mirror of
https://github.com/chanzuckerberg/cellxgene.git
synced 2026-09-21 07:28:12 +08:00
Reorganize order of methods in engine and rest (#305)
This commit is contained in:
Charlotte Weaver
+45
-35
@@ -1,5 +1,14 @@
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from abc import ABCMeta, abstractmethod
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"""
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Sort order for methods
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1. Initialize
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2. Helper
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3. Filter
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4. Data & Metadata
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5. Computation
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"""
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class CXGDriver(metaclass=ABCMeta):
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@@ -45,12 +54,12 @@ class CXGDriver(metaclass=ABCMeta):
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@abstractmethod
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def filter_dataframe(self, filter):
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"""
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Filter cells from data and return a subset of the data. They can operate on both obs and var dimension with
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indexing and filtering by annotation value. Filters are combined with the and operator.
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See REST specs for info on filter format:
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https://docs.google.com/document/d/1Fxjp1SKtCk7l8QP9-7KAjGXL0eldi_qEnNT0NmlGzXI/edit#heading=h.8qc9q57amldx
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Filter cells from data and return a subset of the data. They can operate on both obs and var dimension with
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indexing and filtering by annotation value. Filters are combined with the and operator.
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See REST specs for info on filter format:
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https://docs.google.com/document/d/1Fxjp1SKtCk7l8QP9-7KAjGXL0eldi_qEnNT0NmlGzXI/edit#heading=h.8qc9q57amldx
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:param filter: dictionary with filter parames
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:param filter: dictionary with filter params
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:return: View into scanpy object with cells/genes filtered
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"""
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pass
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@@ -58,12 +67,38 @@ class CXGDriver(metaclass=ABCMeta):
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@abstractmethod
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def annotation(self, df, axis, fields=None):
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"""
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Gets annotation value for each observation
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:param axis:
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Gets annotation value for each observation
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:param df: from filter_cells, dataframe
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:param axis: string obs or var
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:param fields: list of keys for annotation to return, returns all annotation values if not set.
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:return: dict: names - list of fields in order, data - list of lists or metadata [idx, val1, val2...]
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:return: dict: names - list of fields in order, data - list of lists or metadata
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[observation ids, val1, val2...]
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"""
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pass
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@abstractmethod
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def data_frame(self, df, axis):
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"""
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Retrieves data for each variable for observations in data frame
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:param df: from filter_cells, dataframe
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:param axis: string obs or var
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:return: {
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"var": list of variable ids,
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"obs": [cellid, var1 expression, var2 expression, ...],
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}
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"""
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pass
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@abstractmethod
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def diffexp(self, df1, df2, top_n):
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"""
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Computes the top differentially expressed variables between two observation sets. If dataframes
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contain a subset of variables, then statistics for all variables will be returned, otherwise
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only the top N vars will be returned.
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:param df1: from filter_cells, dataframe containing first set of observations
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:param df2: from filter_cells, dataframe containing second set of observations
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:param top_n: Limit results to top N (Top var mode only)
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:return: top genes, stats and expression values for variables
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"""
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pass
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@@ -72,31 +107,6 @@ class CXGDriver(metaclass=ABCMeta):
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"""
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Computes a n-d layout for cells through dimensionality reduction.
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:param df: from filter_cells, dataframe
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:return: [cellid, x, y]
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"""
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pass
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@abstractmethod
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def diffexp(self, df1, df2, genes):
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"""
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Computes the top differentially expressed variables between two observation sets. If dataframes
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contain a subset of variables, then statistics for all variables will be returned, otherwise
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only the top N vars will be returned.
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:param df1: from filter_cells, dataframe containing first set of observations
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:param df2: from filter_cells, dataframe containing second set of observations
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:param topN: Limit results to top N (Top var mode only)
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:return: top genes, stats and expression values for variables
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"""
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pass
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@abstractmethod
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def data_frame(self, df):
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"""
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Retrieves expression for each gene for cells in data frame
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:param df: from filter_cells, dataframe
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:return: {
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"var": list of variable ids,
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"obs": [cellid, var1 expression, var2 expression, ...],
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}
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:return: [cellid, x, y, ...]
