def test_particular_plot(n_steps=3):
for i in xrange(n_steps):
r = np.random.randn(1)
dbplot(r,
plot_type=lambda: HistogramPlot(edges=np.linspace(-5, 5, 20)))
clear_dbplot()
def test_same_object():
"""
There was a bug where when you plotted two of the same array, you got "already seen object". This tests makes
sure it's gotten rid of. If it's gone, both matrices should plot. Otherwise you'll get "Already seen object" showing
up on one of the plots.
"""
a = np.random.randn(20, 20)
for _ in xrange(5):
dbplot(a, 'a')
dbplot(a, 'b')
clear_dbplot()
def test_dbplot(n_steps=3):
arr = np.random.rand(10, 10)
for i in xrange(n_steps):
arr_sq = arr**2
arr = arr_sq / np.mean(arr_sq)
dbplot(arr, 'arr')
for j in xrange(3):
barr = np.random.randn(10, 2)
dbplot(barr, 'barr', plot_type=lambda: LinePlot())
clear_dbplot()
def test_history_plot_updating():
"""
This test checks that we've fixed the bug mentioned in issue 1: https://github.com/QUVA-Lab/artemis/issues/1
That was, when you are updating multiple plots with history in a loop, everytime any of the plots is updated, they
all get updated with the most recent data. You'll see this in plot 'c' - with the bug, it moves in steps, with 3
of the same sample in a row. If it works it should be spikey.
"""
for i in xrange(10):
dbplot(np.random.randn(20, 20), 'a')
dbplot(np.random.randn(20, 20), 'b')
dbplot(np.random.randn(), 'c', plot_type=lambda: MovingPointPlot())
clear_dbplot()
def test_dbplot_logscale(n_steps=3):
arr = np.random.rand(10, 10)
for i in xrange(n_steps):
arr_sq = arr**2
arr = arr_sq / np.mean(arr_sq)
dbplot(arr, 'arr')
for j in xrange(3):
barr = np.random.randn(10, 2)
kw = {"y_axis_type": "log"}
dbplot(barr, 'barr', plot_type=lambda: LinePlot(y_axis_type='log'))
clear_dbplot()
def test_demo_dbplot():
demo_dbplot(n_frames=3)
clear_dbplot()
def test_demo_dbplot():
demo_dbplot(n_frames=3)
clear_dbplot()