StereoExpData supports multiple spatial infomation.

stereo/algorithm/paste/helper.py

@@ -252,15 +252,11 @@ def stack_slices_pairwise(
 
     # new_slices = []
     for i in range(len(slices)):
-        if isinstance(slices[i], AnnBasedStereoExpData):
-            if slices[i].position_z is not None:
-                slices[i].adata.obsm['spatial_paste_pairwise'] = np.concatenate((new_coor[i], slices[i].position_z), axis=1)
-            else:
-                slices[i].adata.obsm['spatial_paste_pairwise'] = new_coor[i]
-            slices[i].spatial_key = 'spatial_paste_pairwise'
+        if slices[i].position_z is not None:
+            slices[i].cells_matrix['spatial_paste_pairwise'] = np.concatenate((new_coor[i], slices[i].position_z), axis=1)
         else:
-            slices[i].raw_position = slices[i].position
-            slices[i].position = new_coor[i]
+            slices[i].cells_matrix['spatial_paste_pairwise'] = new_coor[i]
+        slices[i].spatial_key = 'spatial_paste_pairwise'
 
     if not output_params:
         return slices
@@ -321,25 +317,17 @@ def stack_slices_center(
         new_coor.append(y)
 
     for i in range(len(slices)):
-        if isinstance(slices[i], AnnBasedStereoExpData):
-            if slices[i].position_z is not None:
-                slices[i].adata.obsm['spatial_paste_center'] = np.concatenate((new_coor[i], slices[i].position_z), axis=1)
-            else:
-                slices[i].adata.obsm['spatial_paste_center'] = new_coor[i]
-            slices[i].spatial_key = 'spatial_paste_center'
+        if slices[i].position_z is not None:
+            slices[i].cells_matrix['spatial_paste_center'] = np.concatenate((new_coor[i], slices[i].position_z), axis=1)
         else:
-            slices[i].raw_position = slices[i].position
-            slices[i].position = new_coor[i]
-
-    if isinstance(center_slice, AnnBasedStereoExpData):
-        if center_slice.position_z is not None:
-            center_slice.adata.obsm['spatial_paste_center'] = np.concatenate((center_slice.position, center_slice.position_z), axis=1)
-        else:
-            center_slice.adata.obsm['spatial_paste_center'] = c
-        center_slice.spatial_key = 'spatial_paste_center'
+            slices[i].cells_matrix['spatial_paste_center'] = new_coor[i]
+        slices[i].spatial_key = 'spatial_paste_center'
+    if center_slice.position_z is not None:
+        center_slice.cells_matrix['spatial_paste_center'] = np.concatenate((center_slice.position, center_slice.position_z), axis=1)
     else:
-        center_slice.raw_position = center_slice.position
-        center_slice.position = c
+        center_slice.cells_matrix['spatial_paste_center'] = c
+    center_slice.spatial_key = 'spatial_paste_center'
+
     if not output_params:
         return center_slice, slices
     else:

stereo/algorithm/paste/paste.py

@@ -5,13 +5,16 @@
     Optional
 )
 
+try:
+    from tensorflow.python.ops.numpy_ops import np_config
+    np_config.enable_numpy_behavior()
+except:
+    pass
+
 from stereo.algorithm.ms_algorithm_base import MSDataAlgorithmBase
 from stereo.log_manager import logger
-from .helper import stack_slices_center
-from .helper import stack_slices_pairwise
-from .methods import center_align
-from .methods import pairwise_align
-
+from .helper import stack_slices_center, stack_slices_pairwise
+from .methods import center_align, pairwise_align
 
 class Paste(MSDataAlgorithmBase):
     def main(
@@ -33,12 +36,6 @@ def main(
         """
         if method not in ('pairwise', 'center'):
             raise ValueError(f'Error method({method}), it must be one of pairwise and center')
-
-        try:
-            from tensorflow.python.ops.numpy_ops import np_config
-            np_config.enable_numpy_behavior()
-        except:
-            pass
 
         logger.info(f'Using method {method}')
         if method == 'pairwise':

stereo/algorithm/st_gears/main.py

@@ -1,5 +1,11 @@
 from typing import Optional, Union, List
 
+try:
+    from tensorflow.python.ops.numpy_ops import np_config
+    np_config.enable_numpy_behavior()
+except:
+    pass
+
 from stereo.algorithm.ms_algorithm_base import MSDataAlgorithmBase
 from stereo.core.stereo_exp_data import AnnBasedStereoExpData
 from stereo.io.reader import stereo_to_anndata

