Reorganize order of methods in engine and rest (#305)

server/app/driver/driver.py

@@ -1,5 +1,14 @@
 from abc import ABCMeta, abstractmethod
 
+"""
+Sort order for methods
+1. Initialize
+2. Helper
+3. Filter
+4. Data & Metadata
+5. Computation
+"""
+
 
 class CXGDriver(metaclass=ABCMeta):
 
@@ -50,7 +59,7 @@ class CXGDriver(metaclass=ABCMeta):
         See REST specs for info on filter format:
         https://docs.google.com/document/d/1Fxjp1SKtCk7l8QP9-7KAjGXL0eldi_qEnNT0NmlGzXI/edit#heading=h.8qc9q57amldx
 
-        :param filter: dictionary with filter parames
+        :param filter: dictionary with filter params
         :return: View into scanpy object with cells/genes filtered
         """
         pass
@@ -59,11 +68,37 @@ class CXGDriver(metaclass=ABCMeta):
     def annotation(self, df, axis, fields=None):
         """
         Gets annotation value for each observation
-
-        :param axis:
         :param df: from filter_cells, dataframe
+        :param axis: string obs or var
         :param fields: list of keys for annotation to return, returns all annotation values if not set.
-        :return: dict: names - list of fields in order, data - list of lists or metadata [idx, val1, val2...]
+        :return: dict: names - list of fields in order, data - list of lists or metadata
+        [observation ids, val1, val2...]
+        """
+        pass
+
+    @abstractmethod
+    def data_frame(self, df, axis):
+        """
+        Retrieves data for each variable for observations in data frame
+        :param df: from filter_cells, dataframe
+        :param axis: string obs or var
+        :return: {
+            "var": list of variable ids,
+            "obs": [cellid, var1 expression, var2 expression, ...],
+        }
+        """
+        pass
+
+    @abstractmethod
+    def diffexp(self, df1, df2, top_n):
+        """
+        Computes the top differentially expressed variables between two observation sets. If dataframes
+        contain a subset of variables, then statistics for all variables will be returned, otherwise
+        only the top N vars will be returned.
+        :param df1: from filter_cells, dataframe containing first set of observations
+        :param df2: from filter_cells, dataframe containing second set of observations
+        :param top_n: Limit results to top N (Top var mode only)
+        :return: top genes, stats and expression values for variables
         """
         pass
 
@@ -72,31 +107,6 @@ class CXGDriver(metaclass=ABCMeta):
         """
         Computes a n-d layout for cells through dimensionality reduction.
         :param df: from filter_cells, dataframe
-        :return:  [cellid, x, y]
+        :return:  [cellid, x, y, ...]
-        """
-        pass
-
-    @abstractmethod
-    def diffexp(self, df1, df2, genes):
-        """
-        Computes the top differentially expressed variables between two observation sets. If dataframes
-        contain a subset of variables, then statistics for all variables will be returned, otherwise
-        only the top N vars will be returned.
-        :param df1: from filter_cells, dataframe containing first set of observations
-        :param df2: from filter_cells, dataframe containing second set of observations
-        :param topN: Limit results to top N (Top var mode only)
-        :return: top genes, stats and expression values for variables
-        """
-        pass
-
-    @abstractmethod
-    def data_frame(self, df):
-        """
-        Retrieves expression for each gene for cells in data frame
-        :param df: from filter_cells, dataframe
-        :return: {
-            "var": list of variable ids,
-            "obs": [cellid, var1 expression, var2 expression, ...],
-        }
         """
         pass

server/app/rest_api/rest.py

@@ -12,6 +12,13 @@ from server.app.util.filter import parse_filter, QueryStringError
 from server.app.util.models import FilterModel
 from server.app.util.utils import MimeTypeError, get_mime_type
 
+"""
+Sort order for routes
+1. Initialize
+2. Data & Metadata
+3. Computation
+"""
+
 
 class SchemaAPI(Resource):
     @swagger.doc({
@@ -109,75 +116,6 @@ class ConfigAPI(Resource):
         return make_response(jsonify(config), HTTPStatus.OK)
 
