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Refacor/plotting #183

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36db247
feat(distributions): refactor plotting methods to use DistributionPlo…
MAfarrag Apr 16, 2026
1e59117
feat(distributions): refactor plotting methods to use DistributionPlo…
MAfarrag Apr 16, 2026
21d5ff8
feat(distributions): refactor plotting methods to use DistributionPlo…
MAfarrag Apr 16, 2026
4f1d868
merge main
MAfarrag Apr 23, 2026
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2 changes: 2 additions & 0 deletions src/statista/distributions/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,7 @@
from statista.distributions.normal import Normal
from statista.distributions.parameters import Parameters
from statista.distributions.goodness_of_fit import GoodnessOfFitResult
from statista.distributions.plot import DistributionPlot

__all__ = [
"AbstractDistribution",
Expand All @@ -19,4 +20,5 @@
"Distributions",
"Parameters",
"GoodnessOfFitResult",
"DistributionPlot",
]
6 changes: 3 additions & 3 deletions src/statista/distributions/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@
from statista.distributions.parameters import Parameters
from statista.distributions.goodness_of_fit import GoodnessOfFitResult
from statista.exceptions import ParameterError
from statista.plot import Plot
from statista.distributions.plot import DistributionPlot
from statista.utils import merge_small_bins

ninf = 1e-5
Expand Down Expand Up @@ -341,7 +341,7 @@ def pdf(
qx = np.linspace(float(data_sorted[0]), 1.5 * float(data_sorted[-1]), 10000)
pdf_fitted = self.pdf(parameters=parameters, data=qx)

fig, ax = Plot.pdf(
fig, ax = DistributionPlot.pdf(
qx,
pdf_fitted, # type: ignore[arg-type]
data_sorted,
Expand Down Expand Up @@ -434,7 +434,7 @@ def cdf(

cdf_weibul = PlottingPosition.weibul(data_sorted)

fig, ax = Plot.cdf(
fig, ax = DistributionPlot.cdf(
qx,
cdf_fitted, # type: ignore[arg-type]
data_sorted,
Expand Down
6 changes: 3 additions & 3 deletions src/statista/distributions/gev.py
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Expand Up @@ -23,7 +23,7 @@
from statista.distributions.parameters import Parameters
from statista.distributions.goodness_of_fit import GoodnessOfFitResult
from statista.parameters import Lmoments
from statista.plot import Plot
from statista.distributions.plot import DistributionPlot


class GEV(AbstractDistribution):
Expand Down Expand Up @@ -695,7 +695,7 @@ def confidence_interval( # type: ignore[override]

if plot_figure:
qth = self._inv_cdf(prob_non_exceed, parameters) # type: ignore[arg-type]
fig, ax = Plot.confidence_level(
fig, ax = DistributionPlot.confidence_level(
qth, self.data, q_lower, q_upper, alpha=alpha, **kwargs # type: ignore[arg-type]
)
return q_upper, q_lower, fig, ax
Expand Down Expand Up @@ -786,7 +786,7 @@ def plot(
pdf_fitted: Any = self.pdf(parameters=parameters, data=q_x)
cdf_fitted: Any = self.cdf(parameters=parameters, data=q_x)

fig, ax = Plot.details(
fig, ax = DistributionPlot.details(
q_x,
self.data,
pdf_fitted,
Expand Down
6 changes: 3 additions & 3 deletions src/statista/distributions/gumbel.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,7 @@
from statista.distributions.parameters import Parameters
from statista.distributions.goodness_of_fit import GoodnessOfFitResult
from statista.parameters import Lmoments
from statista.plot import Plot
from statista.distributions.plot import DistributionPlot


class Gumbel(AbstractDistribution):
Expand Down Expand Up @@ -1135,7 +1135,7 @@ def confidence_interval( # type: ignore[override]
if len(prob_non_exceed) != len(self.data):
raise ValueError(PROB_NON_EXCEEDENCE_ERROR)

fig, ax = Plot.confidence_level(
fig, ax = DistributionPlot.confidence_level(
qth, self.data, q_lower, q_upper, alpha=alpha, **kwargs # type: ignore[arg-type]
)
return q_upper, q_lower, fig, ax
Expand Down Expand Up @@ -1229,7 +1229,7 @@ def plot(
pdf_fitted: Any = self.pdf(parameters=parameters, data=q_x)
cdf_fitted: Any = self.cdf(parameters=parameters, data=q_x)

fig, ax = Plot.details(
fig, ax = DistributionPlot.details(
q_x,
self.data,
pdf_fitted,
Expand Down
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