stereo/core/__init__.py

@@ -7,5 +7,5 @@
 @time:2021/03/17
 """
 # flake8: noqa
-from .st_pipeline import StPipeline
-from .stereo_exp_data import StereoExpData
+from .st_pipeline import StPipeline, AnnBasedStPipeline
+from .stereo_exp_data import StereoExpData, AnnBasedStereoExpData

stereo/core/cell.py

@@ -190,11 +190,10 @@ def sub_set(self, index):
         :param index: a numpy array of index info.
         :return: the subset of Cell object.
         """
-
-        if self.cell_border is not None:
-            self.cell_border = self.cell_border[index]
         if isinstance(index, pd.Series):
             index = index.to_numpy()
+        if self.cell_border is not None:
+            self.cell_border = self.cell_border[index]
         self._obs = self._obs.iloc[index].copy()
         for col in self._obs.columns:
             if self._obs[col].dtype.name == 'category':
@@ -303,6 +302,10 @@ def __contains__(self, item):
     def _obs(self):
         return self.__based_ann_data.obs
 
+    @property
+    def obs(self):
+        return self.__based_ann_data.obs
+
     @property
     def matrix(self):
         return self.__based_ann_data.obsm

stereo/core/ms_data.py

@@ -6,7 +6,10 @@
 import numpy as np
 import pandas as pd
 
-from . import StPipeline, StereoExpData
+from . import(
+    StPipeline, AnnBasedStPipeline,
+    StereoExpData, AnnBasedStereoExpData
+)
 from .ms_pipeline import MSDataPipeLine
 from ..plots.plot_collection import PlotCollection
 
@@ -270,16 +273,35 @@ class _MSDataStruct(object):
     _data_dict: Dict[int, str] = field(default_factory=dict)
     __idx_generator: int = _default_idx()
 
+    def __check_data_list(self, data_list):
+        if not isinstance(data_list, list):
+            raise TypeError('data_list must be a list object')
+        first_data = data_list[0]
+        for data in data_list[1:]:
+            if type(data) != type(first_data):
+                raise TypeError('each data in data_list must be the same type, available types: StereoExpData and AnnBasedStereoExpData')
+        return data_list
+
     def __post_init__(self) -> object:
         while len(self._data_list) > len(self._names):
             self._names.append(self.__get_auto_key())
         if not self._name_dict or not self._data_dict:
             self.reset_name(default_key=False)
+        self.__check_data_list(self._data_list)
         return self
+
+    def __iter__(self):
+        return iter(self._data_list)
 
     @property
     def data_list(self):
         return self._data_list
+
+    @data_list.setter
+    def data_list(self, data_list: List[StereoExpData]):
+        self.__check_data_list(data_list)
+        assert len(data_list) == len(self._names), 'length of data_list must be equal to length of names'
+        self._data_list = list(data_list)
 
     @property
     def merged_data(self):
@@ -729,7 +751,7 @@ def integrate(self, scope=None, remove_existed=False, **kwargs):
                 batch_tags = None
             else:
                 batch_tags = [self._names.index(name) for name in self[scope].names]
-            merged_data = merge(*data_list, var_type=self._var_type, batch_tags=batch_tags)
+            merged_data = merge(*data_list, var_type=self._var_type, batch_tags=batch_tags, **kwargs)
         else:
             merged_data = deepcopy(data_list[0])
             batch = self._names.index(self[scope].names[0])
@@ -1066,5 +1088,5 @@ def write(self, filename, to_mudata=False):
             return write_h5mu(self, filename)
 
 
-TL = type('TL', (MSDataPipeLine,), {'ATTR_NAME': 'tl', "BASE_CLASS": StPipeline})
-PLT = type('PLT', (MSDataPipeLine,), {'ATTR_NAME': 'plt', "BASE_CLASS": PlotCollection})
+TL = type('TL', (MSDataPipeLine,), {'ATTR_NAME': 'tl', "BASE_CLASS": None})
+PLT = type('PLT', (MSDataPipeLine,), {'ATTR_NAME': 'plt', "BASE_CLASS": None})

stereo/core/ms_pipeline.py

@@ -24,7 +24,7 @@ def __getitem__(self, item):
 
 class MSDataPipeLine(object):
     ATTR_NAME = 'tl'
-    BASE_CLASS = StPipeline
+    BASE_CLASS = None
 
     def __init__(self, _ms_data):
         super().__init__()
@@ -34,6 +34,7 @@ def __init__(self, _ms_data):
         self._key_record = dict()
         self.__mode = "integrate"
         self.__scope = slice(None)
+        self.__class__.BASE_CLASS = getattr(self.ms_data[0], self.__class__.ATTR_NAME).__class__
 
