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akshayshanker authored Dec 15, 2024
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2 changes: 0 additions & 2 deletions .github/workflows/execute-notebooks.yml
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run: |
python -m pip install --upgrade pip
python -m pip install .
# For LabeledModels.ipynb
python -m pip install estimagic
# For nbstripout
python -m pip install nbstripout
# For nb_exec.py
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15 changes: 7 additions & 8 deletions Documentation/CHANGELOG.md
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### Major Changes

- Adds a discretize method to DBlocks and RBlocks (#1460)[https://github.com/econ-ark/HARK/pull/1460]
- Adds a discretize method to DBlocks and RBlocks [#1460](https://github.com/econ-ark/HARK/pull/1460)
- Allows structural equations in model files to be provided in string form [#1427](https://github.com/econ-ark/HARK/pull/1427)
- Introduces `HARK.parser' module for parsing configuration files into models [#1427](https://github.com/econ-ark/HARK/pull/1427)
- Allows construction of shocks with arguments based on mathematical expressions [#1464](https://github.com/econ-ark/HARK/pull/1464)
- YAML configuration file for the normalized consumption and portolio choice [#1465](https://github.com/econ-ark/HARK/pull/1465)
- Reorganizes the `HARK.distribution` file into `HARK.distributions` submodule with various files for readability and extensibility [#1496](https://github.com/econ-ark/HARK/pull/1496)

#### Minor Changes

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#### Minor Changes


- Add option to pass pre-built grid to `LinearFast`. [1388](https://github.com/econ-ark/HARK/pull/1388)
- Moves calculation of stable points out of ConsIndShock solver, into method called by post_solve [#1349](https://github.com/econ-ark/HARK/pull/1349)
- Adds cubic spline interpolation and value function construction to "warm glow bequest" models.
Expand All @@ -77,8 +77,7 @@ This release drops support for Python 3.8 and 3.9, consistent with SPEC 0, and a
- Create functions for well-known and repeated calculations in single-function solvers. [1395](https://github.com/econ-ark/HARK/pull/1395)
- Re-work WealthPortfolioSolver to use approximate EGM method [#1404](https://github.com/econ-ark/HARK/pull/1404)
- Default parameter dictionaries for AgentType subclasses have been "flattened": all parameters appear in one place for each model, rather than inheriting from parent models' dictionaries. The only exception is submodels *within* a file when only 1 or 2 parameters are added or changed. [#1425](https://github.com/econ-ark/HARK/pull/1425)
- Fix minor bug in `HARK.distribution.Bernoulli` to allow conversion into `DiscreteDistributionLabeled`. [#1432](https://github.com/econ-ark/HARK/pull/1432)

- Fix minor bug in `HARK.distributions.Bernoulli` to allow conversion into `DiscreteDistributionLabeled`. [#1432](https://github.com/econ-ark/HARK/pull/1432)

