def __init__(self, *args, **kwargs):
# set the data set object
if args and isinstance(args[0], dts.XYDataSet):
self.dataset = args[0]
fmt = kwargs.pop("fmt", args[1] if len(args) >= 2 else "")
else:
self.dataset = dts.XYDataSet(*args, **kwargs)
fmt = kwargs.pop("fmt", "")
label = kwargs.pop("label", self.dataset.name)
fmt = fmt if fmt else "o"
# call super constructors
XYObjectOnPlot.__init__(self, label=label, fmt=fmt, **kwargs)
def __try_fit_to_xdata_and_ydata(*args, **kwargs):
"""Helper function to parse the inputs to a call to fit() for separate xdata and ydata"""
xdata = kwargs.pop("xdata", args[0] if args else None)
ydata = kwargs.pop("ydata", args[1] if len(args) > 1 else None)
model = kwargs.pop("model", args[2] if len(args) > 2 else None)
if not isinstance(xdata, dts.ExperimentalValueArray):
xdata = np.asarray(xdata) if isinstance(xdata,
ARRAY_TYPES) else np.empty(0)
if not isinstance(ydata, dts.ExperimentalValueArray):
ydata = np.asarray(ydata) if isinstance(ydata,
ARRAY_TYPES) else np.empty(0)
if xdata.size and ydata.size and model:
return fit_to_xy_dataset(dts.XYDataSet(xdata, ydata, **kwargs), model,
**kwargs)
return None
def fit_target_dataset(self) -> dts.XYDataSet:
bins = self.bin_edges
xvalues = [(bins[i] + bins[i + 1]) / 2 for i in range(len(bins) - 1)]
return dts.XYDataSet(xvalues, self.n, name="histogram")