def test_statsplot_info_binned(diskcaching):
"test the view"
fov, mdl = _Fig.create(withhp=True)
mdl.tasks.jobs.launch(list(mdl.tasks.processors.values()))
mdl.theme.__dict__.update(xinfo=[AxisConfig("binnedz")], yaxis="distance")
cache = dict(_HairpinPlot(fov, mdl.tasks.processors)._reset())
_check_validity(cache, "Δ(closest binding - blockage) (bp)")
vals = [float(i[0]) for i in cache['x_range']['factors']]
assert_allclose(vals, np.round(vals, 2))
assert_allclose(np.diff(vals), np.round(np.diff(vals), 1))
assert .001 <= vals[0] <= .1
mdl.theme.__dict__.update(xinfo=[AxisConfig("binnedbp")], yaxis="distance")
cache = dict(_HairpinPlot(fov, mdl.tasks.processors)._reset())
_check_validity(cache, "Δ(closest binding - blockage) (bp)")
assert all(i[0].endswith(".0") for i in cache['x_range']['factors'])
vals = [float(i[0]) for i in cache['x_range']['factors']]
assert_allclose(vals, np.round(vals))
assert_allclose(np.diff(vals), np.round(np.diff(vals)))
assert 20 <= vals[0] <= 50
fov._fig.__dict__['x_range'] = Range1d()
mdl.theme.linear = True
cache = dict(_HairpinPlot(fov, mdl.tasks.processors)._reset())
assert fov._fig.x_range in cache
assert 'start' in cache[fov._fig.x_range]
assert cache[_Fig.renderers[0].glyph]['width'] == 5.
def test_statsplot_info_reftrack(diskcaching):
"test the view"
fov, mdl = _Fig.create(beads=list(range(5)), withhp=True)
_Fig.newtasks(mdl, beads=list(range(5, 10)), withhp=True)
mdl.tasks.jobs.launch(list(mdl.tasks.processors.values()))
mdl.theme.xinfo = [AxisConfig('track')]
mdl.theme.yaxis = 'hybridisationrate'
cache = dict(_HairpinPlot(fov, mdl.tasks.processors)._reset())
data = cache['_stats']['data']
assert list(data['x']) == [('track 0', '', ''), ('track 1', '', '')]
mdl.display.reference = next(iter(mdl.tasks.roots))
cache = dict(_HairpinPlot(fov, mdl.tasks.processors)._reset())
data2 = cache['_stats']['data']
assert np.isnan(data2['boxcenter']) == 1
assert len(data2['boxcenter']) == 1
assert list(data2['x']) == [('', '', '')]
fov, mdl = _Fig.create(beads=list(range(5)), withhp=True)
_Fig.newtasks(mdl, beads=list(range(1, 6)), withhp=True)
mdl.tasks.jobs.launch(list(mdl.tasks.processors.values()))
mdl.theme.yaxis = 'hybridisationrate'
cache = dict(_HairpinPlot(fov, mdl.tasks.processors)._reset())
data = cache['_stats']['data']
assert list(data['x']) == [('track 0', '', ''), ('track 1', '', '')]
beads = BeadsScatterPlotModel()
wdg1 = PeakcallingPlotModel(beads, mdl)
assert wdg1.reftrack == 0
mdl.display.reference = next(iter(mdl.tasks.roots))
wdg2 = PeakcallingPlotModel(beads, mdl)
assert wdg2.reftrack == 1
assert wdg2.diff(PeakcallingPlotModel(beads, mdl), mdl) == dict(theme={},
display={})
assert wdg2.diff(wdg1, mdl) == dict(theme={}, display=dict(reference=None))
assert wdg1.diff(wdg2, mdl) == dict(
theme={}, display=dict(reference=next(iter(mdl.tasks.roots))))
cache = dict(_HairpinPlot(fov, mdl.tasks.processors)._reset())
data2 = cache['_stats']['data']
assert_allclose(data2['boxcenter'], [0.])
