literal['default'] = 'default', line_style: str = 'default') None[source]#

Create a curve fit (continuous Curve) of the form \(f(x) = a \exp(bx + c)\) from an existing Curve object using an exponential fit.

Parameters:
curve_to_be_fitCurve or Scatter

The object to be fit.

labelstr, optional

Label to be displayed in the legend.

guessesArrayLike, optional

Initial guesses for the parameters of the fit. Order is a, b, c as written above.

colorstr

Color of the curve. Default depends on the figure_style configuration.

line_widthint

Line width of the curve. Default depends on the figure_style configuration.

line_stylestr

Line style of the curve. Default depends on the figure_style configuration.

Attributes:
parametersnp.ndarray

Parameters of the fit (same order as guesses).

cov_matrixnp.ndarray

Covariance matrix of the parameters of the fit.

standard_deviationnp.ndarray

Standard deviation of the parameters of the fit.

functionCallable

Exponential function with the parameters of the fit.