 
-class LayoutObsAPI(Resource):
-    @swagger.doc({
-        "summary": "Get the default layout for all observations.",
-        "tags": ["layout"],
-        "parameters": [],
-        "responses": {
-            "200": {
-                "description": "layout",
-                "examples": {
-                    "application/json": {
-                        "layout": {
-                            "ndims": 2,
-                            "coordinates": [
-                                [0, 0.284483, 0.983744],
-                                [1, 0.038844, 0.739444]
-                            ]
-                        }
-                    }
-                }
-            }
-        }
-    })
-    def get(self):
-        return make_response((jsonify({"layout": current_app.data.layout(current_app.data.data)})), HTTPStatus.OK)
-
-    @swagger.doc({
-        "summary": "Observation layout for filtered subset.",
-        "tags": ["layout"],
-        "parameters": [
-            {
-                "name": "filter",
-                "description": "Complex Filter",
-                "in": "body",
-                "schema": FilterModel
-            }
-        ],
-        "responses": {
-            "200": {
-                "description": "layout",
-                "examples": {
-                    "application/json": {
-                        "layout": {
-                            "ndims": 2,
-                            "coordinates": [
-                                [0, 0.284483, 0.983744],
-                                [1, 0.038844, 0.739444]
-                            ]
-                        }
-                    }
-                }
-            },
-            "400": {
-                "description": "Malformed filter"
-            },
-            "403": {
-                "description": "Non-interactive request"
-            },
-        }
-    })
-    def post(self):
-        try:
-            df = current_app.data.filter_dataframe(request.get_json()["filter"])
-        except KeyError:
-            return make_response("Malformed filter", HTTPStatus.BAD_REQUEST)
-        if len(df.obs.index) > current_app.data.features["layout"]["obs"]["interactiveLimit"]:
-            return make_response("Non-interactive request", HTTPStatus.FORBIDDEN)
-        return make_response((jsonify({"layout": current_app.data.layout(df)})), HTTPStatus.OK)
-
-
 class AnnotationsObsAPI(Resource):
     @swagger.doc({
         "summary": "Fetch annotations (metadata) for all observations.",
@@ -367,112 +305,6 @@ class AnnotationsVarAPI(Resource):
         return make_response(jsonify(annotation_response), HTTPStatus.OK)
 
