diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md index f359f621..749641af 100644 --- a/.github/pull_request_template.md +++ b/.github/pull_request_template.md @@ -7,4 +7,4 @@ ## Additional Context for Reviewers -- [ ] I passed tests locally for both code (`pytest`) and documentation changes (`uv run jb build docs --builder=custom --custom-builder=doctest`) +- [ ] I passed tests locally for both code (`uv run pytest`) and documentation changes (`uv run jb build docs --builder=custom --custom-builder=doctest`) diff --git a/chainladder/adjustments/parallelogram.py b/chainladder/adjustments/parallelogram.py index 1c7a758a..7c225019 100644 --- a/chainladder/adjustments/parallelogram.py +++ b/chainladder/adjustments/parallelogram.py @@ -7,8 +7,8 @@ class ParallelogramOLF(BaseEstimator, TransformerMixin, EstimatorIO): - """ - Estimator to create and apply on-level factors to a Triangle object. This + f""" + Estimator to create and apply on-level factors to a Triangle object. This is commonly used for premium vectors expressed as a Triangle object. Parameters @@ -21,10 +21,15 @@ class ParallelogramOLF(BaseEstimator, TransformerMixin, EstimatorIO): 5% decrease should be stated as -0.05 date_col: str A list-like set of effective dates corresponding to each of the changes - approximation_grain: str - The resolution of the internal calendar used for calculating the on-level factors: - monthly ('M') or daily ('D'). Daily is finer and adjusts for leap years when assigning - factors to origin periods. + approximation_grain: str {"M", "D"} (default="M") + The resolution of the internal calendar spacing used for calculating the + on-level factors: monthly ('M') or daily ('D'). In each `approximation_grain`, + they are treated as a period, and a weighted current rate level is estimated. + While in daily mode, each day is treated as a full period. Daily is finer + and adjusts for leap years when assigning factors to origin periods. + The Friedland text uses monthly, but daily is more accurate. + policy_length: int (default=12) + The length of the policy in months. vertical_line: Rates are typically stated on an effective date basis and premiums on and earned basis. By default, this argument is False and produces @@ -45,12 +50,14 @@ def __init__( change_col="", date_col="", approximation_grain="M", + policy_length=12, vertical_line=False, ): self.rate_history = rate_history self.change_col = change_col self.date_col = date_col self.approximation_grain = approximation_grain + self.policy_length = policy_length self.vertical_line = vertical_line def fit(self, X, y=None, sample_weight=None): @@ -86,6 +93,7 @@ def fit(self, X, y=None, sample_weight=None): start_date=X.origin[0].to_timestamp(how="s"), end_date=X.origin[-1].to_timestamp(how="e"), grain=X.origin_grain, + policy_length=self.policy_length, vertical_line=self.vertical_line, approximation_grain=self.approximation_grain, ) diff --git a/chainladder/core/dunders.py b/chainladder/core/dunders.py index e8799703..78226045 100644 --- a/chainladder/core/dunders.py +++ b/chainladder/core/dunders.py @@ -45,7 +45,7 @@ def _validate_arithmetic(self, other: Any) -> tuple: if isinstance(other, np.ndarray) and self.array_backend != 'numpy': obj = self.copy() other = obj.get_array_module().array(other) - elif isinstance(other, sp) and self.array_backend != 'sparse': + elif isinstance(other, sp.COO) and self.array_backend != 'sparse': obj = self.set_backend('sparse') else: obj = self.copy() diff --git a/chainladder/core/slice.py b/chainladder/core/slice.py index 55c29a82..4c5b98e8 100644 --- a/chainladder/core/slice.py +++ b/chainladder/core/slice.py @@ -103,7 +103,7 @@ def _sparse_setitem(self, key, values): (self.obj.values.coords, np.array(key)[:, None]), 1) self.obj.values.data = np.concatenate( (self.obj.values.data, np.array([values])), 0) - self.obj.values = self.obj.get_array_module()( + self.obj.values = self.obj.get_array_module().COO( self.obj.values.coords, self.obj.values.data, prune=True, has_duplicates=False, shape=self.obj.shape, fill_value=self.obj.values.fill_value) @@ -238,8 +238,8 @@ def __setitem__(self, key, value): value.values.coords[1] = i coords = np.concatenate((before.coords, value.values.coords), axis=1) data = np.concatenate((before.data, value.values.data)) - self.values = xp( - coords, data, shape=self.shape, prune=True, fill_value=xp.nan + self.values = xp.COO( + coords, data, shape=self.shape, prune=True, fill_value=xp.COO.nan ) else: if isinstance(value, TriangleSlicer): diff --git a/chainladder/core/triangle.py b/chainladder/core/triangle.py index dd80c21e..a6a33b52 100644 --- a/chainladder/core/triangle.py +++ b/chainladder/core/triangle.py @@ -524,7 +524,7 @@ def __init__( # Construct Sparse multidimensional array. self.values: COO = num_to_nan( - sp( + sp.COO( coords, amts, prune=True, diff --git a/chainladder/utils/sparse.py b/chainladder/utils/sparse.py index 50533d98..2de836b8 100644 --- a/chainladder/utils/sparse.py +++ b/chainladder/utils/sparse.py @@ -2,23 +2,13 @@ # License, v. 2.0. If a copy of the MPL was not distributed with this # file, You can obtain one at https://mozilla.org/MPL/2.0/. import numpy as np -import sparse -from sparse import COO as sp +import sparse as sp +from sparse import COO as COO from sparse import elemwise -import pandas as pd -import copy sp.isnan = np.isnan -sp.newaxis = np.newaxis -sp.nan = np.array([1.0, np.nan])[-1] -sp.testing = np.testing -sp.nansum = sparse.nansum -sp.nanmin = sparse.nanmin -sp.nanmax = sparse.nanmax -sp.concatenate = sparse.concatenate -sp.diagonal = sparse.diagonal -sp.zeros = sparse.zeros -sp.testing.assert_array_equal = np.testing.assert_equal +COO.nan = np.array([1.0, np.nan])[-1] +setattr(sp, 'testing', np.testing) sp.sqrt = np.sqrt sp.log = np.log sp.exp = np.exp @@ -31,41 +21,41 @@ def nan_to_num(a): if hasattr(a, "fill_value"): a = a.copy() a.data[np.isnan(a.data)] = 0.0 - return sp(coords=a.coords, data=a.data, fill_value=0.0, shape=a.shape) + return COO(coords=a.coords, data=a.data, fill_value=0.0, shape=a.shape) def ones(*args, **kwargs): - return sp(np.ones(*args, **kwargs), fill_value=sp.nan) + return COO(np.ones(*args, **kwargs), fill_value=COO.nan) def nansum(a, axis=None, keepdims=None, *args, **kwargs): - return sp(data=a.data, coords=a.coords, fill_value=0.0, shape=a.shape).sum( + return COO(data=a.data, coords=a.coords, fill_value=0.0, shape=a.shape).sum( axis=axis, keepdims=keepdims, *args, **kwargs ) -sp.nansum = nansum -def nanmean(a, axis=None, keepdims=None, *args, **kwargs): - n = sp.nansum(a, axis=axis, keepdims=keepdims) - d = sp.nansum(sp.nan_to_num(a) != 0, axis=axis, keepdims=keepdims).astype(n.dtype) - n = sp(data=n.data, coords=n.coords, fill_value=np.nan, shape=n.shape) - d = sp(data=d.data, coords=d.coords, fill_value=np.nan, shape=d.shape) + +def nanmean(a, axis=None, keepdims=None): + n = nansum(a, axis=axis, keepdims=keepdims) + d = nansum(nan_to_num(a) != 0, axis=axis, keepdims=keepdims).astype(n.dtype) + n = COO(data=n.data, coords=n.coords, fill_value=np.nan, shape=n.shape) + d = COO(data=d.data, coords=d.coords, fill_value=np.nan, shape=d.shape) out = n / d - return sp(data=out.data, coords=out.coords, fill_value=0, shape=out.shape) + return