140 lines
4.8 KiB
Python
140 lines
4.8 KiB
Python
from flask import Flask, render_template, request, redirect, url_for
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import sqlite3
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib
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import io
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import base64
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from datetime import datetime, timedelta
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import os
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app = Flask(__name__)
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# Pharmacokinetics parameters (in minutes)
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# ln(2) / (Half-life-in-minutes)
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CAFFEINE_ABSORPTION_RATE = 0.05 # per minute (half-life ~15 min)
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CAFFEINE_ELIMINATION_RATE = 0.0023 # per minute (half-life ~5 hours)
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AMPHETAMINE_ABSORPTION_RATE = 0.03 # per minute (half-life ~20 min)
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AMPHETAMINE_ELIMINATION_RATE = 0.0013 # per minute (half-life ~9 hours)
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# Initialize database
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def init_db():
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conn = sqlite3.connect('stimulants.db')
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c = conn.cursor()
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c.execute('''CREATE TABLE IF NOT EXISTS doses
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(id INTEGER PRIMARY KEY AUTOINCREMENT,
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timestamp DATETIME,
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type TEXT,
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amount INTEGER)''')
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conn.commit()
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conn.close()
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# Calculate stimulant amount at given time
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def calculate_amount(doses, time, k_abs, k_elim):
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total = 0
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for dose in doses:
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dose_time = datetime.strptime(dose[0], '%Y-%m-%d %H:%M:%S')
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t = (time - dose_time).total_seconds() / 60 # convert to minutes
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if t >= 0:
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# One-compartment model with first-order absorption
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total += dose[1] * (k_abs / (k_abs - k_elim)) * (
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np.exp(-k_elim * t) - np.exp(-k_abs * t)
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)
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return total
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# Generate graph for past 24 hours
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def generate_graph():
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# Get current time and 24 hours ago
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now = datetime.now()
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start_time = now - timedelta(hours=24)
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# Create time points (every 10 minutes)
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times = [start_time + timedelta(minutes=i*10) for i in range(144)]
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# Get all doses from database
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conn = sqlite3.connect('stimulants.db')
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c = conn.cursor()
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c.execute("SELECT timestamp, amount FROM doses WHERE type='caffeine'")
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caffeine_doses = c.fetchall()
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c.execute("SELECT timestamp, amount FROM doses WHERE type='amphetamine'")
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amphetamine_doses = c.fetchall()
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conn.close()
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# Calculate amounts for each time point
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caffeine_levels = [calculate_amount(caffeine_doses, t,
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CAFFEINE_ABSORPTION_RATE,
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CAFFEINE_ELIMINATION_RATE) for t in times]
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amphetamine_levels = [calculate_amount(amphetamine_doses, t,
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AMPHETAMINE_ABSORPTION_RATE,
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AMPHETAMINE_ELIMINATION_RATE) for t in times]
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# Create plot
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plt.figure(figsize=(12, 6))
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plt.plot(times, caffeine_levels, 'b-', label='Caffeine (mg)')
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plt.plot(times, amphetamine_levels, 'r-', label='Amphetamine (mg)')
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plt.xlabel('Time')
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plt.ylabel('Estimated Amount (mg)')
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plt.title('Stimulant Levels in Body (Past 24 Hours)')
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plt.legend()
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plt.grid(True)
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# Format x-axis
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ax = plt.gca()
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ax.xaxis.set_major_locator(matplotlib.dates.HourLocator(interval=4))
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ax.xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%H:%M'))
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# Convert to base64 string
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img = io.BytesIO()
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plt.savefig(img, format='png')
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img.seek(0)
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graph_url = base64.b64encode(img.getvalue()).decode()
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plt.close()
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return graph_url
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@app.route('/')
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def index():
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# Calculate current amounts
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now = datetime.now()
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conn = sqlite3.connect('stimulants.db')
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c = conn.cursor()
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c.execute("SELECT timestamp, amount FROM doses WHERE type='caffeine'")
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caffeine_doses = c.fetchall()
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c.execute("SELECT timestamp, amount FROM doses WHERE type='amphetamine'")
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amphetamine_doses = c.fetchall()
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conn.close()
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caffeine_amount = calculate_amount(caffeine_doses, now,
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CAFFEINE_ABSORPTION_RATE,
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CAFFEINE_ELIMINATION_RATE)
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amphetamine_amount = calculate_amount(amphetamine_doses, now,
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AMPHETAMINE_ABSORPTION_RATE,
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AMPHETAMINE_ELIMINATION_RATE)
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# Generate graph
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graph_url = generate_graph()
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return render_template('index.html',
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caffeine_amount=round(caffeine_amount, 2),
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amphetamine_amount=round(amphetamine_amount, 2),
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graph_url=graph_url)
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@app.route('/add_dose', methods=['POST'])
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def add_dose():
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stim_type = request.form['type']
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amount = 10 # Fixed 10mg amount
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timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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conn = sqlite3.connect('stimulants.db')
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c = conn.cursor()
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c.execute("INSERT INTO doses (timestamp, type, amount) VALUES (?, ?, ?)",
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(timestamp, stim_type, amount))
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conn.commit()
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conn.close()
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return redirect(url_for('index'))
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if __name__ == '__main__':
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init_db()
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app.run(debug=True)
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