 
-class DiffExpObsAPI(Resource):
-    @swagger.doc({
-        "summary": "Generate differential expression (DE) statistics for two specified subsets of data, "
-                   "as indicated by the two provided observation complex filters",
-        "tags": ["diffexp"],
-        # TODO sort out params
-        # "parameters": [
-        #     # {
-        #     #     "in": "body",
-        #     #     "name": "mode",
-        #     #     "type": "string",
-        #     #     "required": True,
-        #     #     "description": "topN or varFilter"
-        #     # },
-        #     {
-        #         "in": "query",
-        #         "name": "count",
-        #         "type": "int32",
-        #         "description": "TopN mode: how many vars to return"
-        #     },
-        #     {
-        #         "in": "body",
-        #         "name": "varFilter",
-        #         "schema": FilterModel,
-        #         "description": "varFilter: Complex filter, only var for which vars to return"
-        #     },
-        #     {
-        #         "in": "body",
-        #         "name": "set1",
-        #         "schema": FilterModel,
-        #         "required": True,
-        #         "description": "Complex filter, only obs - observations in set1"
-        #     },
-        #     {
-        #         "in": "body",
-        #         "name": "set2",
-        #         "schema": FilterModel,
-        #         "description": "Complex filter, only obs - observations in set2. If not included, inverse of set1."
-        #     },
-        # ],
-        "responses": {
-            "200": {
-                "description": "Statistics are encoded as an array of arrays, with fields ordered as: "
-                               "varIndex, avgDiff,  pVal, pValAdj, set1AvgExp, set2AvgExp",
-                "examples": {
-                    "application/json": [
-                        [328, -2.569489, 2.655706e-63, 3.642036e-57, 383.393, 583.9],
-                        [1250, -2.569489, 2.655706e-63, 3.642036e-57, 383.393, 583.9],
-                    ]
-                }
-            },
-            "400": {
-                "description": "malformed filter"
-            },
-            "403": {
-                "description": "non-interactive request"
-            },
-            "501": {
-                "description": "diffexp is not implemented"
-            }
-        }
-    })
-    def post(self):
-        args = request.get_json()
-        # confirm mode is present and legal
-        try:
-            mode = DiffExpMode(args["mode"])
-        except KeyError:
-            return make_response("Error: mode is required", HTTPStatus.BAD_REQUEST)
-        except ValueError:
-            return make_response(f"Error: invalid mode option {args['mode']}", HTTPStatus.BAD_REQUEST)
-        # Validate filters
-        if mode == DiffExpMode.VAR_FILTER:
-            if "varFilter" not in args:
-                return make_response("varFilter is required when mode is set to varFilter ", HTTPStatus.BAD_REQUEST)
-            if Axis.OBS in args["varFilter"]["filter"]:
-                return make_response("Obs filter not allowed in varFilter", HTTPStatus.BAD_REQUEST)
-        if "set1" not in args:
-            return make_response("set1 is required.", HTTPStatus.BAD_REQUEST)
-        if Axis.VAR in args["set1"]["filter"]:
-            return make_response("Var filter not allowed for set1", HTTPStatus.BAD_REQUEST)
-        # set2
-        if "set2" not in args:
-            return make_response("Set2 as inverse of set1 is not implemented", HTTPStatus.NOT_IMPLEMENTED)
-        if Axis.VAR in args["set2"]["filter"]:
-            return make_response("Var filter not allowed for set2", HTTPStatus.BAD_REQUEST)
-        set1_filter = args["set1"]["filter"]
-        set2_filter = args.get("set2", {"filter": {}})["filter"]
-        if "varFilter" in args:
-            set1_filter[Axis.VAR] = args["varFilter"]["filter"][Axis.VAR]
-            set2_filter[Axis.VAR] = args["varFilter"]["filter"][Axis.VAR]
-        df1 = current_app.data.filter_dataframe(set1_filter, include_uns=False)
-        # TODO inverse
-        df2 = current_app.data.filter_dataframe(set2_filter, include_uns=False)
-        # exceeds size limit
-        if df1.shape[0] + df2.shape[0] > current_app.data.features["diffexp"]["interactiveLimit"]:
-            return make_response("Non-interactive request", HTTPStatus.FORBIDDEN)
-        # mode
-        count = args.get("count", None)
-        try:
-            diffexp = current_app.data.diffexp(df1, df2, count)
-        except ValueError as ve:
-            return make_response(ve.message, HTTPStatus.BAD_REQUEST)
-        return make_response(jsonify(diffexp), HTTPStatus.OK)
-
-
 class DataObsAPI(Resource):
     @swagger.doc({
         "summary": "Get data (expression values) from the dataframe.",
@@ -682,15 +514,193 @@ class DataVarAPI(Resource):
         return make_response((jsonify(current_app.data.data_frame(df, axis=Axis.VAR))), HTTPStatus.OK)
 
