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📘 Formatting your Input Data

Preparing your Data​

Greetings, Cell Shape Researcher! 🧪 Before you embark on your analysis, it's crucial to ensure that your data is formatted correctly for our application.

📜 Format & Structure​

Your data should be presented in a text file with xy coordinates for each cell:

  • Each xy coordinate pair should be separated by a space.
  • Different cells should be distinguished with a line break.

Example:

x1 y1
x2 y2
x3 y3
...

x1 y1
x2 y2

Each pair denotes a point on the cell's boundary. The blank line signifies the start of a new cell's data.

🖥️ Data Parsing Procedure​

Our application utilizes a specialized function to process your data:

def parse_coordinates(file_path):
    # ... (function definition as you provided) ...

This function segregates the cells based on line breaks and delineates individual points using spaces.

Preparing Your Coordinate Data​

Welcome to the Cell Shape Analysis App! To ensure a smooth and efficient analysis, it's essential that your cell shape coordinate data is in the correct format. Let's delve into how you can achieve this.

📜 Desired Format & Structure​

Your data should be structured in the following manner:

  • Each xy coordinate pair should be separated by a space.
  • Different cells should be distinguished with a line break.

Example:

x1 y1
x2 y2
x3 y3
...

x1 y1
x2 y2

🖥️ Helper Functions to Convert Your Data​

If your data isn't already in this format, don't worry! Below are a few Python helper functions to assist you in converting your data:

  1. From List of Lists to Desired Format: If you have your data in a list of lists (where each list represents a cell's coordinates), use this function:
def from_lists_to_format(cells):
    formatted_data = ""
    for cell in cells:
        for coord in cell:
            formatted_data += f"{coord[0]} {coord[1]}\n"
        formatted_data += "\n"
    return formatted_data

Usage:

data = [
    [[1,2], [3,4], [5,6]],
    [[7,8], [9,10]]
]
formatted_data = from_lists_to_format(data)
print(formatted_data)
  1. From CSV to Desired Format: If your data is in a CSV format where each row represents a coordinate and each cell is separated by a new row, use this function:
import csv

def from_csv_to_format(csv_path):
    formatted_data = ""
    with open(csv_path, 'r') as file:
        reader = csv.reader(file)
        for row in reader:
            formatted_data += f"{row[0]} {row[1]}\n"
        formatted_data += "\n"
    return formatted_data

Usage:

formatted_data = from_csv_to_format("path_to_your_file.csv")
print(formatted_data)

Once you've transformed your data using one of the helper functions above, you can save the output to a text file or directly input it into our Cell Shape Analysis App.

🔍 Tip: Always double-check your formatted data to ensure there aren't any discrepancies. Proper data preparation is the foundation of accurate analysis. Happy Analyzing! 🎉

❗ Common Mistakes & Corrections​

  1. Missing Line Breaks: Ensure each cell's data is separated by a line break. This distinction is vital for accurate analysis.
  2. Incorrect Delimiters: Use a space to demarcate the x and y coordinates. Other delimiters will lead to parsing errors.
  3. Extraneous Data: Only include the xy coordinates in the file. Any additional data will be disregarded.

🚀 Ready to Proceed?​

With your data formatted correctly, you're poised to unlock insights into the world of cell shapes. Ensure adherence to the guidelines for optimal results.

🤓 Tip: Cells might be small, but their details are profound. Happy Analyzing! 🎉