Samples.py

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

'''
#Below functions chooses a random data point from any of the models.
def randomPointOld(modelList):
    m = np.random.randint(0, 7)
    la = np.random.randint(0, 400)
    lo = np.random.randint(0, 700)
    return m, la, lo


def displaySample25Old(modelList, lat, lon):
    fig = plt.figure(figsize=(10, 10))
    #number of hours (should be 25)
    for h in range(25):
        #First and second parameters determine inverse size of each sub-plot. 5, 5 means a 5th of the width and 5th of the hieght per subplot.
        ax = fig.add_subplot(5, 5, h + 1, projection='3d')
        #should be len(lat) or 400
        for i in range(5):
            #should be len(lon) or 700
            for j in range(5):
                m, la, lo = randomPointOld(modelList)
                zs = modelList[m][h][la][lo]
                xs = lat[la]
                ys = lon[lo]
                ax.scatter(xs, ys, zs)

        ax.set_xlabel('Latitude')
        ax.set_ylabel('Longitude')
        ax.set_zlabel('Ozone-Level')
    plt.show()


def displaySample1Old(modelList, lat, lon):
    fig = plt.figure(figsize=(10, 10))
    ax = fig.add_subplot(projection='3d')
    # should be len(lat) or 400
    for i in range(20):
        # should be len(lon) or 700
        for j in range(20):
            m, la, lo = randomPointOld(modelList)
            zs = modelList[m][0][la][lo]
            xs = lat[la]
            ys = lon[lo]
            ax.scatter(xs, ys, zs)

    ax.set_xlabel('Latitude')
    ax.set_ylabel('Longitude')
    ax.set_zlabel('Ozone-Level')
    plt.show()
'''


def displaySample1(CBEOne, centroids):
    #decides the colour associated with each cluster/centroid
    colours = {
        0: 'r',
        1: 'b',
        2: 'g',
        3: 'c',
        4: 'm',
        5: 'y'
    }
    fig = plt.figure(figsize=(10, 10))
    ax = fig.add_subplot(projection='3d')
    for i in CBEOne:
        lat = i.lat
        lon = i.lon
        ozone = i.ozone
        print(i.centroid)
        ax.scatter(lat, lon, ozone, c=colours[i.centroid])
    for i in centroids:
        lat = i.lat
        lon = i.lon
        ozone = i.ozone
        ax.scatter(lat, lon, ozone, c='k')
    ax.set_xlabel('Latitude')
    ax.set_ylabel('Longitude')
    ax.set_zlabel('Ozone-Level')
    plt.show()


def displaySample25(kEnsemble, kEntroids):
    colours = {
        0: 'r',
        1: 'b',
        2: 'g',
        3: 'c',
        4: 'm',
        5: 'y'
    }
    fig = plt.figure(figsize=(10, 10))
    for h in range(25):
        ax = fig.add_subplot(5, 5, h + 1, projection='3d')
        for i in kEnsemble[h]:
            lat = i.lat
            lon = i.lon
            ozone = i.ozone
            #print(i.centroid)
            ax.scatter(lat, lon, ozone, c=colours[i.centroid])
        for i in kEntroids[h]:
            lat = i.lat
            lon = i.lon
            ozone = i.ozone
            ax.scatter(lat, lon, ozone, c='k')
    ax.set_xlabel('Latitude')
    ax.set_ylabel('Longitude')
    ax.set_zlabel('Ozone-Level')
    plt.show()