 
+class DiffExpObsAPI(Resource):
+    @swagger.doc({
+        "summary": "Generate differential expression (DE) statistics for two specified subsets of data, "
+                   "as indicated by the two provided observation complex filters",
+        "tags": ["diffexp"],
+        # TODO sort out params
+        # "parameters": [
+        #     # {
+        #     #     "in": "body",
+        #     #     "name": "mode",
+        #     #     "type": "string",
+        #     #     "required": True,
+        #     #     "description": "topN or varFilter"
+        #     # },
+        #     {
+        #         "in": "query",
+        #         "name": "count",
+        #         "type": "int32",
+        #         "description": "TopN mode: how many vars to return"
+        #     },
+        #     {
+        #         "in": "body",
+        #         "name": "varFilter",
+        #         "schema": FilterModel,
+        #         "description": "varFilter: Complex filter, only var for which vars to return"
+        #     },
+        #     {
+        #         "in": "body",
+        #         "name": "set1",
+        #         "schema": FilterModel,
+        #         "required": True,
+        #         "description": "Complex filter, only obs - observations in set1"
+        #     },
+        #     {
+        #         "in": "body",
+        #         "name": "set2",
+        #         "schema": FilterModel,
+        #         "description": "Complex filter, only obs - observations in set2. If not included, inverse of set1."
+        #     },
+        # ],
+        "responses": {
+            "200": {
+                "description": "Statistics are encoded as an array of arrays, with fields ordered as: "
+                               "varIndex, avgDiff,  pVal, pValAdj, set1AvgExp, set2AvgExp",
+                "examples": {
+                    "application/json": [
+                        [328, -2.569489, 2.655706e-63, 3.642036e-57, 383.393, 583.9],
+                        [1250, -2.569489, 2.655706e-63, 3.642036e-57, 383.393, 583.9],
+                    ]
+                }
+            },
+            "400": {
+                "description": "malformed filter"
+            },
+            "403": {
+                "description": "non-interactive request"
+            },
+            "501": {
+                "description": "diffexp is not implemented"
+            }
+        }
+    })
+    def post(self):
+        args = request.get_json()
+        # confirm mode is present and legal
+        try:
+            mode = DiffExpMode(args["mode"])
+        except KeyError:
+            return make_response("Error: mode is required", HTTPStatus.BAD_REQUEST)
+        except ValueError:
+            return make_response(f"Error: invalid mode option {args['mode']}", HTTPStatus.BAD_REQUEST)
+        # Validate filters
+        if mode == DiffExpMode.VAR_FILTER:
+            if "varFilter" not in args:
+                return make_response("varFilter is required when mode is set to varFilter ", HTTPStatus.BAD_REQUEST)
+            if Axis.OBS in args["varFilter"]["filter"]:
+                return make_response("Obs filter not allowed in varFilter", HTTPStatus.BAD_REQUEST)
+        if "set1" not in args:
+            return make_response("set1 is required.", HTTPStatus.BAD_REQUEST)
+        if Axis.VAR in args["set1"]["filter"]:
+            return make_response("Var filter not allowed for set1", HTTPStatus.BAD_REQUEST)
+        # set2
+        if "set2" not in args:
+            return make_response("Set2 as inverse of set1 is not implemented", HTTPStatus.NOT_IMPLEMENTED)
+        if Axis.VAR in args["set2"]["filter"]:
+            return make_response("Var filter not allowed for set2", HTTPStatus.BAD_REQUEST)
+        set1_filter = args["set1"]["filter"]
+        set2_filter = args.get("set2", {"filter": {}})["filter"]
+        if "varFilter" in args:
+            set1_filter[Axis.VAR] = args["varFilter"]["filter"][Axis.VAR]
+            set2_filter[Axis.VAR] = args["varFilter"]["filter"][Axis.VAR]
+        df1 = current_app.data.filter_dataframe(set1_filter, include_uns=False)
+        # TODO inverse
+        df2 = current_app.data.filter_dataframe(set2_filter, include_uns=False)
+        # exceeds size limit
+        if df1.shape[0] + df2.shape[0] > current_app.data.features["diffexp"]["interactiveLimit"]:
+            return make_response("Non-interactive request", HTTPStatus.FORBIDDEN)
+        # mode
+        count = args.get("count", None)
+        try:
+            diffexp = current_app.data.diffexp(df1, df2, count)
+        except ValueError as ve:
+            return make_response(ve.message, HTTPStatus.BAD_REQUEST)
+        return make_response(jsonify(diffexp), HTTPStatus.OK)
+
+
+class LayoutObsAPI(Resource):
+    @swagger.doc({
+        "summary": "Get the default layout for all observations.",
+        "tags": ["layout"],
+        "parameters": [],
+        "responses": {
+            "200": {
+                "description": "layout",
+                "examples": {
+                    "application/json": {
+                        "layout": {
+                            "ndims": 2,
+                            "coordinates": [
+                                [0, 0.284483, 0.983744],
+                                [1, 0.038844, 0.739444]
+                            ]
+                        }
+                    }
+                }
+            }
+        }
+    })
+    def get(self):
+        return make_response((jsonify({"layout": current_app.data.layout(current_app.data.data)})), HTTPStatus.OK)
+
+    @swagger.doc({
+        "summary": "Observation layout for filtered subset.",
+        "tags": ["layout"],
+        "parameters": [
+            {
+                "name": "filter",
+                "description": "Complex Filter",
+                "in": "body",
+                "schema": FilterModel
+            }
+        ],
+        "responses": {
+            "200": {
+                "description": "layout",
+                "examples": {
+                    "application/json": {
+                        "layout": {
+                            "ndims": 2,
+                            "coordinates": [
+                                [0, 0.284483, 0.983744],
+                                [1, 0.038844, 0.739444]
+                            ]
+                        }
+                    }
+                }
+            },
+            "400": {
+                "description": "Malformed filter"
+            },
+            "403": {
+                "description": "Non-interactive request"
+            },
+        }
+    })
+    def post(self):
+        try:
+            df = current_app.data.filter_dataframe(request.get_json()["filter"])
+        except KeyError:
+            return make_response("Malformed filter", HTTPStatus.BAD_REQUEST)
+        if len(df.obs.index) > current_app.data.features["layout"]["obs"]["interactiveLimit"]:
+            return make_response("Non-interactive request", HTTPStatus.FORBIDDEN)
+        return make_response((jsonify({"layout": current_app.data.layout(df)})), HTTPStatus.OK)
+
+
 def get_api_resources():
     bp = Blueprint("api", __name__, url_prefix="/api/v0.2")
     api = Api(bp, add_api_spec_resource=False)
+    # Initialization routes
     api.add_resource(SchemaAPI, "/schema")
     api.add_resource(ConfigAPI, "/config")
-    api.add_resource(LayoutObsAPI, "/layout/obs")
+    # Data routes
     api.add_resource(AnnotationsObsAPI, "/annotations/obs")
-    api.add_resource(DiffExpObsAPI, "/diffexp/obs")
     api.add_resource(AnnotationsVarAPI, "/annotations/var")
     api.add_resource(DataObsAPI, "/data/obs")
     api.add_resource(DataVarAPI, "/data/var")
+    # Computation routes
+    api.add_resource(DiffExpObsAPI, "/diffexp/obs")
+    api.add_resource(LayoutObsAPI, "/layout/obs")
     return api

