use preliz style (#509)

* use preliz style * small fix
arviz-devs · Aug 5, 2024 · 4f376fc · 4f376fc
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diff --git a/docs/examples/gallery/asymmetric_laplace.md b/docs/examples/gallery/asymmetric_laplace.md
@@ -26,9 +26,9 @@ mystnb:
     alt: AsymmetricLaplace Distribution PDF
 ---
 
-import arviz as az
-from preliz import AsymmetricLaplace
-az.style.use('arviz-doc')
+
+from preliz import AsymmetricLaplace, style
+style.use('preliz-doc')
 kappas = [1., 2., .5]
 mus = [0., 0., 3.]
 bs = [1., 1., 1.]

diff --git a/docs/examples/gallery/beta.md b/docs/examples/gallery/beta.md
@@ -25,9 +25,8 @@ mystnb:
 ---
 
 import matplotlib.pyplot as plt
-import arviz as az
-from preliz import Beta
-az.style.use('arviz-doc')
+from preliz import Beta, style
+style.use('preliz-doc')
 alphas = [.5, 5., 2.]
 betas = [.5, 5., 5.]
 for alpha, beta in zip(alphas, betas):

diff --git a/docs/examples/gallery/beta_scaled.md b/docs/examples/gallery/beta_scaled.md
@@ -24,9 +24,9 @@ mystnb:
     alt: Beta Scaled Distribution PDF
 ---
 
-import arviz as az
-from preliz import BetaScaled
-az.style.use('arviz-doc')
+
+from preliz import BetaScaled, style
+style.use('preliz-doc')
 alphas = [2, 2]
 betas = [2, 5]
 lowers = [-0.5, -1]

diff --git a/docs/examples/gallery/cauchy.md b/docs/examples/gallery/cauchy.md
@@ -24,9 +24,9 @@ tags: [remove-input]
 mystnb: image
 ---
 import matplotlib.pyplot as plt
-import arviz as az
-from preliz import Cauchy
-az.style.use('arviz-doc')
+
+from preliz import Cauchy, style
+style.use('preliz-doc')
 alphas = [0., 0., -2.]
 betas = [1, 0.5, 1]
 for alpha, beta in zip(alphas, betas):

diff --git a/docs/examples/gallery/censored.md b/docs/examples/gallery/censored.md
@@ -25,9 +25,9 @@ mystnb:
     alt: Censored Distribution PDF
 ---
 
