def plot_band(line_kws: Dict[str, Any] = None,
fill_kws: Dict[str, Any] = None,
y_min: Optional[float] = None,
**kwargs) -> Axes:
"""Plots gvar as a band.
Arguments:
line_kws: Kwargs specific for line plot
fill_kws: Kwargs specific for fill between
y_min: Minimal value for data
kwargs: Shared kwargs
Requires: x and y1, ym, y2
"""
line_kws = line_kws.copy() or {}
fill_kws = fill_kws.copy() or {}
y1 = kwargs.pop("y1")
ym = kwargs.pop("ym")
y2 = kwargs.pop("y2")
if y_min is not None:
y1 = where(y1 < y_min, y_min, y1)
ym = where(ym < y_min, y_min, ym)
x = kwargs.pop("x")
ax = kwargs.pop("ax", get_current_actor())
line_kws.update(kwargs)
fill_kws.update(kwargs)
ax.plot(x, ym, **line_kws)
ax.fill_between(x, y1, y2, **fill_kws)
return ax
def plot_band(
line_kws: Dict[str, Any] = None, fill_kws: Dict[str, Any] = None, **kwargs
) -> Axes:
"""Plots gvar as a band.
Arguments:
line_kws: Kwargs specific for line plot
fill_kws: Kwargs specific for fill between
kwargs: Shared kwargs
Requires: x and y1, ym, y2
"""
line_kws = line_kws.copy() or {}
fill_kws = fill_kws.copy() or {}
y1 = kwargs.pop("y1")
ym = kwargs.pop("ym")
y2 = kwargs.pop("y2")
x = kwargs.pop("x")
ax = kwargs.pop("ax", get_current_actor())
line_kws.update(kwargs)
fill_kws.update(kwargs)
ax.plot(x, ym, **line_kws)
ax.fill_between(x, y1, y2, **fill_kws)
return ax
def plot_posterior_fit(**kwargs):
"""Fits normal distribution to ensemble and plots normal dist as well as hist
"""
ax = get_current_actor()
x = kwargs["data"].x.values
distplot(a=x, kde=False, ax=ax, hist_kws={"density": True})
plot_gv_dist(fit_norm_dist_to_ens(x, thresh=kwargs.get("thresh", None)),
ax=ax,
color="black")
def plot_gv_dist(gvar: NormalDistVar, **kwargs):
"""Plots pdf of gvar
"""
ax = kwargs.pop("ax", get_current_actor())
normal = gv_to_dist(gvar)
x = linspace(normal.ppf(0.001), normal.ppf(0.999), 100)
y_fit = normal.pdf(x)
ax.plot(x, y_fit, **kwargs)
return ax
def plot_prior_fit(**kwargs):
"""Parses distribution from meta parameters and plots exact distribution and
normal fit
"""
data = kwargs["data"].iloc[0].to_dict()
dist = parse_dist(data)
ax = get_current_actor()
x = linspace(dist.ppf(0.001), dist.ppf(0.999), 100)
y = dist.pdf(x)
ax.fill_between(x, y, alpha=0.5)
plot_gv_dist(fit_norm_dist_to_dist(dist), color="black")