try:
    import cdk
    print("CDK already installed, skipping installation and restart.")
except ImportError:
    !pip install nucleus-cdk==0.6.3 -q > /dev/null 2>&1
    print("\nInstallation complete. Restarting runtime to refresh dependencies...")
    import os
    os._exit(0)

import pandas as pd
pd.set_option('display.max_columns', None)
import seaborn as sns
import matplotlib.pyplot as plt

# Import the cdk platereader module
from cdk.instruments import platereader as pr

from cdk import logging
log = logging.setup_logging(logging.ERROR)

%%writefile drive_utils.py
import os
import re

import gdown


def get_drive_file_id(url):
    """Extract the file ID from a Google Drive share URL."""
    match = re.search(r'/d/([a-zA-Z0-9_-]+)', url)
    if match:
        return match.group(1)
    return None


def download_from_drive(files_info, destination_dir):
    """
    Download files from Google Drive.

    Args:
        files_info (list): List of dicts with 'url' and 'filename'.
        destination_dir (str): Local path to save files.
    Returns:
        dict: Mapping of filenames to local paths.
    """
    os.makedirs(destination_dir, exist_ok=True)

    paths = {}
    for item in files_info:
        url = item['url']
        filename = item['filename']
        dest = os.path.join(destination_dir, filename)
        file_id = get_drive_file_id(url)

        if file_id:
            gdown.download(id=file_id, output=dest, quiet=True)
        else:
            gdown.download(url, output=dest, quiet=True)

        paths[filename] = dest
    return paths

# Set use_drive = True to download data_file and platemap_file from Google Drive instead of
# using local files. Each Drive file must have its permissions set to "Anyone with a link" can "view".
use_drive = True

if use_drive:
    from drive_utils import download_from_drive

    files_to_download = [
        {
            "url": "https://drive.google.com/file/d/1fCIDnSCbRrsiI3w89619i9TKXkkA6Sl-/view?usp=sharing",  # Replace with your data file link.
            "filename": "raw_data.txt",
        },
        {
            "url": "https://drive.google.com/file/d/1t8r2atuNZQvChwyfSsm0ic4uygJrlXHF/view?usp=sharing",  # Replace with your platemap file link.
            "filename": "platemap.csv",
        },
    ]
    downloaded_paths = download_from_drive(files_to_download, destination_dir="data")
    data_file = downloaded_paths["raw_data.txt"]
    platemap_file = downloaded_paths["platemap.csv"]
else:
    data_file = "sample-data/20251111-122213-cytation5-pure-timecourse-gfp-MFG-98-tRNA-QC.txt"
    platemap_file = "sample-data/platemap.csv"

print(f"Data file: {data_file}\nPlatemap file: {platemap_file}")

# Load data
result = pr.load_platereader_data(
    data_file=data_file,
    platemap_file=platemap_file,
    platereader="biotek" # options: "biotek"
)

print(result)

desired_index = 1
data = result[desired_index]

data.view().head()

data.plot(style='Type')

# To check the exact name of your standard
platemap = data.platemap
standards = platemap[platemap['Type']=='Standard']
standards['Name'].unique()

data = data.normalize('10 uM HPTS')

g = data.plot(style='Type', exclude_types=['Standard'])
# g.savefig('after-normalization.png',dpi=300)

# data = data.normalize('10 uM HPTS', window=pd.Timedelta("2.5h"))

# Perform kinetic analysis using sigmoid_drift model
kinetics = data.fit_kinetics()

kinetics.summary

g = kinetics.plot(col="Well")
# g = kinetics.plot() # call this to visualize across replicates

g = kinetics.plot_summary()