-import arviz as az
-from preliz import Normal, Censored
-az.style.use('arviz-doc')
+
+from preliz import Normal, Censored, style
+style.use('preliz-doc')
 Censored(Normal(0, 1), -1, 1).plot_pdf(support=(-4, 4))
 Normal(0, 1).plot_pdf(alpha=0.5);
 ```

diff --git a/docs/examples/gallery/chisquared.md b/docs/examples/gallery/chisquared.md
@@ -25,9 +25,9 @@ mystnb:
 ---
 
 import numpy as np
-import arviz as az
-from preliz import ChiSquared
-az.style.use('arviz-doc')
+
+from preliz import ChiSquared, style
+style.use('preliz-doc')
 nus = [1, 3, 9]
 
 for nu in nus:

diff --git a/docs/examples/gallery/exponential.md b/docs/examples/gallery/exponential.md
@@ -27,9 +27,9 @@ mystnb:
 ---
 
 import matplotlib.pyplot as plt
-import arviz as az
-from preliz import Exponential
-az.style.use('arviz-doc')
+
+from preliz import Exponential, style
+style.use('preliz-doc')
 lambdas = [0.5, 1., 2.]
 
 for lam in lambdas:

diff --git a/docs/examples/gallery/gamma.md b/docs/examples/gallery/gamma.md
@@ -26,9 +26,9 @@ mystnb:
     alt: Gamma Distribution PDF
 ---
 
-import arviz as az
-from preliz import Gamma
-az.style.use('arviz-doc')
+
+from preliz import Gamma, style
+style.use('preliz-doc')
 alphas = [1, 3, 7.5]
 betas = [0.5, 1., 1.]
 

diff --git a/docs/examples/gallery/log_normal.md b/docs/examples/gallery/log_normal.md
@@ -25,9 +25,8 @@ mystnb:
 ---
 
 import matplotlib.pyplot as plt
-import arviz as az
-from preliz import LogNormal
-az.style.use('arviz-doc')
+from preliz import style, LogNormal
+style.use('preliz-doc')
 mus = [0., 0., 0.]
 sigmas = [0.25, 0.5, 1.]
 for mu, sigma in zip(mus, sigmas):

diff --git a/docs/examples/gallery/logistic.md b/docs/examples/gallery/logistic.md
@@ -27,9 +27,9 @@ mystnb:
 ---
 
 import matplotlib.pyplot as plt
-import arviz as az
-from preliz import Logistic
-az.style.use('arviz-doc')
+
+from preliz import Logistic, style
+style.use('preliz-doc')
 mus = [0., 0., -2.]
 ss = [1., 2., .4]
 for mu, s in zip(mus, ss):

diff --git a/docs/examples/gallery/normal.md b/docs/examples/gallery/normal.md
@@ -27,9 +27,9 @@ mystnb:
 ---
 
 import matplotlib.pyplot as plt
-import arviz as az
-from preliz import Normal
-az.style.use('arviz-doc')
+
+from preliz import Normal, style
+style.use('preliz-doc')
 mus = [0., 0., -2.]
 sigmas = [1, 0.5, 1]
 for mu, sigma in zip(mus, sigmas):

diff --git a/docs/examples/gallery/poisson.md b/docs/examples/gallery/poisson.md
@@ -23,9 +23,9 @@ mystnb:
     alt: Poisson Distribution PDF
 ---
 
-import arviz as az
-from preliz import Poisson
-az.style.use('arviz-doc')
+
+from preliz import Poisson, style
+style.use('preliz-doc')
 for mu in [0.5, 3, 8]:
     Poisson(mu).plot_pdf();
 ```

diff --git a/docs/examples/gallery/students_t.md b/docs/examples/gallery/students_t.md
@@ -27,9 +27,9 @@ mystnb:
 ---
 
 import matplotlib.pyplot as plt
-import arviz as az
-from preliz import StudentT
-az.style.use('arviz-doc')
+
+from preliz import StudentT, style
+style.use('preliz-doc')
 nus = [2., 5., 5.]
 mus = [0., 0.,  -4.]
 sigmas = [1., 1., 2.]

diff --git a/docs/examples/gallery/truncated.md b/docs/examples/gallery/truncated.md
@@ -24,9 +24,9 @@ mystnb:
     alt: Truncated Distribution PDF
 ---
 
