In [4]:
%matplotlib inline
from __future__ import division, print_function
import numpy as np
import matplotlib.pyplot as plt
import SHS_data
import evaluation
import util
In [2]:
cliques_by_name, cliques_by_uri = SHS_data.read_cliques()
In [5]:
ratio = (1, 9, 90)
train_cliques, test_cliques, val_cliques = util.split_train_test_validation(cliques_by_name, ratio=ratio)
In [9]:
train_uris = util.uris_from_clique_dict(train_cliques)
test_chroma = SHS_data.read_chroma(train_uris[0])
In [12]:
delta_chroma = np.diff(test_chroma, axis=0)
In [14]:
test_chroma.shape, delta_chroma.shape
Out[14]:
In [23]:
fake_chroma = np.zeros((15,12))
fake_chroma[0,0] = 1
plt.imshow(fake_chroma, interpolation='nearest', cmap='viridis')
Out[23]:
In [25]:
plt.imshow(np.roll(fake_chroma, 1, axis=1), interpolation='nearest', cmap='viridis')
Out[25]:
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