add typing module in api to fix docs and relayed some input data atrr…

…ibutes to model

batchglm/api/__init__.py

@@ -3,5 +3,6 @@
 
 from . import models
 from . import data
+from . import typing
 from . import utils
 from .. import pkg_constants

batchglm/api/typing.py

@@ -0,0 +1,2 @@
+from batchglm.models.base.estimator import EstimatorBaseTyping
+from batchglm.models.base.input import InputDataBaseTyping

batchglm/models/base/__init__.py

@@ -1,4 +1,4 @@
-from .input import _InputDataBase
-from .estimator import _EstimatorBase
+from .input import _InputDataBase, InputDataBaseTyping
+from .estimator import _EstimatorBase, EstimatorBaseTyping
 from .model import _ModelBase
 from .simulator import _SimulatorBase

batchglm/models/base/estimator.py

@@ -291,3 +291,9 @@ def _plot_deviation(
         else:
             return
 
+
+class EstimatorBaseTyping(_EstimatorBase):
+    r"""
+    Estimator base class used for typing in other packages.
+    """
+

batchglm/models/base/input.py

@@ -90,3 +90,8 @@ def fetch_x_sparse(self, idx):
             data_idx = np.squeeze(data_idx, axis=0)
 
         return data_idx, data_val, data_shape
+
+class InputDataBaseTyping:
+    """
+    Input data base class  used for typing in other packages.
+    """

batchglm/models/base/model.py

@@ -1,5 +1,4 @@
 import abc
-import numpy as np
 from typing import Union, Any, Dict, Iterable
 import logging
 

batchglm/models/base_glm/input.py

@@ -17,6 +17,10 @@ class InputDataGLM(_InputDataBase):
     """
     Input data for Generalized Linear Models (GLMs).
     """
+    loc_names: list
+    design_loc_names: list
+    scale_names: list
+    design_scale_names: list
 
     def __init__(
             self,
@@ -94,8 +98,8 @@ def __init__(
 
         self.design_loc = design_loc
         self.design_scale = design_scale
-        self.design_loc_names = design_loc_names
-        self.design_scale_names = design_scale_names
+        self._design_loc_names = design_loc_names
+        self._design_scale_names = design_scale_names
 
         constraints_loc, loc_names = parse_constraints(
             dmat=design_loc,
@@ -111,11 +115,27 @@ def __init__(
         )
         self.constraints_loc = constraints_loc
         self.constraints_scale = constraints_scale
-        self.loc_names = loc_names
-        self.scale_names = scale_names
+        self._loc_names = loc_names
+        self._scale_names = scale_names
 
         self.size_factors = size_factors
 
+    @property
+    def design_loc_names(self):
+        return self._design_loc_names
+
+    @property
+    def design_scale_names(self):
+        return self._design_scale_names
+
+    @property
+    def loc_names(self):
+        return self._loc_names
+
+    @property
+    def scale_names(self):
+        return self._scale_names
+
     @property
     def num_design_loc_params(self):
         return self.design_loc.shape[1]

batchglm/models/base_glm/model.py

@@ -7,6 +7,7 @@
     anndata = None
 
 from .external import _ModelBase
+from .input import InputDataGLM
 
 
 class _ModelGLM(_ModelBase, metaclass=abc.ABCMeta):
@@ -26,7 +27,7 @@ class _ModelGLM(_ModelBase, metaclass=abc.ABCMeta):
 
     def __init__(
             self,
-            input_data
+            input_data: InputDataGLM
     ):
         _ModelBase.__init__(
             self=self,
@@ -63,6 +64,34 @@ def constraints_scale(self) -> np.ndarray:
         else:
             return self.input_data.constraints_scale
 
+    @property
+    def design_loc_names(self) -> list:
+        if self.input_data is None:
+            return None
+        else:
+            return self.input_data.design_loc_names
+
+    @property
+    def design_scale_names(self) -> list:
+        if self.input_data is None:
+            return None
+        else:
+            return self.input_data.design_scale_names
+
+    @property
+    def loc_names(self) -> list:
+        if self.input_data is None:
+            return None
+        else:
+            return self.input_data.loc_names
+
+    @property
+    def scale_names(self) -> list:
+        if self.input_data is None:
+            return None
+        else:
+            return self.input_data.scale_names
+
     @abc.abstractmethod
     def eta_loc(self) -> np.ndarray:
         pass