-import arviz as az
-from preliz import Gamma, Truncated
-az.style.use('arviz-doc')
+
+from preliz import Gamma, Truncated, style
+style.use('preliz-doc')
 Truncated(Gamma(mu=2, sigma=1), 1, 4.5).plot_pdf()
 Gamma(mu=2, sigma=1).plot_pdf();
 ```

diff --git a/docs/examples/gallery/uniform.md b/docs/examples/gallery/uniform.md
@@ -27,9 +27,9 @@ mystnb:
 ---
 
 import matplotlib.pyplot as plt
-import arviz as az
-from preliz import Uniform
-az.style.use('arviz-doc')
+
+from preliz import Uniform, style
+style.use('preliz-doc')
 ls = [1, -2]
 us = [6, 2]
 for l, u in zip(ls, us):

diff --git a/docs/examples/img/AsymmetricLaplace.png b/docs/examples/img/AsymmetricLaplace.png
diff --git a/docs/examples/img/Bernoulli.png b/docs/examples/img/Bernoulli.png
diff --git a/docs/examples/img/Beta.png b/docs/examples/img/Beta.png
diff --git a/docs/examples/img/BetaBinomial.png b/docs/examples/img/BetaBinomial.png
diff --git a/docs/examples/img/BetaScaled.png b/docs/examples/img/BetaScaled.png
diff --git a/docs/examples/img/Binomial.png b/docs/examples/img/Binomial.png
diff --git a/docs/examples/img/Categorical.png b/docs/examples/img/Categorical.png
diff --git a/docs/examples/img/Cauchy.png b/docs/examples/img/Cauchy.png
diff --git a/docs/examples/img/Censored.png b/docs/examples/img/Censored.png
diff --git a/docs/examples/img/ChiSquared.png b/docs/examples/img/ChiSquared.png
diff --git a/docs/examples/img/DiscreteUniform.png b/docs/examples/img/DiscreteUniform.png
diff --git a/docs/examples/img/DiscreteWeibull.png b/docs/examples/img/DiscreteWeibull.png
diff --git a/docs/examples/img/ExGaussian.png b/docs/examples/img/ExGaussian.png
diff --git a/docs/examples/img/Exponential.png b/docs/examples/img/Exponential.png
diff --git a/docs/examples/img/Gamma.png b/docs/examples/img/Gamma.png
diff --git a/docs/examples/img/Geometric.png b/docs/examples/img/Geometric.png
diff --git a/docs/examples/img/Gumbel.png b/docs/examples/img/Gumbel.png
diff --git a/docs/examples/img/HalfCauchy.png b/docs/examples/img/HalfCauchy.png
diff --git a/docs/examples/img/HalfNormal.png b/docs/examples/img/HalfNormal.png
diff --git a/docs/examples/img/HalfStudentT.png b/docs/examples/img/HalfStudentT.png
diff --git a/docs/examples/img/Hurdle.png b/docs/examples/img/Hurdle.png
diff --git a/docs/examples/img/HyperGeometric.png b/docs/examples/img/HyperGeometric.png
diff --git a/docs/examples/img/InverseGamma.png b/docs/examples/img/InverseGamma.png
diff --git a/docs/examples/img/Kumaraswamy.png b/docs/examples/img/Kumaraswamy.png
diff --git a/docs/examples/img/Laplace.png b/docs/examples/img/Laplace.png
diff --git a/docs/examples/img/LogLogistic.png b/docs/examples/img/LogLogistic.png
diff --git a/docs/examples/img/LogNormal.png b/docs/examples/img/LogNormal.png
diff --git a/docs/examples/img/Logistic.png b/docs/examples/img/Logistic.png
diff --git a/docs/examples/img/LogitNormal.png b/docs/examples/img/LogitNormal.png
diff --git a/docs/examples/img/Moyal.png b/docs/examples/img/Moyal.png
diff --git a/docs/examples/img/NegativeBinomial.png b/docs/examples/img/NegativeBinomial.png
diff --git a/docs/examples/img/Normal.png b/docs/examples/img/Normal.png
diff --git a/docs/examples/img/Pareto.png b/docs/examples/img/Pareto.png
diff --git a/docs/examples/img/Poisson.png b/docs/examples/img/Poisson.png
diff --git a/docs/examples/img/Rice.png b/docs/examples/img/Rice.png
diff --git a/docs/examples/img/SkewNormal.png b/docs/examples/img/SkewNormal.png
diff --git a/docs/examples/img/SkewStudentT.png b/docs/examples/img/SkewStudentT.png
diff --git a/docs/examples/img/StudentT.png b/docs/examples/img/StudentT.png
diff --git a/docs/examples/img/Triangular.png b/docs/examples/img/Triangular.png
diff --git a/docs/examples/img/Truncated.png b/docs/examples/img/Truncated.png
diff --git a/docs/examples/img/TruncatedNormal.png b/docs/examples/img/TruncatedNormal.png
diff --git a/docs/examples/img/Uniform.png b/docs/examples/img/Uniform.png
