rename X_approx_distribution to X_approximate_distribution (#2337)

backend/czi_hosted/common/config/dataset_config.py

@@ -44,7 +44,7 @@ class DatasetConfig(BaseConfig):
             self.diffexp__lfc_cutoff = default_config["diffexp"]["lfc_cutoff"]
             self.diffexp__top_n = default_config["diffexp"]["top_n"]
 
-            self.X_approx_distribution = default_config["X_approx_distribution"]
+            self.X_approximate_distribution = default_config["X_approximate_distribution"]
 
         except KeyError as e:
             raise ConfigurationError(f"Unexpected config: {str(e)}")
@@ -60,7 +60,7 @@ class DatasetConfig(BaseConfig):
         self.handle_user_annotations(context)
         self.handle_embeddings()
         self.handle_diffexp(context)
-        self.handle_X_approx_distribution()
+        self.handle_X_approximate_distribution()
 
     def handle_app(self):
         self.validate_correct_type_of_configuration_attribute("app__scripts", list)
@@ -203,9 +203,9 @@ class DatasetConfig(BaseConfig):
                         "running differential expression may take longer or fail."
                     )
 
-    def handle_X_approx_distribution(self):
-        self.validate_correct_type_of_configuration_attribute("X_approx_distribution", str)
-        if self.X_approx_distribution not in ["normal", "count"]:
+    def handle_X_approximate_distribution(self):
+        self.validate_correct_type_of_configuration_attribute("X_approximate_distribution", str)
+        if self.X_approximate_distribution not in ["normal", "count"]:
             raise ConfigurationError(
-                "X_approx_distribution has unknown value -- must be 'normal' or 'count'."
+                "X_approximate_distribution has unknown value -- must be 'normal' or 'count'."
             )

backend/czi_hosted/data_anndata/anndata_adaptor.py

@@ -8,7 +8,7 @@ from scipy import sparse
 
 import backend.common.compute.diffexp_generic as diffexp_generic
 from backend.common.colors import convert_anndata_category_colors_to_cxg_category_colors
-from backend.common.constants import Axis, MAX_LAYOUTS, XApproxDistribution
+from backend.common.constants import Axis, MAX_LAYOUTS, XApproximateDistribution
 from backend.czi_hosted.common.corpora import corpora_get_props_from_anndata
 from backend.common.errors import PrepareError, DatasetAccessError, ConfigurationError
 from backend.common.utils.type_conversion_utils import get_schema_type_hint_of_array
@@ -28,7 +28,7 @@ class AnndataAdaptor(DataAdaptor):
     def __init__(self, data_locator, app_config=None, dataset_config=None):
         super().__init__(data_locator, app_config, dataset_config)
         self.data = None
-        self.X_approx_distribution = None
+        self.X_approximate_distribution = None
         self._load_data(data_locator)
         self._validate_and_initialize()
 
@@ -191,9 +191,9 @@ class AnndataAdaptor(DataAdaptor):
         self.gene_count = self.data.shape[1]
         self._create_schema()
 
-        if self.dataset_config.X_approx_distribution == "auto":
-            raise ConfigurationError("X-approx-distribution 'auto' mode unsupported.")
-        self.X_approx_distribution = self.dataset_config.X_approx_distribution
+        if self.dataset_config.X_approximate_distribution == "auto":
+            raise ConfigurationError("X-approximate-distribution 'auto' mode unsupported.")
+        self.X_approximate_distribution = self.dataset_config.X_approximate_distribution
 
         # heuristic
         n_values = self.data.shape[0] * self.data.shape[1]
@@ -327,8 +327,8 @@ class AnndataAdaptor(DataAdaptor):
         X = self.data.X[obs_mask, var_mask]
         return X
 
-    def get_X_approx_distribution(self) -> XApproxDistribution:
-        return self.X_approx_distribution
+    def get_X_approximate_distribution(self) -> XApproximateDistribution:
+        return self.X_approximate_distribution
 
     def get_shape(self):
         return self.data.shape

backend/czi_hosted/data_common/data_adaptor.py

@@ -7,7 +7,7 @@ from scipy import sparse
 from server_timing import Timing as ServerTiming
 
 from backend.czi_hosted.common.config.app_config import AppConfig
-from backend.common.constants import Axis, XApproxDistribution
+from backend.common.constants import Axis, XApproximateDistribution
 from backend.common.errors import (
     FilterError,
     JSONEncodingValueError,
@@ -84,7 +84,7 @@ class DataAdaptor(metaclass=ABCMeta):
         pass
 
     @abstractmethod
-    def get_X_approx_distribution(self) -> XApproxDistribution:
+    def get_X_approximate_distribution(self) -> XApproximateDistribution:
         """return the approximate distribution of the X matrix."""
         pass
 

backend/czi_hosted/data_cxg/cxg_adaptor.py

@@ -8,7 +8,7 @@ import pandas as pd
 import tiledb
 from server_timing import Timing as ServerTiming
 
-from backend.common.constants import Axis, XApproxDistribution
+from backend.common.constants import Axis, XApproximateDistribution
 from backend.common.errors import DatasetAccessError, ConfigurationError
 from backend.czi_hosted.common.immutable_kvcache import ImmutableKVCache
 from backend.common.utils.type_conversion_utils import get_schema_type_hint_from_dtype
@@ -37,7 +37,7 @@ class CxgAdaptor(DataAdaptor):
         self.lsuri_results = ImmutableKVCache(lambda key: self._lsuri(uri=key, tiledb_ctx=self.tiledb_ctx))
         self.arrays = ImmutableKVCache(lambda key: self._open_array(uri=key, tiledb_ctx=self.tiledb_ctx))
         self.schema = None
-        self.X_approx_distribution = None
+        self.X_approximate_distribution = None
 
         self._validate_and_initialize()
 
@@ -176,9 +176,9 @@ class CxgAdaptor(DataAdaptor):
         if cxg_version not in ["0.0", "0.1", "0.2.0"]:
             raise DatasetAccessError(f"cxg matrix is not valid: {self.url}")
 
-        if self.dataset_config.X_approx_distribution == "auto":
-            raise ConfigurationError("X-approx-distribution 'auto' mode unsupported.")
-        self.X_approx_distribution = self.dataset_config.X_approx_distribution
+        if self.dataset_config.X_approximate_distribution == "auto":
+            raise ConfigurationError("X-approximate-distribution 'auto' mode unsupported.")
+        self.X_approximate_distribution = self.dataset_config.X_approximate_distribution
 
         self.title = title
         self.about = about
@@ -286,8 +286,8 @@ class CxgAdaptor(DataAdaptor):
                 data = X.multi_index[obs_items, var_items][""]
             return data
 
-    def get_X_approx_distribution(self) -> XApproxDistribution:
-        return self.X_approx_distribution
+    def get_X_approximate_distribution(self) -> XApproximateDistribution:
+        return self.X_approximate_distribution
 
     def get_shape(self):
         X = self.open_array("X")

backend/czi_hosted/default_config.py

@@ -203,7 +203,7 @@ dataset:
     lfc_cutoff: 0.01
     top_n: 10
 
-  X_approx_distribution: normal # currently fixed config
+  X_approximate_distribution: normal # currently fixed config
 
 external:
   # You can retrieve configuration parameters from this config file, the environment,