     @property
     def result(self):
@@ -91,12 +92,6 @@ def _use_integrate_method(self, item, *args, **kwargs):
         scope = kwargs.get("scope", slice(None))
         del kwargs["scope"]
 
-        # if item in {"cal_qc", "filter_cells", "filter_genes", "sctransform", "log1p", "normalize_total",
-        #             "scale", "raw_checkpoint", "batches_integrate"}:
-        #     if scope != slice(None):
-        #         raise Exception(f'{item} use integrate should use all sample')
-        #     ms_data_view = self.ms_data
-        # elif scope == slice(None):
         if len(self.ms_data[scope]) == len(self.ms_data):
             ms_data_view = self.ms_data
             if ms_data_view.merged_data is None:
@@ -107,15 +102,8 @@ def _use_integrate_method(self, item, *args, **kwargs):
         scope_key = self.ms_data.generate_scope_key(ms_data_view._names)
         self.ms_data.scopes_data[scope_key] = ms_data_view.merged_data
 
-        # def set_result_key_method(key):
-        #     self.result_keys.setdefault(scope_key, [])
-        #     if key in self.result_keys[scope_key]:
-        #         self.result_keys[scope_key].remove(key)
-        #     self.result_keys[scope_key].append(key)
-
-        # ms_data_view.merged_data.tl.result.set_result_key_method = set_result_key_method
-
-        new_attr = self.__class__.BASE_CLASS.__dict__.get(item, None)
+        # new_attr = self.__class__.BASE_CLASS.__dict__.get(item, None)
+        new_attr = getattr(self.__class__.BASE_CLASS, item, None)
         if new_attr is None:
             if self.__class__.ATTR_NAME == "tl":
                 from stereo.algorithm.algorithm_base import AlgorithmBase
@@ -134,7 +122,8 @@ def _use_integrate_method(self, item, *args, **kwargs):
 
         logger.info(f'data_obj(idx=0) in ms_data start to run {item}')
         return new_attr(
-            ms_data_view.merged_data.__getattribute__(self.__class__.ATTR_NAME),
+            # ms_data_view.merged_data.__getattribute__(self.__class__.ATTR_NAME),
+            getattr(ms_data_view.merged_data, self.__class__.ATTR_NAME),
             *args,
             **kwargs
         )
@@ -146,23 +135,26 @@ def _run_isolated_method(self, item, *args, **kwargs):
         if "scope" in kwargs:
             del kwargs["scope"]
 
-        new_attr = self.__class__.BASE_CLASS.__dict__.get(item, None)
+        # new_attr = self.__class__.BASE_CLASS.__dict__.get(item, None)
+        new_attr = getattr(self.__class__.BASE_CLASS, item, None)
         if self.__class__.ATTR_NAME == 'tl':
             n_jobs = min(len(ms_data_view.data_list), cpu_count())
         else:
             n_jobs = 1
         if new_attr:
-            def log_delayed_task(idx, *arg, **kwargs):
+            def log_delayed_task(idx, obj, *arg, **kwargs):
                 logger.info(f'data_obj(idx={idx}) in ms_data start to run {item}')
                 if self.__class__.ATTR_NAME == 'plt':
                     out_path = kwargs.get('out_path', None)
                     if out_path is not None:
                         path_name, ext = os.path.splitext(out_path)
                         kwargs['out_path'] = f'{path_name}_{idx}{ext}'
-                new_attr(*arg, **kwargs)
+                tl_or_plt = getattr(obj, self.__class__.ATTR_NAME)
+                new_attr(tl_or_plt, *arg, **kwargs)
 
             Parallel(n_jobs=n_jobs, backend='threading', verbose=100)(
-                delayed(log_delayed_task)(idx, obj.__getattribute__(self.__class__.ATTR_NAME), *args, **kwargs)
+                # delayed(log_delayed_task)(idx, obj.__getattribute__(self.__class__.ATTR_NAME), *args, **kwargs)
+                delayed(log_delayed_task)(idx, obj, *args, **kwargs)
                 for idx, obj in enumerate(ms_data_view.data_list)
             )
         else: