import numpy as np
import matplotlib.pyplot as plt

data = np.genfromtxt('small_dataset.csv', delimiter=',',usecols=(0,1,2),names=['y','x','z'])

plt.xlabel('Longitude')
plt.ylabel('Latitude')

x = data['x']
y = data['y']
z = data['z']

column_num=29
row_num=110

# Check if area has minimum allowed standard deviation
def valid_cell(cell):
    
    return False

# Iterate through all the data points and return the filtered data set
def make_filtered_set():
    result = [[]]
    for i in range(row_num):
        for g in range(column_num):
            cells(i,g) = small_dataset(small_dataset(:,1)>min_y + ((i-1)*diff_y) & small_dataset(:,1)<min_y + i*diff_y & small_dataset(:,2)>min_x + ((g-1)*diff_x) & small_dataset(:,2)>min_x + g*diff_x,1:3 );
    return result

yolo = make_filtered_set()

plt.scatter(x,y,c=z, alpha=0.5)
plt.colorbar(label='RSS [dBm]')
plt.show()
#plt.savefig('small_dataset_reduced.png', format='png')