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https://developers.arcgis.com/geoanalytics/tools/gwr/ https://github.com/geeksnome/machine-learning-made-easy/blob/master/locally_weighted_regression.py
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08-30-2023
01:12 PM
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when is the Pro 3.2 expected to release? Can you provide some screenshots how will the tree look like?
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08-30-2023
01:02 PM
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What I wanted here is to have the marked classes appeared in the legend
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08-30-2023
12:58 PM
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I have little knowledge in coding. All what I wanted is a python code for the Geographically Weighted Regression (GWR) that can work in Jupyter or Spyder
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08-28-2023
10:28 PM
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I used the ChatGPT in order to get the python code for the GWR as per the request below --- Write a python code to read the table saved here: "C:\D\H3.xlsx" Write a python code to predict the value of the dependent variable based on the geographically Weighted Regression (GWR) displaying how the weights of neighbouring observations are used to calculate the prediction of the focal observation The first 4 columns are the independent variables The fifth column is the dependent variable The u column represents the x-coordinate The v column represents the y coordinate Use the Gaussian as the kernel function Assume the bandwidth to be 400 meters ------- The ChatGPT provided the code below: -------- import pandas as pd import numpy as np from spreg import GWR from spreg.utils import read_spatialdata # Load the data from the Excel file file_path = r'C:\D\H3.xlsx' data = pd.read_excel(file_path) # Define the independent variables (X1, X2, X3, X4) X = data[['X1', 'X2', 'X3', 'X4']].values # Define the dependent variable (y) y = data['y'].values # Define the coordinates (u and v) u = data['u'].values v = data['v'].values # Define the bandwidth for the Gaussian kernel bandwidth = 400 # meters # Create a spatial weights matrix based on Gaussian kernel distances = np.sqrt((u[:, np.newaxis] - u)**2 + (v[:, np.newaxis] - v)**2) kernel_weights = np.exp(-distances**2 / (2 * bandwidth**2)) # Create a GWR model model = GWR(y, X, kernel_weights) # Fit the GWR model results = model.fit() # Predict the values of the dependent variable predicted_values = results.predict(X) # You can now use predicted_values for your predictions print(predicted_values) ------- However, running this code on the JupyterLab ends up with an error as below
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08-22-2023
10:27 AM
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ArcGIS Pro 3.1.0: What is the python code based on which the weight of the surrounding (neighborhood) of each observation is calculated in the Geographically Weighted Regression (GWR)? As the only difference between the ordinary linear regression (ordinary least square – OLS) and the Geographically Weighted Regression (GWR) is that the observations in the GWR method are weighted based on their neighborhood and after being weighted, the predicted value for the focal observation is calculated based on the weighted observations but not raw observations. Then what is the python code that can show the weight of influence of each surrounding observation on the focal observation?
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08-22-2023
03:44 AM
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Not sure how can I can take the advantage of this python code to stick it in JupyterLab in order to apply the analysis
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08-22-2023
03:22 AM
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ArcGIS Pro 3.1.0: What is the python code for the Geographically Weighted Regression (GWR)? In the screenshot below, I couldn’t figure out how to obtain the python code for the Geographically Weighted Regression (GWR) by which the dependent variable (y) can be expected based on the independent variables (x1, x2, x3, x4) considering the location of each observations where u column represents the x – coordinate and v column represents the y – coordinate
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08-21-2023
11:44 AM
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ArcGIS Pro 3.1.0: What is the best practice to display the tree of a parcel lineage history particularly in case of parcels merge? For example, in the screenshots below, parcel#888 has the following transactions: it is divided into two parcels: 888/1 and 888/2 parcel 888/1 is divided into two parcels: 888/1/A and 888/1/B parcel 888/1/B is merged with 888/2 to form 888/1/B + 888/2 Now as the parcel 888/1/B + 888/2 is identified, it provides different history depending on where we click. What could be the best practice to display the tree of the history of parcel888/1/B + 888/2?
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08-21-2023
10:29 AM
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I thought that identifying a feature on the layer that represents the parcels should be able to display the tree of parcel lineage history.
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08-21-2023
09:24 AM
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ArcGIS Pro 3.1.0: What should the “identify” display in case of split\merge of fabric parcel? In the screenshots below, parcel # 333 has the following transactions: It is split into two parcels: 333/1 and 333/2 The 333/1 is then split into two parcels: 333/1/A and 333/1/B The 333/1/B is merged with 333/2 to form 333/1/B + 333/2 Then what identifying the 333/1/B + 333/2 should display? Do we need to turn on the “historic” layer so that the identify can display the history of the 333/1/B + 333/2? Or this could be managed by identifying only the Q layer?
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08-20-2023
04:23 AM
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ArcGIS Pro 3.1.0: How does the symbology of fabric layers change at particular zoom with no settings for inbound and outbound scales? In the screenshots below, I couldn’t figure out how the symbology of fabric layers changes at particular zoom with no settings for inbound and outbound scales
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08-18-2023
11:13 PM
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Thanks Christine I would appreciate if you could elaborate a little bit more in how to divide parcel#8 into two parcels: 8/1 and 8/2. Then I need to divide parcel # 8/1 into two: 8/1/A and 8/1/B Is it necessary to perform “set active record” option for the parcel that is required to be split?
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08-18-2023
11:54 AM
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ArcGIS Pro 3.1.0: How to update the records layer after editing the parcel layer while working with the fabric? In the screenshot below, parcel#28 is split into two parcels: 28/1 and 28/2. Then how the 28/1 can be further split to 28/1/1 and 28/1/2.
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08-18-2023
04:22 AM
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