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PyPI · #2507 most downloaded on PyPI
Expose features from _ArviZverse_ refactored packages together in the ``arviz`` namespace.
Last release 1 months ago
11 Aug 2026
Ships fairly regularly
a new release about every 2 months
Nearly every release is documented
notes for 46 of 48 stable releases
Nothing withdrawn
no release was ever pulled
8 years old
50 releases · first in 2018
Update deprecated git protocol to https in README by @b25cs1051-KUSH in #2597
Full Changelog: v1.2.0...v1.3.0
One column per quarter.
ArviZ 1.2 builds on the 1.0 release with incremental improvements and no major breaking changes.
ArviZ 1.2 builds on the 1.0 release with incremental improvements and no major breaking changes.
The 1.0 ArviZ introduced many breaking changes: See the migration guide for an overview of improvements and guidance on things that will break and how to update them.
For an overview of new features and fixes since the 1.0 release, see the respective changelogs: arviz-base, arviz-stats and arviz-plots
The whole library has been refactored for extra flexibility and modularity as well as reducing the cost of maintaining and adding new features to the library. arviz is now a metapackage that exposes all the common functions that are implemented in independent packages of the ArviZverse. For a detailed list of changes you can check the changelog of each of these packages.
Take a look at the online book on Exploratory Analysis of Bayesian Models to see it in action and at the docs of the 3 ArviZ packages: arviz-base, arviz-stats and arviz-plots (note all the objects at the top level namespace of these 3 libraries are also exposed as arviz.xyz)
Full Changelog: v1.1.0...v1.2.0
ArviZ 1.1 builds on the 1.0 release with incremental improvements and no major breaking changes.
ArviZ 1.1 builds on the 1.0 release with incremental improvements and no major breaking changes.
The 1.0 ArviZ introduced many breaking changes: See the migration guide for an overview of improvements and guidance on things that will break and how to update them.
The whole library has been refactored for extra flexibility and modularity as well as reducing the cost of maintaining and adding new features to the library. arviz is now a metapackage that exposes all the common functions that are implemented in independent packages of the ArviZverse. For a detailed list of changes you can check the changelog of each of these packages.
Take a look at the online book on Exploratory Analysis of Bayesian Models to see it in action and at the docs of the 3 ArviZ packages: arviz-base, arviz-stats and arviz-plots (note all the objects at the top level namespace of these 3 libraries are also exposed as arviz.xyz)
MigrationWarning instead of breaking InferenceData import by @michaelosthege in #2575Full Changelog: v1.0.0...v1.1.0
This 1.0 ArviZ release comes with many breaking changes: See the migration guide for an overview of improvements and guidance on things that will brea…
This 1.0 ArviZ release comes with many breaking changes: See the migration guide for an overview of improvements and guidance on things that will break and how to update them.
The whole library has been refactored for extra flexibility and modularity as well as reducing the cost of maintaining and adding new features to the library. arviz now exposes all the common functions which are implemented in independent packages of the ArviZverse. Take a look at the online book on Exploratory Analysis of Bayesian Models to see it in action and at the docs of the 3 ArviZ packages: arviz-base, arviz-stats and arviz-plots (note all the objects at the top level namespace of these 3 libraries are also exposed as arviz.xyz)
See the migration guide for an overview of improvements and the docs of the 3 arviz modules: arviz-base, arviz-stats and arviz-plots (all the objects
See the migration guide for an overview of improvements and the docs of the 3 arviz modules: arviz-base, arviz-stats and arviz-plots (all the objects at the top level namespace of these 3 libraries are also exposed as arviz.xyz)
Extra windows specific fix for once a day warning.
Extra windows specific fix for once a day warning.
Path release with improvements to the once a day warning at import time
Path release with improvements to the once a day warning at import time
Patch release to handle the recent 1.8 h5netcdf release. h5netcdf now has two potential backends, and one must be chosen explicitly to get an install
Patch release to handle the recent 1.8 h5netcdf release. h5netcdf now has two potential backends, and one must be chosen explicitly to get an install capable of reading/writing netcdf files.
Important We expect this to be the last 0.x ArviZ release. See the migration guide to read about what this will mean.
Important
We expect this to be the last 0.x ArviZ release. See the migration guide to read about what this will mean.
There hasn't been many changes since 0.22, the main ones are fixes in netcdf serialization for InferenceData and fixes to DataTree<->InferenceData conversions.
Full changelog available on GitHub.
