# Copyright (c) 2024 zfit
from __future__ import annotations
from typing import Callable, Mapping, Optional
from ..core.interfaces import ZfitPDF
from ..core.space import convert_to_space
from . import ztyping
from .checks import RuntimeDependency
from .exception import WorkInProgressError
from .warnings import warn_experimental_feature
try:
import matplotlib.pyplot as plt
except ImportError as error:
plt = RuntimeDependency("plt", error_msg=str(error))
[docs]
def plot_sumpdf_components_pdfV1(
model,
*,
plotfunc: Optional[Callable] = None,
scale=1,
ax=None,
linestyle=None,
plotkwargs: Mapping[str, object] | None = None,
):
"""Plot the components of a sum pdf.
Args:
model: A zfit SumPDF.
plotfunc: A plotting function that takes the `ax` to plot on x, y, and additional arguments.
scale: An overall scale factor to apply to the components.
ax: A matplotlib Axes object to plot on.
linestyle: A linestyle to use for the components. Default is "--".
plotkwargs: Additional keyword arguments to pass to the plotting function.
"""
import zfit
if not isinstance(model, zfit.pdf.SumPDF):
msg = f"model must be a ZfitPDF, not a {type(model)}. Model is {model}."
raise ValueError(msg)
if linestyle is None:
linestyle = "--"
if plotkwargs is None:
plotkwargs = {}
plotfunc = plot_model_pdfV1 if plotfunc is None else plotfunc
for mod, frac in zip(model.pdfs, model.params.values()):
plotfunc(mod, scale=frac * scale, ax=ax, linestyle=linestyle, plotkwargs=plotkwargs)
return ax
[docs]
def plot_model_pdfV1(
model: ZfitPDF,
*,
plotfunc: Callable | None = None,
extended: bool | None = None,
obs: ztyping.ObsTypeInput = None,
scale: float | int | None = None,
ax: plt.Axes | None = None,
num: int | None = None,
full: bool | None = None,
linestyle=None,
plotkwargs=None,
):
"""Plot the 1 dimensional density of a model, possibly scaled by the yield if extended.
Args:
model: An unbinned ZfitPDF.
plotfunc: A plotting function that takes the ``ax`` to plot on, and x, y, and additional arguments. Default is ``ax.plot``.
extended: If True, plot the extended pdf. If False, plot the pdf.
obs: The observable to plot the pdf for. If None, the model's space is used.
scale: An overall scale factor to apply to the pdf.
ax: A matplotlib Axes object to plot on.
num: The number of points to evaluate the pdf at. Default is 300.
full: If True, set the x and y labels and the legend. Default is True.
linestyle: A linestyle to use for the pdf.
plotkwargs: Additional keyword arguments to pass to the plotting function.
Returns:
"""
import zfit.z.numpy as znp
if not isinstance(model, ZfitPDF):
msg = f"model must be a ZfitPDF, not a {type(model)}. Model is {model}."
raise TypeError(msg)
if extended is None:
extended = model.is_extended
if scale is None:
scale = 1
if num is None:
num = 300
if full is None:
full = True
if plotkwargs is None:
plotkwargs = {}
if obs is None:
obs = model.space
if not obs.has_limits:
msg = "Observables must have limits to be plotted. Either provide the limits with `obs` or use a model that has limits."
raise ValueError(msg)
else:
obs = convert_to_space(obs)
if not obs.has_limits:
obs = model.space.with_obs(obs)
if not obs.has_limits:
msg = "Observables must have limits to be plotted. Either provide the limits with `obs` or use a model that has limits."
raise ValueError(msg)
if obs.n_obs != 1:
msg = "obs must be 1D to be plotted."
raise ValueError(msg)
if model.space.n_obs != 1:
if obs is None:
msg = "1D space must be provided for multi-dimensional models to provide a 1D projection."
raise ValueError(msg)
model = model.create_projection_pdf(obs=obs, label=model.label)
lower, upper = obs.v1.limits
x = znp.linspace(lower, upper, num=num)
y = model.ext_pdf(x) if extended else model.pdf(x)
y *= scale
if ax is None:
ax = plt.gca()
elif not isinstance(ax, plt.Axes):
msg = "ax must be a matplotlib Axes object"
raise ValueError(msg)
plotfunc = ax.plot if plotfunc is None else plotfunc
if "label" not in plotkwargs and full:
plotkwargs["label"] = model.label
plotfunc(x, y, linestyle=linestyle, **plotkwargs)
if full:
ax.set_xlabel(obs.label)
ylabel = "Probability density" if not extended else "Extended probability density"
ax.set_ylabel(ylabel)
plt.legend()
return ax
def assert_initialized(func):
def wrapper(self, *args, **kwargs):
if self.pdf is None:
msg = "PDFPlotter is not initialized with a PDF."
raise ValueError(msg)
return func(self, *args, **kwargs)
return wrapper
class ZfitPDFPlotter:
@warn_experimental_feature
@assert_initialized
def plotpdf(
self,
*,
plotfunc: Callable | None = None,
extended: bool | None = None,
obs: ztyping.ObsTypeInput = None,
scale: float | int | None = None,
ax: plt.Axes | None = None,
num: int | None = None,
full: bool | None = None,
linestyle=None,
plotkwargs=None,
):
"""Plot the 1 dimensional density of the PDF, possibly scaled by the yield if extended.
Args:
plotfunc: A plotting function that takes the `ax` to plot on, and x, y, and additional arguments. Default is `ax.plot`.
extended: If True, plot the extended pdf. If False, plot the pdf.
obs: The observable to plot the pdf for. If None, the model's space is used.
scale: An overall scale factor to apply to the pdf.
ax: A matplotlib Axes object to plot on.
num: The number of points to evaluate the pdf at. Default is 300.
full: If True, set the x and y labels and the legend. Default is True.
linestyle: A linestyle to use for the pdf.
plotkwargs: Additional keyword arguments to pass to the plotting function.
Returns:
The matplotlib Axes object.
"""
return self._plotpdf(
plotfunc=plotfunc,
extended=extended,
obs=obs,
scale=scale,
ax=ax,
num=num,
full=full,
linestyle=linestyle,
plotkwargs=plotkwargs,
)
def _plotpdf(self, **kwargs):
raise NotImplementedError
@property
def comp(self):
return None
class PDFPlotter(ZfitPDFPlotter):
def __init__(
self,
pdf: ZfitPDF | None,
pdfplotter: Callable | None = None,
componentplotter: ZfitPDFPlotter = None,
defaults: Mapping[str, object] | None = None,
):
self.defaults = {} if defaults is None else defaults
self.pdf = pdf
if pdfplotter is not None and not callable(pdfplotter):
msg = f"pdfplotter must be a callable, is {type(pdfplotter)}."
raise TypeError(msg)
self._pdfplotter = plot_model_pdfV1 if pdfplotter is None else pdfplotter
if componentplotter is not None and not isinstance(componentplotter, ZfitPDFPlotter):
msg = f"componentplotter must be a ZfitPDFPlotter, is {type(componentplotter)}."
raise TypeError(msg)
self._componentplotter = componentplotter
def __call__(self):
msg = "This is not yet implemented. Use the methods instead."
raise WorkInProgressError(msg)
def _plotpdf(self, **kwargs):
kwargs |= self.defaults
return plot_model_pdfV1(self.pdf, **kwargs)
@property
@assert_initialized
def comp(self):
return self._componentplotter
class SumCompPlotter(ZfitPDFPlotter):
def __init__(
self,
pdf: ZfitPDF | None,
*args,
**kwargs,
):
if pdf is not None and not isinstance(pdf, ZfitPDF):
msg = f"pdf must be a ZfitPDF, is {type(pdf)}."
raise TypeError(msg)
self.pdf = pdf
super().__init__(*args, **kwargs)
def _plotpdf(self, **kwargs):
import zfit
if not isinstance(pdf := self.pdf, zfit.pdf.SumPDF): # we can relax this later with duck typing
msg = f"pdf must be a SumPDF, is {type(pdf)}."
raise TypeError(msg)
scale = kwargs.pop("scale")
if scale is None:
scale = 1
for mod, frac in zip(pdf.pdfs, pdf.params.values()):
ax = mod.plot.plotpdf(scale=frac * scale, **kwargs)
return ax
