import gradio as gr import pandas as pd import numpy as np import json from io import StringIO from collections import OrderedDict import os # ---------------------- Accessing data from Notion ---------------------- # from notion_client import Client as client_notion from imports_utils import fetch_all_database_pages from imports_utils import get_property_value from imports_utils import getDataFromNotion from imports_utils import notionToken from config import useNotionData from config import landuseDatabaseId , subdomainAttributesDatabaseId from config import landuseColumnName from config import subdomainColumnName from config import sqmPerEmployeeColumnName from config import thresholdsColumnName from config import maxPointsColumnName from config import domainColumnName if notionToken is None: raise Exception("Notion token not found. Please check the environment variables.") else: print("Notion token found successfully!") if useNotionData: notion = client_notion(auth=notionToken) lu_mapperDict, subdomain_mapperDict = getDataFromNotion( notion=notion, notionToken=notionToken, landuseDatabaseID=landuseDatabaseId, subdomainDatabaseID=subdomainAttributesDatabaseId ) # ---------------------- Accessing data from Speckle ---------------------- # from specklepy.api.client import SpeckleClient from specklepy.api.credentials import get_default_account, get_local_accounts from specklepy.transports.server import ServerTransport from specklepy.api import operations from specklepy.objects.geometry import Polyline, Point from specklepy.objects import Base import speckle_utils import data_utils from config import landuseDatabaseId , streamId, dmBranchName, dmCommitId, luBranchName, luCommitId, distanceMatrixActivityNodes from imports_utils import speckleToken from config import useSpeckleData from imports_utils import getDataFromSpeckle if speckleToken is None: raise Exception("Speckle token not found") else: print("Speckle token found successfully!") if useSpeckleData == True: CLIENT = SpeckleClient(host="https://speckle.xyz/") account = get_default_account() CLIENT.authenticate_with_token(token=speckleToken) landuses, matrices = getDataFromSpeckle(speckleClient = CLIENT, streamID=streamId,matrixBranchName=dmBranchName, landuseBranchName=luBranchName) df_dm = matrices[distanceMatrixActivityNodes] df_dm_dict = df_dm.to_dict('index') df_dm = df_dm.replace([np.inf, -np.inf], 10000).fillna(0) df_dm = df_dm.apply(pd.to_numeric, errors='coerce') df_dm = df_dm.round(0).astype(int) mask_connected = df_dm.index.tolist() df_lu = landuses.loc[mask_connected] mergeAssetNonAssetLanduse = True if mergeAssetNonAssetLanduse: df_lu.columns = [col.replace('ASSETS+', '') for col in df_lu.columns] df_lu = df_lu.replace([np.inf, -np.inf], 10000).fillna(0) df_lu = df_lu.apply(pd.to_numeric, errors='coerce') df_lu = df_lu.astype(int) df_lu = df_lu.T.groupby(level=0).sum().T def test(input_json): print("Received input") # Parse the input JSON string try: inputs = json.loads(input_json) except json.JSONDecodeError: inputs = json.loads(input_json.replace("'", '"')) # ------------------------- Accessing input data from Grasshopper ------------------------- # from imports_utils import getDataFromGrasshopper from config import alpha as alphaDefault from config import threshold as thresholdDefault from imports_utils import findUniqueDomains from imports_utils import findUniqueSubdomains from imports_utils import landusesToSubdomains from imports_utils import FindWorkplacesNumber from imports_utils import computeAccessibility from imports_utils import computeAccessibility_pointOfInterest from imports_utils import remap from imports_utils import accessibilityToLivability useGrasshopperData = inputs['input']["useGrasshopperData"] # fetch grasshoper data or not if useGrasshopperData == "True": dfMatrix_gh, dfLanduses_gh, attributeMapperDict_gh, landuseMapperDict_gh, alpha, threshold = getDataFromGrasshopper( inputJson = inputs, inputNameMatrix = "matrix", inputNameLanduse = "landuse_areas", inputNameAttributeMapper = "attributeMapperDict", inputNameLanduseMapper = "landuseMapperDict", inputNameAlpha = "alpha", inputNameThreshold = "threshold" ) dfMatrix = dfMatrix_gh dfLanduses = dfLanduses_gh if useNotionData != True: attributeMapperDict = attributeMapperDict_gh landuseMapperDict = landuseMapperDict_gh else: dfMatrix_gh, dfLanduses_gh, attributeMapperDict_gh, landuseMapperDict_gh, alpha, threshold = getDataFromGrasshopper( inputJson = inputs, inputNameMatrix = None, inputNameLanduse = None, inputNameAttributeMapper = None, inputNameLanduseMapper = None, inputNameAlpha = "alpha", inputNameThreshold = "threshold" ) dfLanduses = df_lu.copy() dfMatrix = df_dm.copy() landuseMapperDict = lu_mapperDict livabilityMapperDict = subdomain_mapperDict domainsUnique = findUniqueDomains(livabilityMapperDict) subdomainsUnique = findUniqueSubdomains(landuseMapperDict) LivabilitySubdomainsWeights = landusesToSubdomains(dfMatrix,dfLanduses,landuseMapperDict,subdomainsUnique) WorkplacesNumber = FindWorkplacesNumber(dfMatrix,livabilityMapperDict,LivabilitySubdomainsWeights,subdomainsUnique) # prepare an input weights dataframe for the parameter LivabilitySubdomainsInputs LivabilitySubdomainsInputs =pd.concat([LivabilitySubdomainsWeights, WorkplacesNumber], axis=1) subdomainsAccessibility = computeAccessibility(dfMatrix,LivabilitySubdomainsInputs,alpha,threshold) livability = accessibilityToLivability(dfMatrix,subdomainsAccessibility,livabilityMapperDict,domainsUnique) livability_dictionary = livability.to_dict('index') LivabilitySubdomainsInputs_dictionary = LivabilitySubdomainsInputs.to_dict('index') subdomainsAccessibility_dictionary = subdomainsAccessibility.to_dict('index') LivabilitySubdomainsWeights_dictionary = LivabilitySubdomainsWeights.to_dict('index') df_lu_dict = dfLanduses.to_dict('index') dm_dictionary = dfMatrix.to_dict('index') # Prepare the output output = { "subdomainsAccessibility_dictionary": subdomainsAccessibility_dictionary, "livability_dictionary": livability_dictionary, "subdomainsWeights_dictionary": LivabilitySubdomainsInputs_dictionary, "luDomainMapper": landuseMapperDict, "attributeMapper": livabilityMapperDict, "mask_connected": mask_connected, "dm_an": dm_dictionary, "landuses":df_lu_dict, "constants": [alpha, threshold] } return json.dumps(output) # Define the Gradio interface with a single JSON input iface = gr.Interface( fn=test, inputs=gr.Textbox(label="Input JSON", lines=20, placeholder="Enter JSON with all parameters here..."), outputs=gr.JSON(label="Output JSON"), title="testspace" ) iface.launch()