The highlights of these release are interoperability of InferenceData and the new `xarray.DataTree` object and automatic inferring of dimension names
The highlights of these release are interoperability of InferenceData and the new xarray.DataTree object and automatic inferring of dimension names from plates in the numpyro converter.
We have also done more testing of the arviz.preview module. Take a look at the migration guide if you want an early peek to the changes and improvements to come. You can treat arviz.preview as a beta release of ArviZ 1.0 so use carefully and keep an eye on the development. We hope to have a release candidate available for wider user testing in a few months.
Full changelog available on GitHub.
plot_pair now has more flexible support for reference_values (2438)arviz.from_numpyro(..., dims=None) automatically infer dims from the numpyro model based on its numpyro.plate structurereference_values and labeller now work together in plot_pair (2437)plot_lm for multidimensional data (2408)scipy-stubs as a development dependency (2445)plot_kde (2460)fix docs right sidebar and bokeh deprecation warning by @OriolAbril in https://github.com/arviz-devs/arviz/pull/2405
dims and default_dims are provided by @lucianopaz in https://github.com/arviz-devs/arviz/pull/2395plot_hdi raise exception when x is string (#2412) by @milesalanmoore in https://github.com/arviz-devs/arviz/pull/2413InfereceData -> InferenceData by @star1327p in https://github.com/arviz-devs/arviz/pull/2428Full Changelog: https://github.com/arviz-devs/arviz/compare/v0.20.0...v0.21.0
arviz.data.generate_dims_coords handle dims and default_dims consistently (2395)InferenceData when explicitly requested (2401)az.plot_bf into az.bayes_factor (2402)method="sd" of mcse to not use normality assumption (2167)az.plot_hdi for x of type str (2413)The highlight this release is the addition of optimized simultaneous ECDF confidence bands. It also includes support for idata["new_group"] = dataset
The highlight this release is the addition of optimized simultaneous ECDF confidence bands. It also includes support for idata["new_group"] = dataset directly and several bug fixes and documentation improvements.
For users of arviz.from_pytree it will now be necessary to install dm-tree manually as it was only used in this one function and has been made an optional dependency.
Full changelog available on GitHub.
idata[group] (2374)dm-tree and optional dependency (2379)psislw modifying input inplace (2377)plot_compare more intuitive (2388)loo and waic (2366)This release highlights are: Work with Bokeh3, uses revised Pareto k threshold, refactor plot_ecdf arguments, expose new features as preview submodule
This release highlights are: Work with Bokeh3, uses revised Pareto k threshold, refactor plot_ecdf arguments, expose new features as preview submodule.
Full Changelog: https://github.com/arviz-devs/arviz/blob/main/CHANGELOG.md#v0190-2024-jul-19
ci_prob, eval_points, rvs, and random_state to plot_ecdf (2316)stats.hdi_prob and replaced with stats.ci_prob (2316)arviz.preview
submodule (2361)Ensure support with numpy 2.0 (2321)
Update testing strategy to include an environment without optional dependencies and an environment with scientific python nightlies (2321)
Address bokeh related deprecations (2362)
Fix legend overwriting issue in plot_trace (2334)
It also has bugfixes and addresses multiple deprecation warnings from dependencies that were being triggered.
This release highlights are support for nested dictionaries and pytrees in from_dict converter and data examples updates: it adds a new example data rugby_field with 4d variables and updates the rugby example to include log_prior and unconstrained_posterior groups.
It also has bugfixes and addresses multiple deprecation warnings from dependencies that were being triggered.
Full changelog available on GitHub.
rugby_field and update rugby example data (2322)pytrees and robust to nested dictionaries. (2291).close method to InferenceData (2338)values2, fpr, pointwise, npoints, and pit in plot_ecdf (2316)Patch release with a couple bug fixes, mainly plot_forest didn't work when latest numba was installed which has now been fixed.
Patch release with a couple bug fixes, mainly plot_forest didn't work when latest numba was installed which has now been fixed.
Full changelog available on GitHub.
This new release adds a couple new features, mainly support for prior/likelihood sensitivity checks via arviz.psens and several bugfix and documentati
This new release adds a couple new features, mainly support for prior/likelihood sensitivity checks via arviz.psens and several bugfix and documentation improvements.
Full changelog available on GitHub.
psens (2093)InfereceData.to_dataframemethod (2277)plot_ppc when dimension order isn't chain, draw, ... (2283)plot_ppc, plot_bpv, plot_loo_pit... when repeated. (2283)__delitem__ method to InferenceData (2292)This patch release includes numba related fixes to avoid triggering deprecations and improve behaviour overall.