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"""
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pass
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+187
-177
@@ -12,6 +12,13 @@ from server.app.util.filter import parse_filter, QueryStringError
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from server.app.util.models import FilterModel
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from server.app.util.utils import MimeTypeError, get_mime_type
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"""
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Sort order for routes
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1. Initialize
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2. Data & Metadata
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3. Computation
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"""
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class SchemaAPI(Resource):
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@swagger.doc({
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@@ -109,75 +116,6 @@ class ConfigAPI(Resource):
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return make_response(jsonify(config), HTTPStatus.OK)
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class LayoutObsAPI(Resource):
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@swagger.doc({
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"summary": "Get the default layout for all observations.",
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"tags": ["layout"],
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"parameters": [],
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"responses": {
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"200": {
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"description": "layout",
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"examples": {
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"application/json": {
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"layout": {
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"ndims": 2,
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"coordinates": [
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[0, 0.284483, 0.983744],
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[1, 0.038844, 0.739444]
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]
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}
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}
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}
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}
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}
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})
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def get(self):
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return make_response((jsonify({"layout": current_app.data.layout(current_app.data.data)})), HTTPStatus.OK)
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@swagger.doc({
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"summary": "Observation layout for filtered subset.",
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"tags": ["layout"],
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"parameters": [
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{
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"name": "filter",
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"description": "Complex Filter",
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"in": "body",
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"schema": FilterModel
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}
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],
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"responses": {
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"200": {
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"description": "layout",
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"examples": {
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"application/json": {
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"layout": {
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"ndims": 2,
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"coordinates": [
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[0, 0.284483, 0.983744],
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[1, 0.038844, 0.739444]
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]
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}
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}
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}
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},
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"400": {
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"description": "Malformed filter"
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},
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"403": {
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"description": "Non-interactive request"
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},
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}
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})
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def post(self):
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try:
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df = current_app.data.filter_dataframe(request.get_json()["filter"])
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except KeyError:
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return make_response("Malformed filter", HTTPStatus.BAD_REQUEST)
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if len(df.obs.index) > current_app.data.features["layout"]["obs"]["interactiveLimit"]:
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return make_response("Non-interactive request", HTTPStatus.FORBIDDEN)
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return make_response((jsonify({"layout": current_app.data.layout(df)})), HTTPStatus.OK)
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class AnnotationsObsAPI(Resource):
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@swagger.doc({
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"summary": "Fetch annotations (metadata) for all observations.",
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@@ -367,112 +305,6 @@ class AnnotationsVarAPI(Resource):
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return make_response(jsonify(annotation_response), HTTPStatus.OK)
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class DiffExpObsAPI(Resource):
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@swagger.doc({
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"summary": "Generate differential expression (DE) statistics for two specified subsets of data, "
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"as indicated by the two provided observation complex filters",
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"tags": ["diffexp"],
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# TODO sort out params
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# "parameters": [
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# # {
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# # "in": "body",
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# # "name": "mode",
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# # "type": "string",
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# # "required": True,
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# # "description": "topN or varFilter"
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# # },
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# {
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# "in": "query",
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# "name": "count",
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# "type": "int32",
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# "description": "TopN mode: how many vars to return"
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# },
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# {
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# "in": "body",
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# "name": "varFilter",
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# "schema": FilterModel,
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# "description": "varFilter: Complex filter, only var for which vars to return"
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# },
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# {
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# "in": "body",
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# "name": "set1",
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# "schema": FilterModel,
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# "required": True,
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# "description": "Complex filter, only obs - observations in set1"
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# },
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# {
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# "in": "body",
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# "name": "set2",
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# "schema": FilterModel,
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# "description": "Complex filter, only obs - observations in set2. If not included, inverse of set1."
