fix: CI fail

docs/source/gallery/GeneralizedLinearModels/logistic-regression.ipynb

@@ -1,5 +1,15 @@
 {
    "cells": [
+      {
+         "cell_type": "code",
+         "execution_count": null,
+         "id": "1ac67c32",
+         "metadata": {},
+         "outputs": [],
+         "source": [
+            "%matplotlib inline"
+         ]
+      },
       {
          "cell_type": "markdown",
          "id": "7f5e5d54",
@@ -516,4 +526,4 @@
    },
    "nbformat": 4,
    "nbformat_minor": 5
-}
+}

docs/source/gallery/GeneralizedLinearModels/poisson-identity-link.ipynb

@@ -5,7 +5,7 @@
    "id": "f540b29b",
    "metadata": {},
    "source": [
-    "# Poisson Regression with Identity link"
+    "# multiple response non-negativity identity link Poisson model"
    ]
   },
   {
@@ -414,7 +414,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.14"
+   "version": "3.10.13"
   }
  },
  "nbformat": 4,

pytest/test_args.py

@@ -32,9 +32,7 @@
 def test_numeric_solver(model, solver_creator):
     from skscope.numeric_solver import convex_solver_BFGS
 
-    solver = solver_creator(
-        model["n_features"], model["n_informative"], numeric_solver=convex_solver_BFGS
-    )
+    solver = solver_creator(model["n_features"], model["n_informative"], numeric_solver=convex_solver_BFGS)
     solver.solve(model["loss"], jit=True)
 
     assert set(model["support_set"]) == set(solver.get_support())
@@ -169,9 +167,7 @@ def test_scope_hessian():
 
 
 def test_scope_dynamic_max_exchange_num():
-    solver = ScopeSolver(
-        linear["n_features"], linear["n_informative"], is_dynamic_max_exchange_num=False
-    )
+    solver = ScopeSolver(linear["n_features"], linear["n_informative"], is_dynamic_max_exchange_num=False)
     solver.solve(linear["loss"], jit=True)
 
     assert set(linear["support_set"]) == set(solver.support_set)
@@ -188,7 +184,6 @@ def test_scope_args():
         path_type="gs",
         important_search=1,
         preselect=[linear["support_set"][0]],
-        console_log_level="error",
     )
     solver.solve(linear["loss"], jit=True)
 
@@ -200,6 +195,5 @@ def test_scope_args():
         sample_size=linear["n_samples"],
         cv=2,
         split_method=lambda data, indeices: (data[0][indeices], data[1][indeices]),
-        file_log_level="error",
     )
     solver.solve(linear["loss_data"], data=linear["data"])

skscope/solver.py

@@ -256,7 +256,8 @@ def _set_log_level(console_log_level, file_log_level, log_file_name):
         if not isinstance(log_file_name, str):
             raise ValueError("log_file_name must be a string")
 
-        _scope.init_spdlog(console_log_level, file_log_level, log_file_name)
+        if console_log_level < 6 or file_log_level < 6:
+            _scope.init_spdlog(console_log_level, file_log_level, log_file_name)
 
     def solve(
         self,