This patch release includes numba related fixes to avoid triggering deprecations and improve behaviour overall.
Full changelog available on GitHub.
This new release adds several new features, mostly related to InferenceData I/O and maintenance and bugfix improvements.
This new release adds several new features, mostly related to InferenceData I/O and maintenance and bugfix improvements.
Full changelog available on GitHub.
az.to_zarr and az.from_zarr (2236)Fix memory usage and improve efficiency in from_emcee (2215)
Adds Savage-Dickey density ratio plot for Bayes factor approximation. (2037, 2152)
CmdStanPySamplingWrapper and PyMCSamplingWrapper classes (2158)reloo outdated usage of ELPDData (2158)plot_trace with option kind="rank_bars" (2180)plot_lm unsupported usage of np.tile (2186)_z_scale to work with SciPy 1.10 (2186)plot_trace with divergences (2151)Full Changelog: https://github.com/arviz-devs/arviz/compare/v0.14.0...v0.15.0
Fix dimension ordering for traceplot with divergences by @sethaxen in https://github.com/arviz-devs/arviz/pull/2151
Full Changelog: https://github.com/arviz-devs/arviz/compare/v0.13.0...0.14.0
weight_predictions function to allow generation of weighted predictions from two or more InfereceData with posterior_predictive groups and a set of weights (2147)plot_ppc. (2161)plot_trace with divergences (2151)Add side argument to plot_violin to allow single-sided violin plots (1996)
side argument to plot_violin to allow single-sided violin plots (1996)from_beanmachine. (2107)from_pystan for PyStan 3. (2132)arviz.extract function.fill_last, contour and plot_kwargs arguments from plot_pair function (2085)See full CHANGELOG.md file for a detailed release changes description.
side argument to plot_violin to allow single-sided violin plots (1996)from_beanmachine. (2107from_pystan for PyStan 3. (2132az.plot_hdi for x of type np.datetime64 and smooth=True (2016)ax.plot usage to ax.scatter in plot_pair (1990)contourpy package (2104)bfmi and plot_energy (2126)fill_last, contour and plot_kwargs arguments from plot_pair function (2085)Add side argument to plot_violin to allow single-sided violin plots (1996)
side argument to plot_violin to allow single-sided violin plots (1996)from_beanmachine. (2107)from_pystan for PyStan 3. (2132)arviz.extract function.fill_last, contour and plot_kwargs arguments from plot_pair function (2085)See full CHANGELOG.md file for a detailed release changes description.
Version 0.12.1 introduces a new argument to arviz.summary: stat_focus to choose between using the mean and highest density intervals or the median and
Version 0.12.1 introduces a new argument to arviz.summary: stat_focus to choose between using the mean and highest density intervals or the median and equal-tail intervals as summaries. It also has several doc improvements and bug fixes.
stat_focus argument to arviz.summary (1998)psislw now smooths log-weights even when shape is lower than 1/3(2011)from_cmdstanpy, handles parameter vectors of length 1 (2023)BaseLabeller that broke NoVarLabeller (2018)Add new convenience function arviz.extract_dataset (1725)
Change log
arviz.extract_dataset (1725)combine_dims argument to several functions (1676)InferenceData.from_netcdf with regex support (1749)plot_lmfrom_cmdstan log_likelihood parameter (as in from_pystan)plot_compare, plot_elpd can now take dicts of InferenceData or ELPDData (1690)stats.ic_pointwise to True (1690)DataFrame.append to pandas.concat (1973)plot_pair. (1985)plot_dist_comparison() in case subplots go over the limit (1688)Forestplot documentationFix standard deviation code in density utils
Patch release 0.11.4
np.std. (1833)Many small changes. Includes code from GSOC.
Patch release on v0.11.2.
