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Release/2.1.1 #24

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merged 6 commits into from
Sep 12, 2024
Merged

Release/2.1.1 #24

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bd02d00
Merge pull request #19 from washingtonpost/main
dmnapolitano Mar 29, 2024
30dc66a
Updating dependencies' versions
dmnapolitano Sep 12, 2024
5e86db4
Handle the fact that QuantileRegressionSolver still uses ECOS
dmnapolitano Sep 12, 2024
94f1a9e
Switching cvxpy solver from ECOS to Clarabel
dmnapolitano Sep 12, 2024
0676a3c
Merge pull request #22 from washingtonpost/ELEX-4413-update-dependenc…
dmnapolitano Sep 12, 2024
dcae2b6
Preparing for version 2.1.1 :tada:
dmnapolitano Sep 12, 2024
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4 changes: 2 additions & 2 deletions setup.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@

from setuptools import find_packages, setup

INSTALL_REQUIRES = ["cvxpy~=1.4", "numpy~=1.26", "scipy~=1.12"]
INSTALL_REQUIRES = ["cvxpy~=1.5", "numpy~=2.1", "scipy~=1.14"]

THIS_FILE_DIR = os.path.dirname(__file__)

Expand All @@ -13,7 +13,7 @@
LONG_DESCRIPTION = f.read()

# The full version, including alpha/beta/rc tags
RELEASE = "2.1.0"
RELEASE = "2.1.1"
# The short X.Y version
VERSION = ".".join(RELEASE.split(".")[:2])

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4 changes: 2 additions & 2 deletions src/elexsolver/QuantileRegressionSolver.py
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Expand Up @@ -62,15 +62,15 @@ def _fit_with_regularization(
Fits quantile regression with regularization
TODO: convert this problem to use the dual like in the non regularization case
"""
arguments = {"ECOS": {"max_iters": 10000}}
arguments = {cp.CLARABEL: {"max_iter": 10000}}
coefficients = cp.Variable((x.shape[1],))
y_hat = x @ coefficients
residual = y - y_hat
loss_function = cp.sum(cp.multiply(weights, 0.5 * cp.abs(residual) + (tau - 0.5) * residual))
loss_function += lambda_ * self._get_regularizer(coefficients, regularize_intercept, n_feat_ignore_reg)
objective = cp.Minimize(loss_function)
problem = cp.Problem(objective)
problem.solve(solver="ECOS", **arguments.get("ECOS", {}))
problem.solve(solver=cp.CLARABEL, **arguments.get(cp.CLARABEL, {}))
return coefficients.value

def fit(
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