def main():
mnist = Mnist(os.path.join(os.getcwd(), "datasets/train.csv"), rows=100)
for dataset in mnist.random()[:1]:
# reshape from 1x784 to 28x28 and scale to 0-1
array = numpy.asfarray(dataset.data).reshape((28, 28)) / 255
fig, ax = plt.subplots()
im = ax.imshow(array, cmap=plt.get_cmap('Greys'), interpolation='None')
fig.colorbar(im)
ax.set_title(dataset.label)
plt.show()
class TestMnist(unittest.TestCase):
""" Tests ... """
def setUp(self):
self._mnist = Mnist(
os.path.join(os.path.dirname(__file__), 'resources/mnist.csv'))
def tearDown(self):
pass
def test_load_data(self):
"""
Test case for ...
"""
assert len(self._mnist.get()) == 10
assert self._mnist.get()[0].label == 7
pass
def test_rand(self):
"""
Test case for ...
"""
assert len(self._mnist.random()[:5]) == 5
pass