Functional Requirements

1. Load a csv file through file browser Download Sample File
2. Delimiter can be either space or a single comma
3. The csv file contains 2D matrix of numbers(with column structure as |x-coord, y-coord, value|)
4. Display the content in a text box or table.
5. Replace bad zero values by interpolating with spatial neighbours
6. Write the result in another text box or table.

Technical Requirements

1. HTML5 File browser with limiting only to single csv file
2. Parse csv file to collect metrics(file size, delimiter and header row) and records
3. Javascript to render table
4. Javascript business logic to replace the zero values by spatial interpolation technique called Inverse Distance Weighting(IDW) method from https://gisgeography.com/inverse-distance-weighting-idw-interpolation/

Workflow in steps

1. Parse the csv data
2. Print delimiter
3. Print has header row
4. Print file size
5. Print total number of records count
6. Print input records table
7. Filter the bad records when the value field is zero
8. Print number of bad recods count
9. Print bad recods table
10. Filter valid records by removing bad records
11. Find the two closest valid points to the bad records
12. Calculate the interpolated values using IDW math for bad records based on the two closest points
13. Update the interpolated values into the original records
14. Print the final interpolated recods

Limitations

1. Single formatted error message will be displayed when a file is uploaded with any of the following - duplicate data set; missing coordinates; invalid data such as alphabets and special characters
2. File holding records inclusive of empty lines will still be processed as the code will automatically ignore the empty lines and process rest of the dataset
3. While uploading the same file subsequently, please press the reset button and then upload the file
4. File containing records with both Space and Comma as delimiters cannot be uploaded