assert list(data2['x']) == [('', '', '')]
def test_statsplot_info_filter(diskcaching):
"test the view"
beads, mdl = _Fig.create(beads=[1, 7, 14, 33, 12], withhp=True)
mdl.tasks.jobs.launch(list(mdl.tasks.processors.values()))
mdl.theme.__dict__.update(
xinfo=[AxisConfig("hairpin"),
AxisConfig("closest")], yaxis="fnperbp")
cache = dict(_HairpinPlot(beads, mdl.tasks.processors)._reset())
assert cache['x_range']['factors'] == list(
zip(repeat('GF1'), repeat(""),
['157.0', '258.0', '393.0', '503.0', '704.0', '795.0']))
mdl.display.ranges[('peaks', 'baseposition')] = Slice(200, 400)
cache = dict(_HairpinPlot(beads, mdl.tasks.processors)._reset())
assert cache['x_range']['factors'] == list(
zip(repeat('GF1'), repeat(""), ['258.0', '393.0']))
def test_statsplot_info_zmum_vsbp(diskcaching):
"test the view"
fov, mdl = _Fig.create(withhp=True)
mdl.tasks.jobs.launch(list(mdl.tasks.processors.values()))
mdl.theme.__dict__.update(
xinfo=[AxisConfig("closest"),
AxisConfig("binnedz")],
yaxis="baseposition")
cache = dict(_HairpinPlot(fov, mdl.tasks.processors)._reset())
_check_validity(cache, "z (bp)")
assert np.abs(cache[_Fig.y_range]['max_interval'] - 1531) < 5
def test_statsplot_info_hpins1(diskcaching):
"test the view"
fov, mdl = _Fig.create(withhp=True)
mdl.tasks.jobs.launch(list(mdl.tasks.processors.values()))
mdl.theme.__dict__.update(xinfo=[AxisConfig("status")],
yaxis="averageduration")
cache = dict(_HairpinPlot(fov, mdl.tasks.processors)._reset())
_check_validity(cache, "binding duration (s)")
assert cache['x_range']['factors'] == [
('\u2063baseline', '', ''),
('\u2063\u2063identified', '', ''),
('\u2063\u2063\u2063\u2063unidentified', '', ''),
]
def test_statsplot_info_hpins3(diskcaching):
"test the view"
fov, mdl = _Fig.create(withhp=True)
mdl.tasks.jobs.launch(list(mdl.tasks.processors.values()))
mdl.theme.__dict__.update(xinfo=[AxisConfig("closest")], yaxis="distance")
cache = dict(_HairpinPlot(fov, mdl.tasks.processors)._reset())
_check_validity(cache, "Δ(closest binding - blockage) (bp)")
assert cache['x_range']['factors'] == list(
zip(
[
'38.0', '46.0', '151.0', '157.0', '222.0', '258.0', '274.0',
'294.0', '347.0', '357.0', '379.0', '393.0', '503.0', '540.0',
'569.0', '576.0', '659.0', '704.0', '738.0', '754.0', '784.0',
'791.0', '795.0', '800.0'
],
repeat(""),
repeat(""),
))
def test_statsplot_info_fnperbp(diskcaching):
"test the view"
fov, mdl = _Fig.create(beads=[1, 7, 14, 33, 12], withhp=True)
mdl.tasks.jobs.launch(list(mdl.tasks.processors.values()))
mdl.theme.__dict__.update(
xinfo=[AxisConfig("hairpin"),
AxisConfig("closest")], yaxis="fnperbp")
cache = dict(_HairpinPlot(fov, mdl.tasks.processors)._reset())
assert cache['x_range']['factors'] == list(
zip(repeat('GF1'), repeat(""),
['157.0', '258.0', '393.0', '503.0', '704.0', '795.0']))
stats = cache['_stats']['data']
for i in ('bottom', 'top'):
assert np.isnan(stats[i]).sum() == 0
assert np.all(stats['bottom'] <= stats['boxcenter'])
assert np.all(stats['top'] >= stats['boxcenter'])
def test_statsplot_info_pkcount(diskcaching):
"test the view"
beads, mdl = _Fig.create(beads=[13, 3, 27], withhp=True)
mdl.tasks.jobs.launch(list(mdl.tasks.processors.values()))
for name in ('closest', 'exclusive'):
mdl.theme.__dict__.update(
xinfo=[AxisConfig("hairpin"),
AxisConfig(name)], yaxis="bead")
cache = dict(_HairpinPlot(beads, mdl.tasks.processors)._reset())
assert_allclose(cache['_stats']['data']['boxheight'],
[100., *((200 / 3, ) * 3), *((100, ) * 3)])
assert cache['x_range']['factors'] == [('GF3', '', '46.0'),
('GF3', '', '274.0'),
('GF3', '', '357.0'),
('GF3', '', '576.0'),
('GF3', '', '659.0'),
('GF3', '', '754.0'),
('GF3', '', '784.0')]