cleanup (#2285)

Author: juanitorduz

docs/source/notebooks/mmm/mmm_allocation_assessment.ipynb

@@ -502,11 +502,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "from pymc_marketing.mmm import utility as ut"
+    "from pymc_marketing.mmm import utils as ut"
    ]
   },
   {

docs/source/notebooks/mmm/mmm_budget_allocation_example.ipynb

@@ -2998,7 +2998,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -3029,7 +3029,7 @@
     "\n",
     "from pymc_marketing.mmm.budget_optimizer import BudgetOptimizer\n",
     "from pymc_marketing.mmm.constraints import Constraint\n",
-    "from pymc_marketing.mmm.utility import _check_samples_dimensionality\n",
+    "from pymc_marketing.mmm.utils import _check_samples_dimensionality\n",
     "\n",
     "target_response = 145_000\n",
     "\n",

docs/source/notebooks/mmm/mmm_migration_guide.ipynb

@@ -146,7 +146,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "74a0ce31",
    "metadata": {},
    "outputs": [

docs/source/notebooks/mmm/mmm_multi_objective_optimization.ipynb

@@ -18,7 +18,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -54,7 +54,7 @@
     "from pymc_marketing.mmm.builders.yaml import build_mmm_from_yaml\n",
     "from pymc_marketing.mmm.constraints import Constraint\n",
     "from pymc_marketing.mmm.multidimensional import MultiDimensionalBudgetOptimizerWrapper\n",
-    "from pymc_marketing.mmm.utility import _check_samples_dimensionality\n",
+    "from pymc_marketing.mmm.utils import _check_samples_dimensionality\n",
     "from pymc_marketing.paths import data_dir\n",
     "from pymc_marketing.pytensor_utils import merge_models"
    ]

pymc_marketing/mmm/budget_optimizer.py

@@ -210,7 +210,7 @@
     build_default_sum_constraint,
     compile_constraints_for_scipy,
 )
-from pymc_marketing.mmm.utility import UtilityFunctionType, average_response
+from pymc_marketing.mmm.utils import UtilityFunctionType, average_response
 from pymc_marketing.pytensor_utils import merge_models
 
 # Delayed import inside methods to avoid circular dependency on pytensor_utils

pymc_marketing/mmm/mmm.py

@@ -52,9 +52,10 @@
 from pymc_marketing.mmm.preprocessing import MaxAbsScaleChannels, MaxAbsScaleTarget
 from pymc_marketing.mmm.scaling import Scaling, VariableScaling
 from pymc_marketing.mmm.tvp import create_time_varying_gp_multiplier, infer_time_index
-from pymc_marketing.mmm.utility import UtilityFunctionType, average_response
 from pymc_marketing.mmm.utils import (
+    UtilityFunctionType,
     apply_sklearn_transformer_across_dim,
+    average_response,
     create_new_spend_data,
 )
 from pymc_marketing.mmm.validating import ValidateControlColumns

pymc_marketing/mmm/multidimensional.py

@@ -199,9 +199,10 @@
 from pymc_marketing.mmm.scaling import Scaling, VariableScaling
 from pymc_marketing.mmm.sensitivity_analysis import SensitivityAnalysis
 from pymc_marketing.mmm.tvp import create_hsgp_from_config, infer_time_index
-from pymc_marketing.mmm.utility import UtilityFunctionType, average_response
 from pymc_marketing.mmm.utils import (
+    UtilityFunctionType,
     add_noise_to_channel_allocation,
+    average_response,
     create_zero_dataset,
 )
 from pymc_marketing.model_builder import (