In [42]:

    

import predict_rainfall as rain
import load_rainfall as load
import numpy as np
import plotly.plotly as py
import plotly.graph_objs as go
from plotly.offline import init_notebook_mode, plot, iplot


    

In [43]:

    

init_notebook_mode(connected=True)


    

In [163]:

    

X14, y = load.load_training_data(t=14, height_span=[0, 1], downsample_size=2, image_size=21)
X13, y = load.load_training_data(t=13, height_span=[0, 1], downsample_size=2, image_size=21)
X12, y = load.load_training_data(t=12, height_span=[0, 1], downsample_size=2, image_size=21)
X1, y = load.load_training_data(t=1, height_span=[0, 1], downsample_size=2, image_size=21)


    

    




loading training data... t: 14, h: [0, 1], img_size: 21, downsample: 2, limit: 10000
find cached raw data!
change channels to last
loading training data... t: 13, h: [0, 1], img_size: 21, downsample: 2, limit: 10000
find cached raw data!
change channels to last
loading training data... t: 12, h: [0, 1], img_size: 21, downsample: 2, limit: 10000
find cached raw data!
change channels to last
loading training data... t: 1, h: [0, 1], img_size: 21, downsample: 2, limit: 10000
find cached raw data!
change channels to last

In [162]:

    

sorted_idx = np.argsort(y, axis=0)
for X in [X14, X12, X1]:
    rank = 8001
    print(y[sorted_idx[rank]])
    z = X[sorted_idx[rank, 0], :, :, 0]
    trace = go.Heatmap(z=z)
    data = [trace]
    iplot(data, filename='radar heat map')


    

    




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In [193]:

    

low_thres = 20
high_thres = 80


X14_high = np.count_nonzero(X14[:,:,:,0] > high_thres, axis=(1,2))
X13_high = np.count_nonzero(X13[:,:,:,0] > high_thres, axis=(1,2))
X12_high = np.count_nonzero(X12[:,:,:,0] > high_thres, axis=(1,2))
X1_high = np.count_nonzero(X1[:,:,:,0] > high_thres, axis=(1,2))

X14_low = np.count_nonzero(X14[:,:,:,0] < low_thres, axis=(1,2))
X13_low = np.count_nonzero(X13[:,:,:,0] < low_thres, axis=(1,2))
X12_low = np.count_nonzero(X13[:,:,:,0] < low_thres, axis=(1,2))
X1_low = np.count_nonzero(X1[:,:,:,0] < low_thres, axis=(1,2))

diff_X_high = X14_high - X12_high
diff_X_low = X14_low - X12_low

y_flatten = y.flatten()

print(diff_X_high)
print(diff_X_low)

print(y_flatten)

trace = go.Scatter(x = diff_X_high, y = y_flatten, mode = 'markers')
data = [trace]
iplot(data, filename='diff vs y')


    

    




[ -1  -3  45 ..., -15 -67 -23]
[  0  -2   0 ...,  -1 -19  -3]
[ 2.3  2.1  2.8 ...,  1.2  1.   0.8]