import numpy as np
import matplotlib.pyplot as plt
import yfinance as yf
from datetime import date, timedelta

samsung = yf.download('005930.KS', start=date.today()-timedelta(10*365))
y = samsung['Adj Close'].values

plt.figure(figsize=(10,6), dpi=100)
plt.plot(samsung.index, y)
plt.grid(True)
plt.xlabel('Date')
plt.ylabel('Adjusted close price')
plt.title('Samsung Electronics Co., Ltd. (005930.KS)')
plt.show()

N = len(y)

window = [7, 30, 90, 180]

k = len(window)

x = np.zeros((k,N))

for i in range(k):
  n = window[i]
  for j in range(N):
    start = max(0,j-n+1)
    data = y[start:j+1]
    n_data = len(data)
    #print(start, j, n_data, data)
    x[i,j] = np.sum(data)/n_data

plt.figure(figsize=(10,6), dpi=100)
plt.plot(y, alpha=0.4, label='Samsung Electronics')
for i in range(k):
  plt.plot(x[i,:], label=f'Moving average with n={window[i]}')
plt.grid()
plt.xlabel('Date')
plt.ylabel('Adjusted close price')
plt.title('Samsung Electronics Co., Ltd. (005930.KS)')
plt.legend()
plt.show()

import numpy as np
import matplotlib.pyplot as plt

# Generate some sample gravity data
num_points = 50
np.random.seed(3001)
x = np.random.rand(num_points)
y = np.random.rand(num_points)
gravity_values = np.sin(2*np.pi*x) + np.cos(2*np.pi*y) \
  + np.random.randn(num_points)*0.1

# Plot the results
plt.figure(figsize=(8, 6), dpi=100)
plt.scatter(x, y, c=gravity_values, label='Gravity Measurements')
plt.colorbar(label='Gravity Anomaly')
plt.xlabel('X')
plt.ylabel('Y')
plt.title('Gravity Anomaly Interpolation using IDW')
plt.legend()
plt.grid()
plt.show()

# Define the interpolation grid
grid_x, grid_y = np.mgrid[0:1:100j, 0:1:100j]

# Perform IDW interpolation
interpolated_gravity = np.zeros_like(grid_x)
for i in range(grid_x.shape[0]):
    for j in range(grid_x.shape[1]):
        distances = np.sqrt((grid_x[i, j] - x)**2 + (grid_y[i, j] - y)**2)
        weights = 1 / distances**2  # Inverse distance squared weighting
        interpolated_gravity[i, j] = np.sum(gravity_values * weights) / np.sum(weights)
        #interpolated_gravity[i, j] = np.sin(2*np.pi*grid_x[i,j]) + np.cos(2*np.pi*grid_y[i,j])

# Plot the results
plt.figure(figsize=(8, 6), dpi=100)
plt.scatter(x, y, c=gravity_values, label='Gravity Measurements')
plt.contourf(grid_x, grid_y, interpolated_gravity, alpha=0.7)
plt.colorbar(label='Gravity Anomaly')
plt.xlabel('X')
plt.ylabel('Y')
plt.title('Gravity Anomaly Interpolation using IDW')
plt.legend()
plt.grid()
plt.show()