COO(data=out.data, coords=out.coords, fill_value=0, shape=out.shape) def array(a, *args, **kwargs): if kwargs.get("fill_value", None) is not None: fill_value = kwargs.pop("fill_value") else: - fill_value = sp.nan - if type(a) == sp: - return sp(a, *args, **kwargs, fill_value=fill_value) + fill_value = COO.nan + if type(a) == sp.COO: + return COO(a, *args, **kwargs, fill_value=fill_value) else: - return sp(np.array(a, *args, **kwargs), fill_value=fill_value) + return COO(np.array(a, *args, **kwargs), fill_value=fill_value) def arange(*args, **kwargs): - return sparse.COO.from_numpy(np.arange(*args, **kwargs)) + return COO.from_numpy(np.arange(*args, **kwargs)) def where(*args, **kwargs): @@ -76,12 +66,12 @@ def cumprod(a, axis=None, dtype=None, out=None): return array(np.cumprod(a.todense(), axis=axis, dtype=dtype, out=out)) -def floor(x, *args, **kwargs): +def floor(x): x.data = np.floor(x.data) return x - +sp.nansum = nansum sp.minimum = np.minimum sp.maximum = np.maximum sp.floor = floor @@ -91,4 +81,6 @@ def floor(x, *args, **kwargs): sp.nan_to_num = nan_to_num sp.ones = ones sp.cumprod = cumprod +COO.cumprod = cumprod sp.nanmean = nanmean +sp.sum = COO.sum diff --git a/chainladder/utils/tests/test_sparse.py b/chainladder/utils/tests/test_sparse.py new file mode 100644 index 00000000..c8a2b211 --- /dev/null +++ b/chainladder/utils/tests/test_sparse.py @@ -0,0 +1,110 @@ +import numpy as np + +from chainladder.utils.sparse import ( + array, + floor, + COO, + where +) + + +def test_array_from_list_default_fill_value() -> None: + """ + Tests chainladder.utils.sparse.array() when no fill value is provided. + Checks whether the default nan is filled. + + Returns + ------- + None + + """ + result: COO = array([1.0, 2.0, 3.0]) + assert isinstance(result, COO) + assert np.isnan(result.fill_value) + + +def test_array_from_list_explicit_fill_value() -> None: + """ + Tests chainladder.utils.sparse.array() when a fill value of 0 is provided. + Checks whether the 0 is filled. + + Returns + ------- + + """ + result: COO = array([1, 2, 3], fill_value=0) + assert isinstance(result, COO) + assert result.fill_value == 0 + + +def test_array_from_coo_default_fill_value() -> None: + """ + Tests chainladder.utils.sparse.array() when initializing from a sparse array with a default fill value. + + Returns + ------- + None + + """ + coo = COO.from_numpy(np.array([1.0, 2.0, 3.0])) + result: COO = array(coo) + assert isinstance(result, COO) + assert np.isnan(result.fill_value) + + +def test_array_from_coo_explicit_fill_value() -> None: + """ + Tests chainladder.utils.sparse.array() when initializing from a sparse array with an explicit fill value. + + Returns + ------- + None + + """ + coo = COO.from_numpy(np.array([1, 2, 3])) + result: COO = array(coo, fill_value=0) + assert isinstance(result, COO) + assert result.fill_value == 0 + + +def test_where_selects_from_two_arrays() -> None: + """ + Tests element-wise where across sparse arrays. Calls np.where on each element triplet + (cond[i], a[i], b[i]) - returning a[i] where the condition is True and b[i] where it's False. + + Returns + ------- + None + """ + a: COO = array([1.0, 2.0, 3.0]) + b: COO = array([10.0, 20.0, 30.0]) + cond: COO = array([True, False, True]) + result: COO = where(cond, a, b) + assert isinstance(result, COO) + np.testing.assert_array_equal(result.todense(), [1.0, 20.0, 3.0]) + + +def test_floor_rounds_down() -> None: + """ + Checks floor function rounding down with positive and negative floats. + + Returns + ------- + None + """ + a: COO = array([1.2, 2.7, -0.3]) + result: COO = floor(a) + np.testing.assert_array_equal(result.todense(), [1.0, 