### 0.14.1

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- Changes the `DiscreteDistribution` class to allow for arbitrary array-valued random variables. [#1146](https://github.com/econ-ark/HARK/pull/1146)
- Adds `IndShockRiskyAssetConsumerType` as agent which can invest savings all in safe asset, all in risky asset, a fixed share in risky asset, or optimize its portfolio. [#1107](https://github.com/econ-ark/HARK/issues/1107)
- Updates all HARK models to allow for age-varying interest rates. [#1150](https://github.com/econ-ark/HARK/pull/1150)
- Adds `DiscreteDistribution.expected` method which expects vectorized functions and is faster than `HARK.distribution.calc_expectation`. [#1156](https://github.com/econ-ark/HARK/pull/1156)
- Adds `DiscreteDistribution.expected` method which expects vectorized functions and is faster than `HARK.distributions.calc_expectation`. [#1156](https://github.com/econ-ark/HARK/pull/1156)
- Adds `DiscreteDistributionXRA` class which extends `DiscreteDistribution` to allow for underlying data to be stored in a `xarray.DataArray` object. [#1156](https://github.com/econ-ark/HARK/pull/1156)
- Adds keyword argument `labels` to `expected()` when using `DiscreteDistributionXRA` to allow for expressive functions that use labeled xarrays. [#1156](https://github.com/econ-ark/HARK/pull/1156)
- Adds a wrapper for [`interpolation.py`](https://github.com/EconForge/interpolation.py) for fast multilinear interpolation. [#1151](https://github.com/econ-ark/HARK/pull/1151)
Expand All @@ -137,7 +136,7 @@ Release Date: February 16, 2023
- Updates the `numpy` random generator from `RandomState` to `Generator`. [#1193](https://github.com/econ-ark/HARK/pull/1193)
- Turns the income and income+return distributions into `DiscreteDistributionLabeled` objects. [#1189](https://github.com/econ-ark/HARK/pull/1189)
- Creates `UtilityFuncCRRA` which is an object oriented utility function with a coefficient of constant relative risk aversion and includes derivatives and inverses. Also creates `UtilityFuncCobbDouglas`, `UtilityFuncCobbDouglasCRRA`, and `UtilityFuncConstElastSubs`. [#1168](https://github.com/econ-ark/HARK/pull/1168)
- Reorganizes `HARK.distribution`. All distributions now inherit all features from `scipy.stats`. New `ContinuousFrozenDistribution` and `DiscreteFrozenDistribution` to use `scipy.stats` distributions not yet implemented in HARK. New `Distribution.discretize(N, method = "***")` replaces `Distribution.approx(N)`. New `DiscreteDistribution.limit` attribute describes continuous origin and discretization method. [#1197](https://github.com/econ-ark/HARK/pull/1197).
- Reorganizes `HARK.distributions`. All distributions now inherit all features from `scipy.stats`. New `ContinuousFrozenDistribution` and `DiscreteFrozenDistribution` to use `scipy.stats` distributions not yet implemented in HARK. New `Distribution.discretize(N, method = "***")` replaces `Distribution.approx(N)`. New `DiscreteDistribution.limit` attribute describes continuous origin and discretization method. [#1197](https://github.com/econ-ark/HARK/pull/1197).
- Creates new class of _labeled_ models under `ConsLabeledModel` that use xarray for more expressive modeling of underlying mathematical and economics variables. [#1177](https://github.com/econ-ark/HARK/pull/1177)

#### Minor Changes
Expand All @@ -148,7 +147,7 @@ Release Date: February 16, 2023
- Adds `benchmark` utility to profile the performance of `HARK` solvers. [#1131](https://github.com/econ-ark/HARK/pull/1131)
- Fixes scaling bug in Normal equiprobable approximation method. [1139](https://github.com/econ-ark/HARK/pull/1139)
- Removes the extra-dimension that was returned by `calc_expectations` in some instances. [#1149](https://github.com/econ-ark/HARK/pull/1149)
- Adds `HARK.distribution.expected` alias for `DiscreteDistribution.expected`. [#1156](https://github.com/econ-ark/HARK/pull/1156)
- Adds `HARK.distributions.expected` alias for `DiscreteDistribution.expected`. [#1156](https://github.com/econ-ark/HARK/pull/1156)
- Renames attributes in `DiscreteDistribution`: `X` to `atoms` and `pmf` to `pmv`. [#1164](https://github.com/econ-ark/HARK/pull/1164), [#1051](https://github.com/econ-ark/HARK/pull/1151), [#1159](https://github.com/econ-ark/HARK/pull/1159).
- Remove or replace automated tests that depend on brittle simulation results. [#1148](https://github.com/econ-ark/HARK/pull/1148)
- Updates asset grid constructor from `ConsIndShockModel.py` to allow for linearly-spaced grids when `aXtraNestFac == -1`. [#1172](https://github.com/econ-ark/HARK/pull/1172)
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- Converts non-mathematical code to PEP8 compliant form [#953](https://github.com/econ-ark/HARK/pull/953)
- Adds a constructor for LogNormal distributions from mean and standard deviation [#891](https://github.com/econ-ark/HARK/pull/891/)
- Uses new LogNormal constructor in ConsPortfolioModel [#891](https://github.com/econ-ark/HARK/pull/891/)
- calcExpectations method for taking the expectation of a distribution over a function [#884](https://github.com/econ-ark/HARK/pull/884/] (#897)[https://github.com/econ-ark/HARK/pull/897/)
- calcExpectations method for taking the expectation of a distribution over a function [#884](<https://github.com/econ-ark/HARK/pull/884/>] (#897)[https://github.com/econ-ark/HARK/pull/897/)
- Implements the multivariate normal as a supported distribution, with a discretization method. See [#948](https://github.com/econ-ark/HARK/pull/948).
- Centralizes the definition of value, marginal value, and marginal marginal value functions that use inverse-space
interpolation for problems with CRRA utility. See [#888](https://github.com/econ-ark/HARK/pull/888).
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