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# },
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# ],
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"responses": {
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"200": {
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"description": "Statistics are encoded as an array of arrays, with fields ordered as: "
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"varIndex, avgDiff, pVal, pValAdj, set1AvgExp, set2AvgExp",
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"examples": {
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"application/json": [
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[328, -2.569489, 2.655706e-63, 3.642036e-57, 383.393, 583.9],
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[1250, -2.569489, 2.655706e-63, 3.642036e-57, 383.393, 583.9],
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]
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}
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},
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"400": {
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"description": "malformed filter"
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},
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"403": {
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"description": "non-interactive request"
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},
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"501": {
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"description": "diffexp is not implemented"
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}
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}
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})
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def post(self):
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args = request.get_json()
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# confirm mode is present and legal
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try:
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mode = DiffExpMode(args["mode"])
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except KeyError:
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return make_response("Error: mode is required", HTTPStatus.BAD_REQUEST)
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except ValueError:
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return make_response(f"Error: invalid mode option {args['mode']}", HTTPStatus.BAD_REQUEST)
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# Validate filters
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if mode == DiffExpMode.VAR_FILTER:
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if "varFilter" not in args:
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return make_response("varFilter is required when mode is set to varFilter ", HTTPStatus.BAD_REQUEST)
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if Axis.OBS in args["varFilter"]["filter"]:
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return make_response("Obs filter not allowed in varFilter", HTTPStatus.BAD_REQUEST)
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if "set1" not in args:
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return make_response("set1 is required.", HTTPStatus.BAD_REQUEST)
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if Axis.VAR in args["set1"]["filter"]:
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return make_response("Var filter not allowed for set1", HTTPStatus.BAD_REQUEST)
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# set2
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if "set2" not in args:
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return make_response("Set2 as inverse of set1 is not implemented", HTTPStatus.NOT_IMPLEMENTED)
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if Axis.VAR in args["set2"]["filter"]:
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return make_response("Var filter not allowed for set2", HTTPStatus.BAD_REQUEST)
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set1_filter = args["set1"]["filter"]
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set2_filter = args.get("set2", {"filter": {}})["filter"]
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if "varFilter" in args:
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set1_filter[Axis.VAR] = args["varFilter"]["filter"][Axis.VAR]
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set2_filter[Axis.VAR] = args["varFilter"]["filter"][Axis.VAR]
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df1 = current_app.data.filter_dataframe(set1_filter, include_uns=False)
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# TODO inverse
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df2 = current_app.data.filter_dataframe(set2_filter, include_uns=False)
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# exceeds size limit
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if df1.shape[0] + df2.shape[0] > current_app.data.features["diffexp"]["interactiveLimit"]:
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return make_response("Non-interactive request", HTTPStatus.FORBIDDEN)
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# mode
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count = args.get("count", None)
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try:
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diffexp = current_app.data.diffexp(df1, df2, count)
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except ValueError as ve:
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return make_response(ve.message, HTTPStatus.BAD_REQUEST)
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return make_response(jsonify(diffexp), HTTPStatus.OK)
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class DataObsAPI(Resource):
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@swagger.doc({
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"summary": "Get data (expression values) from the dataframe.",
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@@ -682,15 +514,193 @@ class DataVarAPI(Resource):
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return make_response((jsonify(current_app.data.data_frame(df, axis=Axis.VAR))), HTTPStatus.OK)
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|
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|
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class DiffExpObsAPI(Resource):
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@swagger.doc({
|
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"summary": "Generate differential expression (DE) statistics for two specified subsets of data, "
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"as indicated by the two provided observation complex filters",
|
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"tags": ["diffexp"],
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# TODO sort out params
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# "parameters": [
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# # {
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# # "in": "body",
|
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# # "name": "mode",
|
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# # "type": "string",
|
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# # "required": True,
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# # "description": "topN or varFilter"
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# # },
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# {
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# "in": "query",
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# "name": "count",
|
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# "type": "int32",
|
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# "description": "TopN mode: how many vars to return"
|
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# },
|
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# {
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# "in": "body",
|
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# "name": "varFilter",
|
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# "schema": FilterModel,
|
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# "description": "varFilter: Complex filter, only var for which vars to return"
|
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# },
|
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# {
|
||||
# "in": "body",
|
||||
# "name": "set1",
|
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# "schema": FilterModel,
|
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# "required": True,
|
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# "description": "Complex filter, only obs - observations in set1"
|
||||
# },
|
||||
# {
|
||||
# "in": "body",
|
||||
# "name": "set2",
|
||||
# "schema": FilterModel,
|
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# "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"
|
||||
}
|
||||
}
|
||||
})
|
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def post(self):
|
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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
|
||||
|
||||
@@ -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, ...]
|
||||
"""
|
||||
# TODO Filtering cells is fine, but filtering genes does nothing because the neighbors are
|
||||
# calculated using the original vars (geneset) and this doesn’t get updated when you use less.
|
||||
# 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()
|
||||
:param axis: string obs or var
|
||||
:return: {
|
||||
"var": list of variable ids,
|
||||
"obs": [cellid, var1 expression, var2 expression, ...],
|
||||
}
|
||||
"""
|
||||
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: {
|
||||
"var": list of variable ids,
|
||||
"obs": [cellid, var1 expression, var2 expression, ...],
|
||||
}
|
||||
:return: [cellid, x, y, ...]
|
||||
"""
|
||||
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
|
||||
# TODO Filtering cells is fine, but filtering genes does nothing because the neighbors are
|
||||
# calculated using the original vars (geneset) and this doesn’t get updated when you use less.
|
||||
# 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()
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user