2.0, -1.0]) + + +def test_floor_mutates_in_place() -> None: + """ + Checks in-place mutation of floor function. + + Returns + ------- + None + """ + a = array([1.2, 2.7, -0.3]) + result: COO = floor(a) + assert result is a diff --git a/chainladder/utils/tests/test_utilities.py b/chainladder/utils/tests/test_utilities.py index f625a542..472aad63 100644 --- a/chainladder/utils/tests/test_utilities.py +++ b/chainladder/utils/tests/test_utilities.py @@ -112,6 +112,66 @@ def test_vertical_line(): assert abs(olf.loc["2017"].iloc[0] - true_olf) < 0.00001 +def test_policy_length(): + rate_history = pd.DataFrame( + { + "EffDate": ["2010-07-01", "2011-01-01", "2012-04-01"], + "RateChange": [0.05, 0.1, -0.01], + } + ) + data = pd.DataFrame( + {"Year": [2010, 2011, 2012, 2013, 2014], "EarnedPremium": [10_000] * 5} + ) + prem_tri = cl.Triangle( + data, origin="Year", columns="EarnedPremium", cumulative=True + ) + + prem_tri = cl.ParallelogramOLF( + rate_history, change_col="RateChange", date_col="EffDate", policy_length=12 + ).fit_transform(prem_tri) + assert ( + np.round(prem_tri.olf_.values.flatten(), 6) + == [1.136348, 1.043056, 0.992792, 0.999684, 1] + ).all() + + prem_tri = cl.ParallelogramOLF( + rate_history, change_col="RateChange", date_col="EffDate", policy_length=6 + ).fit_transform(prem_tri) + assert ( + np.round(prem_tri.olf_.values.flatten(), 6) + == [1.129333, 1.013023, 0.994975, 1, 1] + ).all() + + rate_history = pd.DataFrame( + { + "EffDate": ["2010-07-01", "2011-10-01", "2012-04-01"], + "RateChange": [0.35, 0.149, -0.095], + } + ) + data = pd.DataFrame( + {"Year": [2010, 2011, 2012, 2013, 2014], "EarnedPremium": [10_000] * 5} + ) + prem_tri = cl.Triangle(data, origin="Year", columns="EarnedPremium", cumulative=True) + + prem_tri = cl.ParallelogramOLF( + rate_history, + change_col="RateChange", + date_col="EffDate", + policy_length=12, + approximation_grain="M", + ).fit_transform(prem_tri) + assert (np.round(prem_tri.olf_.values.flatten(),6) == [1.344949, 1.069526, 0.966045, 0.996730, 1]).all() + + prem_tri = cl.ParallelogramOLF( + rate_history, + change_col="RateChange", + date_col="EffDate", + policy_length=6, + approximation_grain="M", + ).fit_transform(prem_tri) + assert (np.round(prem_tri.olf_.values.flatten(),6) == [1.290842, 1.030251, 0.958285, 1, 1]).all() + + def test_triangle_json_io(clrd): xp = clrd.get_array_module() clrd2 = cl.read_json(clrd.to_json(), array_backend=clrd.array_backend) @@ -157,33 +217,38 @@ def test_json_df(): ) assert abs(cl.read_json(x.to_json()).lambda_ - x.lambda_).sum() < 1e-5 + def test_read_csv_single(raa): # Test the read_csv function for a single dimensional input. - + # Read in the csv file. from pathlib import Path + raa_csv_path = Path(__file__).parent.parent / "data" / "raa.csv" assert raa == cl.read_csv( filepath_or_buffer=raa_csv_path, - origin = "origin", - development = "development", - columns = ["values"], - index = None, - cumulative = True) + origin="origin", + development="development", + columns=["values"], + index=None, + cumulative=True, + ) + def test_read_csv_multi(clrd): # Test the read_csv function for multidimensional input. # Read in the csv file. from pathlib import Path + clrd_csv_path = Path(__file__).parent.parent / "data" / "clrd.csv" assert clrd == cl.read_csv( filepath_or_buffer=clrd_csv_path, - origin = "AccidentYear", - development = "DevelopmentYear", - columns = [ + origin="AccidentYear", + development="DevelopmentYear", + columns=[ "IncurLoss", "CumPaidLoss", "BulkLoss", @@ -191,9 +256,10 @@ def test_read_csv_multi(clrd): "EarnedPremCeded", "EarnedPremNet", ], - index = ["GRNAME","LOB"], - cumulative = True - ) + index=["GRNAME", "LOB"], + cumulative=True, + ) + def test_concat(clrd): tri = clrd.groupby("LOB").sum() diff --git a/chainladder/utils/utility_functions.py b/chainladder/utils/utility_functions.py index 37c381f1..f871ee30 100644 --- a/chainladder/utils/utility_functions.py +++ b/chainladder/utils/utility_functions.py @@ -524,6 +524,7 @@ def parallelogram_olf( start_date=None, end_date=None, grain="Y", + policy_length=12, approximation_grain="M", vertical_line=False, ): @@ -559,8 +560,8 @@ def parallelogram_olf( if not vertical_line: rolling_num = { - "M": 12, - "D": 365, + "M": policy_length, + "D": 365*int(policy_length/12), } cum_avg_rate_non_leaps = cum_rate_changes.rolling( @@ -730,14 +731,14 @@ def num_to_value( arr.coords = arr.coords[:, arr.data != 0] arr.data = arr.data[arr.data != 0] - arr: COO = sp( + arr: COO = sp.COO( coords=arr.coords, data=arr.data, - fill_value=sp.nan, # noqa + fill_value=sp.COO.nan, # noqa shape=arr.shape ) else: - arr: COO = sp( + arr: COO = sp.COO( num_to_nan(np.nan_to_num(arr.todense())), fill_value=value ) diff --git a/chainladder/utils/weighted_regression.py b/chainladder/utils/weighted_regression.py index aec67d22..12a5ef7e 100644 --- a/chainladder/utils/weighted_regression.py +++ b/chainladder/utils/weighted_regression.py @@ -53,7 +53,7 @@ def _fit_OLS(self): y[w == 0] = xp.nan else: w2 = w.copy() - w2 = sp(data=w2.data, coords=w2.coords, fill_value=sp.nan, shape=w2.shape) + w2 = sp.COO(data=w2.data, coords=w2.coords, fill_value=sp.nan, shape=w2.shape) x, y = x * w2, y * w2 with warnings.catch_warnings(): diff --git a/docs/getting_started/install.md b/docs/getting_started/install.md index a53ba6c4..b1374a2d 100644 --- a/docs/getting_started/install.md +++ b/docs/getting_started/install.md @@ -3,15 +3,18 @@ We strongly encourage users to install chainladder in a dedicated virtual environment. ## General Installation -Install the chainladder package using `pip`: +We recommend **uv** for installing `chainladder`, but you can use any of the managers below: [![](https://pepy.tech/badge/chainladder)](https://pepy.tech/project/chainladder) -Installing `chainladder` using `pip`: - -`pip install chainladder` +| Manager | Command | Source | +|:---|:---|:---| +| uv (recommended) | `uv add chainladder` | PyPI | +| pip | `pip install chainladder` | PyPI | +| pixi | `pixi add chainladder` | conda-forge | +| conda | `conda install -c conda-forge chainladder` | conda-forge | Alternatively, if you have git and want to enjoy unreleased features, you can install directly from `Github`: diff --git a/docs/getting_started/tutorials/triangle-tutorial.ipynb b/docs/getting_started/tutorials/triangle-tutorial.ipynb index e2d3a67a..e413faad 100644 --- a/docs/getting_started/tutorials/triangle-tutorial.ipynb +++ b/docs/getting_started/tutorials/triangle-tutorial.ipynb @@ -6085,7 +6085,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "`Pandas` has wonderful datetime inference functionality that the `Triangle` heavily uses to infer origin and development granularity. Even still, there are occassions where date format inferences can fail. It is often better to explicitly tell the triangle the date format, and is usually good pratice to explicitly state the date format instead." + "`Pandas` has wonderful datetime inference functionality that the `Triangle` heavily uses to infer origin and development granularity. Even still, there are occasions where date format inferences can fail. It is often better to explicitly tell the triangle the date format, and is usually good practice to explicitly state the