refactor(logs): add better log config

auton_survival/__init__.py

@@ -475,6 +475,3 @@ class is a composite transform that does both Imputing ***and*** Scaling with
 
 import warnings
 from tqdm.auto import tqdm
-import logging
-
-logging.basicConfig()

auton_survival/experiments.py

@@ -35,9 +35,11 @@
 from sklearn.utils import shuffle
 
 from tqdm import tqdm
-import logging
 
-logger = logging.getLogger(__name__)
+
+from auton_survival.logging import LOGGER
+
+logger = LOGGER.getChild(__name__)
 
 
 class SurvivalRegressionCV:

auton_survival/logging.py

@@ -0,0 +1,3 @@
+import logging
+
+LOGGER = logging.getLogger("auton_survival")

auton_survival/metrics.py

@@ -32,10 +32,12 @@
 from scipy.optimize import fsolve
 from sklearn.metrics import auc
 from tqdm import tqdm
-import logging
+
 import warnings
 
-logger = logging.getLogger(__name__)
+from auton_survival.logging import LOGGER
+
+logger = LOGGER.getChild(__name__)
 
 
 def treatment_effect(

auton_survival/models/cmhe/__init__.py

@@ -75,7 +75,7 @@
 
 """
 
-import logging
+
 import numpy as np
 import torch
 
@@ -85,7 +85,9 @@
 
 from auton_survival.utils import _dataframe_to_array
 
-logger = logging.getLogger(__name__)
+from auton_survival.logging import LOGGER
+
+logger = LOGGER.getChild(__name__)
 
 
 class DeepCoxMixturesHeterogenousEffects:

auton_survival/models/cmhe/cmhe_utilities.py

@@ -21,7 +21,7 @@
 # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 # SOFTWARE.
 
-import logging
+
 import torch
 import numpy as np
 
@@ -40,7 +40,9 @@
     smooth_bl_survival,
 )
 
-logger = logging.getLogger(__name__)
+from auton_survival.logging import LOGGER
+
+logger = LOGGER.getChild(__name__)
 
 
 def get_likelihood(model, breslow_splines, x, t, e, a):

auton_survival/models/cph/__init__.py

@@ -24,7 +24,7 @@
 r""" Deep Cox Proportional Hazards Model"""
 
 from collections import namedtuple
-import logging
+
 import torch
 import numpy as np
 import random
@@ -37,7 +37,9 @@
 from auton_survival.models.utils.recurrent_nn_utils import _get_padded_targets
 
 
-logger = logging.getLogger(__name__)
+from auton_survival.logging import LOGGER
+
+logger = LOGGER.getChild(__name__)
 
 
 DcphModel = namedtuple("DcphModel", ["module", "breslow"])

auton_survival/models/cph/dcph_utilities.py

@@ -1,7 +1,7 @@
 import torch
 import numpy as np
 import pandas as pd
-import logging
+
 
 from sksurv.linear_model.coxph import BreslowEstimator
 
@@ -19,7 +19,9 @@
     partial_ll_loss,
 )
 
-logger = logging.getLogger(__name__)
+from auton_survival.logging import LOGGER
+
+logger = LOGGER.getChild(__name__)
 
 
 def fit_breslow(model, x, t, e):

auton_survival/models/dcm/__init__.py

@@ -50,7 +50,7 @@
 
 """
 
-import logging
+
 import torch
 import numpy as np
 
@@ -59,7 +59,9 @@
 
 from auton_survival.utils import _dataframe_to_array
 
-logger = logging.getLogger(__name__)
+from auton_survival.logging import LOGGER
+
+logger = LOGGER.getChild(__name__)
 
 
 class DeepCoxMixtures:

auton_survival/models/dcm/dcm_utilities.py

@@ -1,5 +1,5 @@
 import warnings
-import logging
+
 from matplotlib.pyplot import get
 
 import torch
@@ -24,7 +24,9 @@
     smooth_bl_survival,
 )
 
-logger = logging.getLogger(__name__)
+from auton_survival.logging import LOGGER
+
+logger = LOGGER.getChild(__name__)
 
 
 def get_likelihood(model, breslow_splines, x, t, e):

auton_survival/models/dsm/__init__.py

@@ -156,7 +156,7 @@
 
 """
 
-import logging
+
 import torch
 import numpy as np
 
@@ -183,7 +183,9 @@
 __pdoc__["DSMBase"] = False
 
 
-logger = logging.getLogger(__name__)
+from auton_survival.logging import LOGGER
+
+logger = LOGGER.getChild(__name__)
 
 
 class DSMBase:

auton_survival/models/dsm/dsm_utilities.py

@@ -37,10 +37,11 @@
 import numpy as np
 
 import gc
-import logging
 
 
-logger = logging.getLogger(__name__)
+from auton_survival.logging import LOGGER
+
+logger = LOGGER.getChild(__name__)
 
 
 def pretrain_dsm(

auton_survival/phenotyping.py

@@ -24,7 +24,7 @@
 """Utilities to phenotype individuals based on similar survival
 characteristics."""
 
-import logging
+
 from random import random
 import warnings
 import numpy as np
@@ -38,7 +38,9 @@
 from auton_survival.utils import _get_method_kwargs
 from auton_survival.experiments import CounterfactualSurvivalRegressionCV
 
-logger = logging.getLogger(__name__)
+from auton_survival.logging import LOGGER
+
+logger = LOGGER.getChild(__name__)
 
 
 class Phenotyper:

auton_survival/reporting.py

@@ -1,4 +1,3 @@
-import logging
 import numpy as np
 import pandas as pd
 
@@ -8,7 +7,9 @@
 from lifelines.plotting import add_at_risk_counts
 
 
-logger = logging.getLogger(__name__)
+from auton_survival.logging import LOGGER
+
+logger = LOGGER.getChild(__name__)
 
 
 def plot_kaplanmeier(outcomes, groups=None, plot_counts=False, **kwargs):