Many small changes. Includes code from GSOC.
psislw (1943)labeller argument to enable label customization in plots and summary (1201)arviz.labels module with classes and utilities (1201 and 1605)plot_posterior (1570)rope_color and ref_val_color arguments to plot_posterior (1570)from_cmdstanpy, from_cmdstan and from_pystan (1579 and 1599)forestplot (1591)ppcplot (1602)InferenceData from NetCDF (1637)data.log_likelihood, stats.ic_compare_method and plot.density_kind to rcParams (1611)stats.compare(), and var_name parameter. (1616)plot_kde with the new hdi_probs parameter. (1665)index_origin with all the library (1201)from_cmdstanpy (1579)from_pystan converters to follow schema convention (1585DefaultTrace in from_pymc3 (1590)c argument in plot_khat (1592)ax argument in plot_elpd (1593)stats.py compare function (1607)ess/rhat plots in plot_forest (1606)from_numpyro crash when importing model with thinning=x for x > 1 (1619)InferenceData object is passed using io_pymc3's trace argument (1629)xlabels in plot_elpd (1601)sample dim to __sample__ when stacking chain and draw to avoid dimension collision (1647)circular argument in plot_dist in favor of is_circular (1681)legend argument in plot_separation (1701)plot_loo_pit (1745)filter_vars and filter_groups now raise ValueError if illegal arguments are passed (1772)index_origin and order arguments in az.summary (1201)arviz.labels module (1201 and 1635)SamplingWrapper classes (1582)plot_hdi using Inference Data (1615)geweke diagnostic from numba user guide (1653)The highlight of the release is updating the from_cmdstanpy to work with cmdstanpy>=0.9.68. The other changes are listed below
Patch release on v0.11.1.
The highlight of the release is updating the from_cmdstanpy to work with cmdstanpy>=0.9.68. The other changes are listed below
to_zarr and from_zarr methods to InferenceData (1518)from_cmdstanpy, from_cmdstan, from_numpyro and from_pymc3 converters to follow schema convention (1550, 1541, 1525 and 1555)from_cmdstan. csv reader, dtype problem fixed and dtype kwarg added for manual dtype casting (1565)coords argument in plot_posterior docstring (1566)See also detailed change log of v0.11.0
Patch release on v0.11.1. Changes are:
Patch release on v0.11.1. Changes are:
plot_pair labels that prevented coord names to be shown when necessary (1533)See also detailed change log of v0.11.0
plot_pair labels that prevented coord names to be shown when necessary (1533)plot_khat deprecate annotate argument in favor of threshold.
to_dataframe method, __getitem__ magic and copy method to InferenceDataref_line, bar, vlines and marker_vlines kwargs to plot_rankplot_ppcloo_pitcompare (1438)SamplingWrapper base APIfrom_pystan store attrs as strings to allow netCDF storageplot_tracecompact=True by default in our plotsfrom_pymc3 compatible with theano-pymc 1.1.0plot_khat deprecate annotate argument in favor of threshold.See detailed change log
to_dataframe method to InferenceData (1395)__getitem__ magic to InferenceData (1395)ref_line, bar, vlines and marker_vlines kwargs to plot_rank (1419)plot_ppc (1422)loo_pit (1500)skipna argument to plot_posterior (1432)compare (1438)copy() method to InferenceData class. (1501).compare (1412)distplot.py (1414)loo_pit extraction of log likelihood (1418)from_pystan store attrs as strings to allow netCDF storage (1417)plot_violin (1426 )plot_trace (1428)pair_plot for mixed discrete and continuous variables (1434)plot_compare (1435)plt_kde, plot_dist and plot_hdi (1452)compact=True by default in our plots (1468)plot_elpd, avoid modifying the input dict (1477)plot_trace when kind=rank_vlines or kind=rank_bars (1476)observed argument of pymc3.DensityDist in from_pymc3 (1495)from_pymc3 compatible with theano-pymc 1.1.0 (1495)plot_khat deprecate annotate argument in favor of threshold. The new argument accepts floats (1478)input_core_dims in hdi and plot_hdi docstrings (1410)SamplingWrappers usage (1373)sample_stats naming convention to the InferenceData schema (1063)InferenceData methods (1338)SamplingWrapper base API (1373)Added support for circular variables to several functions
InferenceData JSON converter and to_dict functionplot_separation for binary dataInferenceData capabilities for computation and combination of multiple objects.plot_bpvSee detailed change log