date format instead." ] }, { diff --git a/docs/library/api.md b/docs/library/api.md index 0e412b07..d0985fab 100644 --- a/docs/library/api.md +++ b/docs/library/api.md @@ -107,9 +107,9 @@ Classes .. _adjustments_ref: -:mod:`chainladder.workflow`: Adjustments -======================================== -.. automodule:: chainladder.workflow +:mod:`chainladder.adjustments`: Adjustments +=========================================== +.. automodule:: chainladder.adjustments :no-members: :no-inherited-members: diff --git a/docs/library/releases.md b/docs/library/releases.md index 9a4c967a..e2be91e9 100644 --- a/docs/library/releases.md +++ b/docs/library/releases.md @@ -2,6 +2,60 @@ ## Version 0.9 +### Version 0.9.2 + +Release Date: May 11, 2026 + +**What's Changed** +* Bump nbconvert from 7.16.6 to 7.17.0 by @dependabot[bot] in [#672](https://github.com/casact/chainladder-python/pull/672) +* Adding dict support for renaming columns by @henrydingliu in [#671](https://github.com/casact/chainladder-python/pull/671) +* Drop python3.9 by @kennethshsu in [#675](https://github.com/casact/chainladder-python/pull/675) +* Bump pillow from 11.3.0 to 12.1.1 by @dependabot[bot] in [#673](https://github.com/casact/chainladder-python/pull/673) +* Various fix by @henrydingliu in [#676](https://github.com/casact/chainladder-python/pull/676) +* Build(deps): Bump tornado from 6.5.2 to 6.5.5 by @dependabot[bot] in [#677](https://github.com/casact/chainladder-python/pull/677) +* Build(deps): Bump requests from 2.32.5 to 2.33.0 by @dependabot[bot] in [#685](https://github.com/casact/chainladder-python/pull/685) +* Build(deps): Bump pygments from 2.19.2 to 2.20.0 by @dependabot[bot] in [#688](https://github.com/casact/chainladder-python/pull/688) +* Build(deps): Bump pillow from 12.1.1 to 12.2.0 by @dependabot[bot] in [#697](https://github.com/casact/chainladder-python/pull/697) +* Build(deps): Bump pytest from 8.4.2 to 9.0.3 by @dependabot[bot] in [#698](https://github.com/casact/chainladder-python/pull/698) +* [#689](https://github.com/casact/chainladder-python/issues/689) by @kennethshsu in [#690](https://github.com/casact/chainladder-python/pull/690) +* Improve docstring for approximation_grain in ParallelogramOLF by @kennethshsu in [#687](https://github.com/casact/chainladder-python/pull/687) +* Addressed wheel vulnerability by @kennethshsu in [#699](https://github.com/casact/chainladder-python/pull/699) +* Build(deps): Bump nbconvert from 7.17.0 to 7.17.1 by @dependabot[bot] in [#703](https://github.com/casact/chainladder-python/pull/703) +* DOCS: Begin work on examples. by @genedan in [#700](https://github.com/casact/chainladder-python/pull/700) +* Build(deps): Bump lxml from 6.0.2 to 6.1.0 by @dependabot[bot] in [#705](https://github.com/casact/chainladder-python/pull/705) +* nan_triangle 1D logic overhaul by @danielfong-act in [#702](https://github.com/casact/chainladder-python/pull/702) +* Add links to object source code in API Reference section by @genedan in [#710](https://github.com/casact/chainladder-python/pull/710) +* [#707](https://github.com/casact/chainladder-python/issues/707) by @kennethshsu in [#711](https://github.com/casact/chainladder-python/pull/711) +* Pr template by @kennethshsu in [#712](https://github.com/casact/chainladder-python/pull/712) +* DOCS: Expand Triangle constructor examples (#704) by @EKtheSage in [#714](https://github.com/casact/chainladder-python/pull/714) +* FEAT: Initialize triangle from dict. by @genedan in [#706](https://github.com/casact/chainladder-python/pull/706) +* DOCS: Add examples to Triangle methods and properties (#704) by @EKtheSage