server/app/scanpy_engine/scanpy_engine.py

@@ -11,6 +11,15 @@ from scipy import stats
 from server.app.driver.driver import CXGDriver
 from server.app.util.constants import Axis, DEFAULT_TOP_N, DiffExpMode
 
+"""
+Sort order for methods
+1. Initialize
+2. Helper
+3. Filter
+4. Data & Metadata
+5. Computation
+"""
+
 
 class ScanpyEngine(CXGDriver):
 
@@ -151,7 +160,7 @@ class ScanpyEngine(CXGDriver):
         Filter data based on index. ex. [1, 3, [111:200]]
         :param filter: subset of filter dict for obs/var:index
         :param index: np logical vector containing true for passing false for failing filter
-        :param axis: Axis
+        :param axis: string obs or var
         :return: np logical vector for whether the data passes the filter
         """
         if axis == Axis.OBS:
@@ -194,9 +203,8 @@ class ScanpyEngine(CXGDriver):
     def annotation(self, df, axis, fields=None):
         """
          Gets annotation value for each observation
-
-        :param axis:
         :param df: from filter_cells, dataframe
+        :param axis: string obs or var
         :param fields: list of keys for annotation to return, returns all annotation values if not set.
         :return: dict: names - list of fields in order, data - list of lists or metadata
         [observation ids, val1, val2...]
@@ -211,24 +219,37 @@ class ScanpyEngine(CXGDriver):
         }
 
