Permalink
Cannot retrieve contributors at this time
Name already in use
A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?
Clustering-Ozone-EU-Data/Samples.py
Go to fileThis commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
112 lines (101 sloc)
3.06 KB
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
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() |