in [#719](https://github.com/casact/chainladder-python/pull/719) +* DOCS: Add examples to deterministic IBNR methods (#704) by @EKtheSage in [#721](https://github.com/casact/chainladder-python/pull/721) +* Docs/issue 704 tailconstant examples by @priyam0k in [#722](https://github.com/casact/chainladder-python/pull/722) +* Add Friedland datasets to cl.load_sample() by @genedan in [#730](https://github.com/casact/chainladder-python/pull/730) +* CHORE: Update workflows to test docs examples. by @genedan in [#713](https://github.com/casact/chainladder-python/pull/713) +* Added an example and improved docstring for load_sample by @kennethshsu in [#715](https://github.com/casact/chainladder-python/pull/715) +* Missing testoutput by @kennethshsu in [#731](https://github.com/casact/chainladder-python/pull/731) +* Fix test indentation and add print statement by @kennethshsu in [#732](https://github.com/casact/chainladder-python/pull/732) +* Fixed doc site build fails by @kennethshsu in [#733](https://github.com/casact/chainladder-python/pull/733) +* ENH: Continue work on type hinting, add pyright to check type coverage. by @genedan in [#735](https://github.com/casact/chainladder-python/pull/735) +* Rtd branch fix by @henrydingliu in [#741](https://github.com/casact/chainladder-python/pull/741) +* fix(tests): use assert in test_n_periods so failures actually fail by @SaguaroDev in [#744](https://github.com/casact/chainladder-python/pull/744) +* Build(deps): Bump mistune from 3.1.4 to 3.2.1 by @dependabot[bot] in [#748](https://github.com/casact/chainladder-python/pull/748) +* Update pyproject.toml - Add numpy ([#738](https://github.com/casact/chainladder-python/issues/738)) by @wendy-w2029 in [#750](https://github.com/casact/chainladder-python/pull/750) +* Enhance docstrings and examples for improved clarity for many estimators by @kennethshsu in [#747](https://github.com/casact/chainladder-python/pull/747) +* Fix Adjustments API page linking to chainladder.workflow (#757) by @SaguaroDev in [#762](https://github.com/casact/chainladder-python/pull/762) +* Annotate matplotlib dependency as required for TriangleDisplay.heatmap() (#758) by @SaguaroDev in [#761](https://github.com/casact/chainladder-python/pull/761) +* REFACTOR: Reorganize type hierarchy of sparse.py. Move array-level fu… by @genedan in [#739](https://github.com/casact/chainladder-python/pull/739) +* Build(deps): Bump urllib3 from 2.6.3 to 2.7.0 by @dependabot[bot] in [#767](https://github.com/casact/chainladder-python/pull/767) + +**New Contributors** +* @priyam0k made their first contribution in [#722](https://github.com/casact/chainladder-python/pull/722) +* @SaguaroDev made their first contribution in [#744](https://github.com/casact/chainladder-python/pull/744) +* @wendy-w2029 made their first contribution in [#750](https://github.com/casact/chainladder-python/pull/750) + +**Full Changelog**: https://github.com/casact/chainladder-python/compare/v0.9.1...v0.9.2 + ### Version 0.9.1 Release Date: Jan 30, 2026 @@ -143,7 +197,7 @@ Release Date: May 24, 2024 Release Date: Apr 10, 2024 **What's Changed** -* Various bug fixes and improvements +* Fix for [\#509](https://github.com/casact/chainladder-python/issues/509) (triangle / core initialization and packaging metadata). ### Version 0.8.19 @@ -174,7 +228,9 @@ Release Date: Sep 18, 2023 Release Date: Jun 17, 2023 **What's Changed** -* Bump of 0.8.16 +* Relax the `pandas<2.0` upper bound in CI/deps metadata. +* Update `environment-latest.yaml` and `pytest_upstream_nightly.yml` ([#442](https://github.com/casact/chainladder-python/pull/442)). +* Adjust pytest-related