is_circular argument to plot_dist and plot_kde allowing for a circular histogram (Matplotlib, Bokeh) or 1D KDE plot (Matplotlib). (1266)to_dict method for InferenceData object (1223)circ_var_names argument to plot_trace allowing for circular traceplot (Matplotlib) (1336)hdi_prop level (1348)plot_separation (1359)xr.Dataset to InferenceData (1254)extend and add_groups to InferenceData (1300 and 1386)__iter__ method (.items) for InferenceData (1356)plot_bpv (#1379)plot_posterior fix overlap of hdi and rope (1263)plot_dist bins argument error fixed (1306)az.summary (1313)ELPDData string representation (1321)radon example dataset to current InferenceData schema specification (1320)from_cmdstan functionality and add warmup groups (1330 and 1351)_fast_kde() with kde() which now also supports circular variables via the argument circular (1284).from_pystan attrs information content (1353)plot_trace to return and accept axes (1361)scipy.stats.rankdata (1380)plot_parallel examples (1380)plot_forest (1390)from_dict will now store warmup groups even with the main group missing (1386)from_pymc3 without a model context available raises aFutureWarning and will be deprecated in a future version
loo-pit KDE and HDI were improvedhtml_repr of InferenceData objects for jupyter notebooksfrom_pymc3 automatically retrieves coords and dims from model contextplot_trace now supports multiple aesthetics to identify chain and variable shape and supports matplotlib aliasesplot_hdi can now take already computed HDI valuesfrom_pymc3 without a model context available raises aFutureWarning and will be deprecated in a future versionplot_trace, chain_prop and compact_prop as tuples will now raise a FutureWarninghdi with 2d data raises a FutureWarningSee detailed change log
html_repr of InferenceData objects for jupyter notebooks. (1217)from_pyjags. (1219 and 1245)from_pymc3 can now retrieve coords and dims from model context (1228, 1240 and 1249)plot_trace now supports multiple aesthetics to identify chain and variable
shape and support matplotlib aliases (1253)plot_hdi can now take already computed HDI values (1241)plot_bpv. A new plot for Bayesian p-values (1222)MultiObservedRV to observed_data when using
from_pymc3 (1098)plot_pair when trying to use plot_kde on InferenceData
objects. (1218)log_likelihood argument to from_pyro and a warning if log likelihood cannot be obtained (1227)plot_hdi and fixed matplotlib axes generation (1241)zorder of scatter points from 0 to 0.6 in plot_pair (1246)get_bins for numpy 1.19 compatibility (1256)rug, divergences arguments in plot_trace (1253)from_pymc3 without a model context available now raises a
FutureWarning and will be deprecated in a future version (1227)plot_trace, chain_prop and compact_prop as tuples will now raise a
FutureWarning (1253)hdi with 2d data raises a FutureWarning (1241)Third patch release on v0.8.0. Includes fixes on from_pymc3
from_pymc3 to handle old pymc3 releases and
sliced traces and to provide useful warnings (1211)Second patch release on v0.8.0. Includes fixes on from_pymc3
from_pymc3 for sliced pymc3.MultiTrace input (1209)Patch release on v0.8.0. Changes are:
Patch release on v0.8.0. Changes are:
See also detailed change log of v0.8.0
functions hpd and plot_hpd have been deprecated in favour of hdi and plot_hdi respectively
predictions and log_likelihood groupsInferenceData.map methodvar_names argument in stats and plotting functions now supports filtering parameters based on partial naming (filter="like") or regular expressions (filter="regex")hdi has been extended to work on arrays with more than 2d and on InferenceData objectsplot_trace to display rank plothpd and plot_hpd have been deprecated in favour of hdi and plot_hdi respectivelycredible_interval has been deprecated in favour of hdi_probSee detailed change log
var_names arg can now filter parameters based on partial naming (filter="like") or regular expressions (filter="regex") (see 1154).true_values argument for plot_pair. It allows for a scatter plot showing the true values of the variables (1140)hpd function to make it work with mutidimensional arrays, InferenceData and xarray objects (1117)predictions and predictions_constant_data) to from_dict (1125)predictions and predictions_constant_data) and constant_data group to pyro and numpyro translation (1090, 1125)num_chains and pred_dims arguments to from_pyro and from_numpyro (1090, 1125)cet_grey_r and cet_grey_r. These are perceptually uniform gray scale cmaps from colorcet (linear_grey_10_95_c0) (1164)hdi_prob will not plot hdi if argument hide is passed. Previously credible_interval would omit HPD if None was passed (1176)stats.ic_pointwise rcParam (1173)var_name argument to information criterion calculation: compare,
