refactor(logs): add single logger

auton_survival/__init__.py

@@ -472,9 +472,3 @@ class is a composite transform that does both Imputing ***and*** Scaling with
 from .models.dcm import DeepCoxMixtures
 from .models.cph import DeepCoxPH, DeepRecurrentCoxPH
 from .models.cmhe import DeepCoxMixturesHeterogenousEffects
-
-import warnings
-from tqdm.auto import tqdm
-import logging
-
-logging.basicConfig()

auton_survival/experiments.py

@@ -37,9 +37,7 @@
 from tqdm import tqdm
 
 
-import logging
-
-logger = logging.getLogger(__name__)
+from auton_survival.logging import logger
 
 
 class SurvivalRegressionCV:

auton_survival/logging.py

@@ -0,0 +1,4 @@
+import logging
+
+LOGGER_NAME = "auton_survival"
+logger = logging.getLogger(LOGGER_NAME)

auton_survival/metrics.py

@@ -35,9 +35,7 @@
 
 import warnings
 
-import logging
-
-logger = logging.getLogger(__name__)
+from auton_survival.logging import logger
 
 
 def treatment_effect(

auton_survival/models/cmhe/__init__.py

@@ -85,9 +85,7 @@
 
 from auton_survival.utils import _dataframe_to_array
 
-import logging
-
-logger = logging.getLogger(__name__)
+from auton_survival.logging import logger
 
 
 class DeepCoxMixturesHeterogenousEffects:

auton_survival/models/cmhe/cmhe_utilities.py

@@ -40,9 +40,7 @@
     smooth_bl_survival,
 )
 
-import logging
-
-logger = logging.getLogger(__name__)
+from auton_survival.logging import logger
 
 
 def get_likelihood(model, breslow_splines, x, t, e, a):

auton_survival/models/cph/__init__.py

@@ -37,9 +37,7 @@
 from auton_survival.models.utils.recurrent_nn_utils import _get_padded_targets
 
 
-import logging
-
-logger = logging.getLogger(__name__)
+from auton_survival.logging import logger
 
 
 DcphModel = namedtuple("DcphModel", ["module", "breslow"])

auton_survival/models/cph/dcph_utilities.py

@@ -19,9 +19,7 @@
     partial_ll_loss,
 )
 
-import logging
-
-logger = logging.getLogger(__name__)
+from auton_survival.logging import logger
 
 
 def fit_breslow(model, x, t, e):

auton_survival/models/dcm/__init__.py

@@ -59,9 +59,7 @@
 
 from auton_survival.utils import _dataframe_to_array
 
-import logging
-
-logger = logging.getLogger(__name__)
+from auton_survival.logging import logger
 
 
 class DeepCoxMixtures:

auton_survival/models/dcm/dcm_utilities.py

@@ -24,9 +24,7 @@
     smooth_bl_survival,
 )
 
-import logging
-
-logger = logging.getLogger(__name__)
+from auton_survival.logging import logger
 
 
 def get_likelihood(model, breslow_splines, x, t, e):

auton_survival/models/dsm/__init__.py

@@ -183,9 +183,7 @@
 __pdoc__["DSMBase"] = False
 
 
-import logging
-
-logger = logging.getLogger(__name__)
+from auton_survival.logging import logger
 
 
 class DSMBase:

auton_survival/models/dsm/dsm_utilities.py

@@ -39,9 +39,7 @@
 import gc
 
 
-import logging
-
-logger = logging.getLogger(__name__)
+from auton_survival.logging import logger
 
 
 def pretrain_dsm(

auton_survival/phenotyping.py

@@ -38,9 +38,7 @@
 from auton_survival.utils import _get_method_kwargs
 from auton_survival.experiments import CounterfactualSurvivalRegressionCV
 
-import logging
-
-logger = logging.getLogger(__name__)
+from auton_survival.logging import logger
 
 
 class Phenotyper:

auton_survival/reporting.py

@@ -7,9 +7,7 @@
 from lifelines.plotting import add_at_risk_counts
 
 
-import logging
-
-logger = logging.getLogger(__name__)
+from auton_survival.logging import logger
 
 
 def plot_kaplanmeier(outcomes, groups=None, plot_counts=False, **kwargs):