diff --git a/docs/examples/img/VonMises.png b/docs/examples/img/VonMises.png
diff --git a/docs/examples/img/Wald.png b/docs/examples/img/Wald.png
diff --git a/docs/examples/img/Weibull.png b/docs/examples/img/Weibull.png
diff --git a/docs/examples/img/ZeroInflatedBinomial.png b/docs/examples/img/ZeroInflatedBinomial.png
diff --git a/docs/examples/img/ZeroInflatedNegativeBinomial.png b/docs/examples/img/ZeroInflatedNegativeBinomial.png
diff --git a/docs/examples/img/ZeroInflatedPoisson.png b/docs/examples/img/ZeroInflatedPoisson.png
diff --git a/docs/examples/observed_space_examples.rst b/docs/examples/observed_space_examples.rst
@@ -3,16 +3,16 @@ Predictive Elicitation
 
 .. code-block:: python
 
-    import arviz as az
+    
     import preliz as pz
     import numpy as np
     import pandas as pd
 
 .. code-block:: python
 
-    az.style.library["arviz-doc"]["figure.dpi"] = 100
-    az.style.library["arviz-doc"]["figure.figsize"] = (10, 4)
-    az.style.use("arviz-doc")
+    pz.style.library["preliz-doc"]["figure.dpi"] = 100
+    pz.style.library["preliz-doc"]["figure.figsize"] = (10, 4)
+    pz.style.use("preliz-doc")
 
 Predictive elicitation refers to the elicitation of priors by making evaluations on the observed space, instead of the parameters space. The advantage of the former is that generally it is easier to think about observations than parameters, specially for domain experts. If you are a forest engineer, you may be more familiar with the expected rate of wildfires in an area than with the ``rho`` parameter of a model.
 

diff --git a/docs/examples/param_space_1d_examples.ipynb b/docs/examples/param_space_1d_examples.ipynb
diff --git a/docs/get_cover_gallery.py b/docs/get_cover_gallery.py
@@ -1,13 +1,14 @@
 # pylint: disable=invalid-name
 import matplotlib.pyplot as plt
-import arviz as az
+
 import numpy as np
 from preliz import Gamma
 from preliz import distributions
+from preliz import style
 from preliz.internal.distribution_helper import init_vals
 
 
-az.style.use("arviz-doc")
+style.use("preliz-doc")
 rng = np.random.default_rng(247)
 
 init_vals["Hurdle"] = None

diff --git a/docs/get_cover_gallery_multivariate.py b/docs/get_cover_gallery_multivariate.py
@@ -1,10 +1,10 @@
 # pylint: disable=invalid-name
 import matplotlib.pyplot as plt
-import arviz as az
+
 import numpy as np
-from preliz import Dirichlet, MvNormal
+from preliz import style, Dirichlet, MvNormal
 
-az.style.use("arviz-doc")
+style.use("preliz-doc")
 
 w = 1834 / 300
 h = 1234 / 300

diff --git a/preliz/__init__.py b/preliz/__init__.py
@@ -4,8 +4,10 @@
 Tools to help you pick a prior
 """
 import logging
+from os import path as os_path
 
 from matplotlib import rcParams
+from matplotlib import style
 
 from .distributions import *
 from .predictive import *
@@ -27,3 +29,9 @@
 # Allow legend outside plot in maxent to be included when saving a figure
 # We may want to make this more explicit by having preliz.rcParams
 rcParams["savefig.bbox"] = "tight"
+
+
+# add PreliZ's styles to matplotlib's styles
+_preliz_style_path = os_path.join(os_path.dirname(__file__), "styles")
+style.core.USER_LIBRARY_PATHS.append(_preliz_style_path)
+style.core.reload_library()
diff --git a/preliz/distributions/asymmetric_laplace.py b/preliz/distributions/asymmetric_laplace.py
@@ -27,9 +27,9 @@ class AsymmetricLaplace(Continuous):
     .. plot::
         :context: close-figs
 
-        import arviz as az
-        from preliz import AsymmetricLaplace
-        az.style.use('arviz-doc')
+
+        from preliz import AsymmetricLaplace, style
+        style.use('preliz-doc')
         kappas = [1., 2., .5]
         mus = [0., 0., 3.]
         bs = [1., 1., 1.]

diff --git a/preliz/distributions/bernoulli.py b/preliz/distributions/bernoulli.py
@@ -21,9 +21,9 @@ class Bernoulli(Discrete):
     .. plot::
         :context: close-figs
 
-        import arviz as az
-        from preliz import Bernoulli
-        az.style.use('arviz-doc')
+
+        from preliz import Bernoulli, style
+        style.use('preliz-doc')
         for p in [0, 0.5, 0.8]:
             Bernoulli(p).plot_pdf()
 

diff --git a/preliz/distributions/beta.py b/preliz/distributions/beta.py
@@ -34,9 +34,9 @@ class Beta(Continuous):
     .. plot::
         :context: close-figs
 
-        import arviz as az
-        from preliz import Beta
-        az.style.use('arviz-doc')
+        
+        from preliz import Beta, style
+        style.use('preliz-doc')
         alphas = [.5, 5., 2.]
         betas = [.5, 5., 5.]
         for alpha, beta in zip(alphas, betas):

diff --git a/preliz/distributions/betabinomial.py b/preliz/distributions/betabinomial.py
@@ -30,9 +30,9 @@ class BetaBinomial(Discrete):
     .. plot::
         :context: close-figs
 
-        import arviz as az
-        from preliz import BetaBinomial
-        az.style.use('arviz-doc')
+
+        from preliz import BetaBinomial, style
+        style.use('preliz-doc')
         alphas = [0.5, 1, 2.3]
         betas = [0.5, 1, 2]
         n = 10

diff --git a/preliz/distributions/betascaled.py b/preliz/distributions/betascaled.py
@@ -32,9 +32,9 @@ class BetaScaled(Continuous):
     .. plot::
         :context: close-figs
 
-        import arviz as az
-        from preliz import BetaScaled
-        az.style.use('arviz-doc')
+
+        from preliz import BetaScaled, style
+        style.use('preliz-doc')
         alphas = [2, 2]
         betas = [2, 5]
         lowers = [-0.5, -1]

diff --git a/preliz/distributions/binomial.py b/preliz/distributions/binomial.py
@@ -25,9 +25,9 @@ class Binomial(Discrete):
     .. plot::
         :context: close-figs
 
-        import arviz as az
-        from preliz import Binomial
-        az.style.use('arviz-doc')
+
+        from preliz import Binomial, style
+        style.use('preliz-doc')
         ns = [5, 10, 10]
         ps = [0.5, 0.5, 0.7]
         for n, p in zip(ns, ps):

diff --git a/preliz/distributions/categorical.py b/preliz/distributions/categorical.py
@@ -20,9 +20,9 @@ class Categorical(Discrete):
     .. plot::
         :context: close-figs
 
-        import arviz as az
-        from preliz import Categorical
-        az.style.use('arviz-doc')
+
+        from preliz import Categorical, style
+        style.use('preliz-doc')
         ps = [[0.1, 0.6, 0.3], [0.3, 0.1, 0.1, 0.5]]
         for p in ps:
             Categorical(p).plot_pdf()

diff --git a/preliz/distributions/cauchy.py b/preliz/distributions/cauchy.py
@@ -23,9 +23,9 @@ class Cauchy(Continuous):
     .. plot::
         :context: close-figs
 
-        import arviz as az
-        from preliz import Cauchy
-        az.style.use('arviz-doc')
+
+        from preliz import Cauchy, style
+        style.use('preliz-doc')
         alphas = [0., 0., -2.]
         betas = [.5, 1., 1.]
         for alpha, beta in zip(alphas, betas):

diff --git a/preliz/distributions/censored.py b/preliz/distributions/censored.py
@@ -29,9 +29,9 @@ class Censored(DistributionTransformer):
     .. plot::
         :context: close-figs
 
-        import arviz as az
-        from preliz import Normal, Censored
-        az.style.use('arviz-doc')
+        
+        from preliz import Normal, Censored, style
+        style.use('preliz-doc')
         Censored(Normal(0, 1), -1, 1).plot_pdf(support=(-4, 4))
         Normal(0, 1).plot_pdf(alpha=0.5)
         

diff --git a/preliz/distributions/chi_squared.py b/preliz/distributions/chi_squared.py
@@ -25,9 +25,9 @@ class ChiSquared(Continuous):
     .. plot::
         :context: close-figs
 
-        import arviz as az
-        from preliz import ChiSquared
-        az.style.use('arviz-doc')
+
+        from preliz import ChiSquared, style
+        style.use('preliz-doc')
         nus = [1., 3., 9.]
         for nu in nus:
                 ax = ChiSquared(nu).plot_pdf(support=(0,20))