loo and waic (1173)plot_pair functionality for two variables with bokeh backend (1179)diagonal argument for marginals and fixed point_estimate_marker_kwargs in plot_pair (1167)credible_interval=None in plot_posterior (1115)plot_dist with multidimensional input (1115)TypeError in transform argument of plot_density and plot_forest when InferenceData is a list or tuple (1121)_fast_kde, _fast_kde_2d, get_bins and _sturges_formula to numeric_utils and get_coords to utils (1142)axes argument to ax (1144)plot_posterior with rcParam "plot.matplotlib.show" = True (1151)fill_last argument of plot_kde to False by default (1158)hpd function deprecated in favor of hdi. credible_interval argument replaced by hdi_probthroughout with exception of plot_loo_pit (1176)plot_hpd function deprecated in favor of plot_hdi. (1190)setup.py including Matplotlib framework (1133)plot_pair (1110)psislw and r2_score (1129)intersphinx for better
references (1184)New defaults for cross validation: loo (old: waic) and log -scale (old: deviance -scale)
loo (old: waic) and log -scale (old: deviance -scale)predictions grouplog_likelihood groupplot_density, plot_energy and plot_ess support interactive legends in Bokeh, automatic legend in plot_trace(..., compact=True) in matplotlibtransform argument to plotting functionsSee detailed change log
predictions and predictions_constant_data groups) to pymc3, pystan, cmdstan and cmdstanpy translations (983, 1032 and 1064)predictions and predictions_constant_data groups) to pymc3 and pystan translations (983 and 1032)plot.point_estimate (994), stats.ic_scale (993) and stats.credible_interval (1017)group argument to plot_ppc (1008), plot_pair (1009) and plot_joint (1012)transform argument to plot_trace, plot_forest, plot_pair, plot_posterior, plot_rank, plot_parallel, plot_violin,plot_density, plot_joint (1036)skipna argument to hpd and summary (1035)transform argument to plot_trace, plot_forest, plot_pair, plot_posterior, plot_rank, plot_parallel, plot_violin,plot_density, plot_joint (1036)marker functionality to bokeh_plot_elpd (1040)ridgeplot_quantiles argument to plot_forest (1047)densityplot, energyplot
and essplot (1024)loo (old: waic) and log -scale (old: deviance -scale) (1067)arviz.wrappers module to allow ArviZ to refit the models if necessary (771)reloo function to ArviZ (771)matplotlib_kwarg_dealiaser (1073)log_likelihood argument to from_pymc3 (1082)plot.bokeh.layout and plot.backend. (1089)plot_trace with compact=True (matplotlib only) (1070)plot_pair with bokeh backend (1074)point_estimate in plot_posterior (1038)hpd_plot (1039)io_pymc3.py to handle models with potentials (1043)from_pymc3 implementation
in groups prior, prior_predictive and observed_data (1045)plot_kde_2d (1075)prior data in from_pyro (1071)from_pymc3 now requires PyMC3>=3.8InferenceData schema specification (log_likelihood,
predictions and predictions_constant_data groups)plot_joint (1001)concat method (1037)Minor release due to error in packaging import statement.
Minor release due to error in packaging import statement.
#975
packaging import from absolute to relative format, explicitly importing version function#976
packaging import from absolute to relative format, explicitly importing version functionFully support numpyro (@fehiepsi )
numpyro (@fehiepsi )az.concat functionality (@anzelpwj )numpyro (@fehiepsi )az.concat functionality (@anzelpwj )Comment dev requirements in setup.py
Plot Forest reports ess and rhat by default
## New features * Add plot_dist (#592) * New rhat and ess (#623) * Add plot_hpd (#611) * Add plot_rank (#625) ## Deprecations * Remove load_data and s
Plot ppc supports multiple chains
Add some more information to the inference data of tfp
plot_forest (#448)from_dict for easier creation of az.InferenceData objects (#524)from_pyro with multiple chains (#463)__version__ for attr (#466)Fix installation problem with release 0.3.0
Fix installation problem with release 0.3.0
ArviZ should be now stable enough for daily use. We do not expect major API changes in the near future, instead we expect to work on adding new featur
ArviZ should be now stable enough for daily use. We do not expect major API changes in the near future, instead we expect to work on adding new features and plots.
Nothing published for this version
Includes plots, statistics, and diagnostics. Works well with objects from PyMC3, PyStan, CmdStan, emcee, and Pyro natively, as well as any dictionary
Includes plots, statistics, and diagnostics. Works well with objects from PyMC3, PyStan, CmdStan, emcee, and Pyro natively, as well as any dictionary of arrays.
First release of ArviZ. Has feature parity with PyMC3 plotting and diagnostics, but is still considered alpha software.
First release of ArviZ. Has feature parity with PyMC3 plotting and diagnostics, but is still considered alpha software.
Nothing published for this version
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