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.. _whats_new_v0p7:

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What's New in Halotools v0.7?
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Halotools ``v0.7`` is now available for installation with conda and pip. New features are summarized below. See :ref:`changelog` for details on smaller issues and bug-fixes. See :ref:`whats_new_v0x_history` for full release history information.


New Utility Functions
=====================

Probabilistic binning
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The `~halotools.utils.fuzzy_digitize` function in `halotools.utils` allows you to discretize an
array in a probabilistic fashion, which can be useful for applications of conditional abundance matching.

Estimation of Conditional Probability Distributions
-----------------------------------------------------
The `~halotools.utils.sliding_conditional_percentile` function in `halotools.utils` calculates Prob(< y | x) for any arbitrary distribution of two-dimensional data. This function can be used to estimate, for example, quantiles of galaxy size as a function of stellar mass, and also should be useful in applications of conditional abundance matching.


New Mock Observables
====================

Inertia Tensor calculation
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The pairwise calculation `~halotools.mock_observables.inertia_tensor_per_object` computes the inertia tensor of a mass distribution surrounding each point in a sample of galaxies or halos.

API Changes
===========

* The old implementation of the `~halotools.empirical_models.conditional_abunmatch` function has been renamed to be `~halotools.empirical_models.conditional_abunmatch_bin_based`.

* There is an entirely distinct, bin-free implementation of Conditional Abundance Matching that now bears the name `~halotools.empirical_models.conditional_abunmatch`.

* The `~halotools.mock_observables.mean_delta_sigma` function has replaced the previous calculation of gg-lensing. See #95 and #980.

Bug Fixes
=========
See issues tagged with the v0.7 milestone for a complete list of all bug fixes and changes.