dependency pins. ### Version 0.8.16 @@ -185,7 +241,7 @@ Release Date: Jun 17, 2023 * fix for [\#411](https://github.com/casact/chainladder-python/issues/411) * fix for [\#438](https://github.com/casact/chainladder-python/issues/438) -## New Contributors +**New Contributors** * [@MatthewCaseres](https://github.com/MatthewCaseres) made their first contribution. * [@andrejakobsen](https://github.com/andrejakobsen) made their first contribution. @@ -226,7 +282,18 @@ Release Date: Apr 11, 2023 Release Date: Nov 25, 2022 - +**What's Changed** +* Major documentation refresh for Jupyter Book and CAS Annual Meeting materials: user guide and gallery restructure, new exercises and demos, usage/Colab notes, and bibliography updates (including [#311](https://github.com/casact/chainladder-python/pull/311) and related annual-meeting prep PRs [#335](https://github.com/casact/chainladder-python/pull/335)–[#361](https://github.com/casact/chainladder-python/pull/361)). +* Additional Friedland and other sample datasets for `load_sample` ([#347](https://github.com/casact/chainladder-python/pull/347), [#353](https://github.com/casact/chainladder-python/pull/353), [#355](https://github.com/casact/chainladder-python/pull/355), [#357](https://github.com/casact/chainladder-python/pull/357), [#358](https://github.com/casact/chainladder-python/pull/358), [#359](https://github.com/casact/chainladder-python/pull/359), [#362](https://github.com/casact/chainladder-python/pull/362), [#363](https://github.com/casact/chainladder-python/pull/363)). +* `Development` transformer: `std_residuals_` ([#352](https://github.com/casact/chainladder-python/pull/352)). +* Four-dimensional triangles: extend `drop_high` / `drop_low` (including `drop_above` / `drop_below`) ([#375](https://github.com/casact/chainladder-python/pull/375), [#381](https://github.com/casact/chainladder-python/pull/381)). +* Semi-annual key for tail handling ([#384](https://github.com/casact/chainladder-python/pull/384)). +* Triangle `to_frame()` updates and reduced reliance on `origin_as_datetime` inside `to_frame()` ([#360](https://github.com/casact/chainladder-python/pull/360)). +* Bug fixes and hardening for `Development` and triangles ([#373](https://github.com/casact/chainladder-python/pull/373), [#371](https://github.com/casact/chainladder-python/pull/371), [#368](https://github.com/casact/chainladder-python/pull/368), [#366](https://github.com/casact/chainladder-python/pull/366)); follow-ups by @henrydingliu ([#370](https://github.com/casact/chainladder-python/pull/370)). +* `DevelopmentCorrelation` / valuation correlation: annotations, intermediate diagnostics, and `p_critical` validation ([#342](https://github.com/casact/chainladder-python/pull/342)). +* README, GitHub issue templates, and docs environment updates; reduce `to_datetime` deprecation noise. + +**Full Changelog**: https://github.com/casact/chainladder-python/compare/v0.8.13...v0.8.14 ### Version 0.8.13 @@ -250,6 +317,8 @@ Release Date: Jun 27, 2022 Release Date: Mar 8, 2022 +*Note:* There was no `0.8.11` stable release on PyPI; only pre-release tags `v0.8.11-alpha` and `v0.8.11-beta` were published. + **Bug Fixes** - [\#254](https://github.com/casact/chainladder-python/issues/254) Fixed an undesired mutation when using cl.concat diff --git a/pyproject.toml b/pyproject.toml index 07231fe5..46a4901d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "chainladder" -version = "0.9.1" +version = "0.9.2" authors = [ {name = "John Bogaardt", email = "jbogaardt@gmail.com"}, ] @@ -30,12 +30,12 @@ classifiers = [ ] 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