     # @cache.memoize()
-    def layout(self, df):
+    def data_frame(self, df, axis):
         """
-        Computes a n-d layout for cells through dimensionality reduction.
+        Retrieves data for each variable for observations in data frame
         :param df: from filter_cells, dataframe
-        :return:  [cellid, x, y, ...]
+        :param axis: string obs or var
-        """
+        :return: {
-        # TODO Filtering cells is fine, but filtering genes does nothing because the neighbors are
+            "var": list of variable ids,
-        # calculated using the original vars (geneset) and this doesn’t get updated when you use less.
+            "obs": [cellid, var1 expression, var2 expression, ...],
-        # Need to recalculate neighbors (long) if user requests new layout filtered by var
-        getattr(sc.tl, self.layout_method)(df, random_state=123)
-        df_layout = df.obsm[f"X_{self.layout_method}"]
-        normalized_layout = DataFrame((df_layout - df_layout.min()) / (df_layout.max() - df_layout.min()),
-                                      index=df.obs.index)
-        return {
-            "ndims": normalized_layout.shape[1],
-            # reset_index gets obs' id into output
-            "coordinates": normalized_layout.reset_index().values.tolist()
         }
+        """
+        var_idx = df.var.index.tolist()
+        obs_idx = df.obs.index.tolist()
+        values = df.X
+        df_shape = df.shape
+        if df_shape[0] == 1:
+            values = values[None, :]
+        elif df_shape[1] == 1:
+            values = values[:, None]
+        if axis == Axis.OBS:
+            expression = DataFrame(values, index=obs_idx)
+            result = {
+                "var": var_idx,
+                "obs": expression.reset_index().values.tolist()
+            }
+        else:
+            expression = DataFrame(values.T, index=var_idx)
+            result = {
+                "obs": obs_idx,
+                "var": expression.reset_index().values.tolist(),
+            }
+        return result
 
     # @cache.memoize()
     def diffexp(self, df1, df2, top_n=None):
@@ -238,7 +259,7 @@ class ScanpyEngine(CXGDriver):
         only the top N vars will be returned.
         :param df1: from filter_cells, dataframe containing first set of observations
         :param df2: from filter_cells, dataframe containing second set of observations
-        :param topN: Limit results to top N (Top var mode only)
+        :param top_n: Limit results to top N (Top var mode only)
         :return: top genes, stats and expression values for variables
         """
         # If not the same genes, test is wrong!
@@ -280,33 +301,21 @@ class ScanpyEngine(CXGDriver):
         return sorted(result, key=lambda gene: gene[0])
 
     # @cache.memoize()
-    def data_frame(self, df, axis):
+    def layout(self, df):
         """
-        Retrieves data for each variable for observations in data frame
+        Computes a n-d layout for cells through dimensionality reduction.
         :param df: from filter_cells, dataframe
-        :return: {
+        :return:  [cellid, x, y, ...]
-            "var": list of variable ids,
-            "obs": [cellid, var1 expression, var2 expression, ...],
-        }
         """
-        var_idx = df.var.index.tolist()
+        # TODO Filtering cells is fine, but filtering genes does nothing because the neighbors are
-        obs_idx = df.obs.index.tolist()
+        # calculated using the original vars (geneset) and this doesn’t get updated when you use less.
-        values = df.X
+        # Need to recalculate neighbors (long) if user requests new layout filtered by var
-        df_shape = df.shape
+        getattr(sc.tl, self.layout_method)(df, random_state=123)
-        if df_shape[0] == 1:
+        df_layout = df.obsm[f"X_{self.layout_method}"]
-            values = values[None, :]
+        normalized_layout = DataFrame((df_layout - df_layout.min()) / (df_layout.max() - df_layout.min()),
-        elif df_shape[1] == 1:
+                                      index=df.obs.index)
-            values = values[:, None]
+        return {
-        if axis == Axis.OBS:
+            "ndims": normalized_layout.shape[1],
-            expression = DataFrame(values, index=obs_idx)
+            # reset_index gets obs' id into output
-            result = {
+            "coordinates": normalized_layout.reset_index().values.tolist()
-                "var": var_idx,
-                "obs": expression.reset_index().values.tolist()
         }
-        else:
-            expression = DataFrame(values.T, index=var_idx)
-            result = {
-                "obs": obs_idx,
-                "var": expression.reset_index().values.tolist(),
-            }
-        return result