def test_arg_find_runs_offset(self):
# because of the nature of the find_runs algorithm, there may be
# fencepost errors with runs that start at x[1] or x[-2]
x = array([10, 12, 13, 14, 28, 16])
assert_equal(arg_find_runs(x), [[0, 1], [1, 4], [4, 5], [5, 6]])
x = array([10, 15, 16, 17, 34])
assert_equal(arg_find_runs(x), [[0, 1], [1, 4], [4, 5]])
def _get_selection_screencoords(self):
""" Returns a tuple of (x1, x2) screen space coordinates of the start
and end selection points.
If there is no current selection, then returns an empty list.
"""
ds = getattr(self.plot, self.axis)
selection = ds.metadata.get(self.metadata_name, None)
if selection is None:
return []
# "selections" metadata must be a tuple
if self.metadata_name == "selections" or \
(selection is not None and isinstance(selection, tuple)):
if selection is not None and len(selection) == 2:
return [self.mapper.map_screen(array(selection))]
else:
return []
# All other metadata is interpreted as a mask on dataspace
else:
ar = arange(0, len(selection), 1)
runs = arg_find_runs(ar[selection])
coords = []
for inds in runs:
start = ds._data[ar[selection][inds[0]]]
end = ds._data[ar[selection][inds[1] - 1]]
coords.append(self.mapper.map_screen(array((start, end))))
return coords
def _get_selection_screencoords(self):
""" Returns a tuple of (x1, x2) screen space coordinates of the start
and end selection points.
If there is no current selection, then returns an empty list.
"""
ds = getattr(self.plot, self.axis)
selection = ds.metadata.get(self.metadata_name, None)
if selection is None:
return []
# "selections" metadata must be a tuple
if self.metadata_name == "selections" or \
(selection is not None and isinstance(selection, tuple)):
if selection is not None and len(selection) == 2:
return [self.mapper.map_screen(array(selection))]
else:
return []
# All other metadata is interpreted as a mask on dataspace
else:
ar = arange(0,len(selection), 1)
runs = arg_find_runs(ar[selection])
coords = []
for inds in runs:
start = ds._data[ar[selection][inds[0]]]
end = ds._data[ar[selection][inds[1]-1]]
coords.append(self.mapper.map_screen(array((start, end))))
return coords
def render(self, gc, component):
# Uses the component to map our path into screen space
nan_mask = invert(isnan(self.path[:, 0])).astype(int)
blocks = [b for b in arg_find_runs(nan_mask, "flat") if nan_mask[b[0]] != 0]
screen_pts = component.map_screen(self.path)
with gc:
gc.clip_to_rect(component.x, component.y, component.width, component.height)
gc.set_stroke_color(self.line_color_)
for start, end in blocks:
gc.begin_path()
gc.lines(screen_pts[start:end])
gc.stroke_path()
self.render_turtle(gc, component)
def render(self, gc, component):
# Uses the component to map our path into screen space
nan_mask = invert(isnan(self.path[:, 0])).astype(int)
blocks = [
b for b in arg_find_runs(nan_mask, "flat") if nan_mask[b[0]] != 0
]
screen_pts = component.map_screen(self.path)
with gc:
gc.clip_to_rect(component.x, component.y, component.width,
component.height)
gc.set_stroke_color(self.line_color_)
for start, end in blocks:
gc.begin_path()
gc.lines(screen_pts[start:end])
gc.stroke_path()
self.render_turtle(gc, component)
def _get_selection_screencoords(self):
""" Returns a tuple of (x1, x2) screen space coordinates of the start
and end selection points.
If there is no current selection, then returns None.
"""
ds = getattr(self.plot, self.axis)
selection = ds.metadata[self.metadata_name]
if selection is None or len(selection) == 1:
return []
# if not an even number of points, trim the last point
elif len(selection)%2 != 0:
del selection[-1]
# "selections" metadata is a tuple of selection pairs
if self.metadata_name == "selections":
coords = []
for index in range(len(selection)/2):
interval = (selection[index*2],selection[index*2+1])
coords.append(self.mapper.map_screen(array(interval)))
return coords
else:
selection_points = len(selection)
coords = []
# treat the metadata as a mask on dataspace
if len(ds._data) == selection_points:
selected = nonzero(selection)[0]
runs = arg_find_runs(selected)
for run in runs:
start = ds._data[selected[run[0]]]
end = ds._data[selected[run[1]-1]]
coords.append(self.mapper.map_screen(array((start, end))))
# selection is tuples of selected regions in dataspace
else:
for index in range(len(selection)/2):
interval = (selection[index*2],selection[index*2+1])
coords.append(self.mapper.map_screen(array(interval)))
return coords
def test_arg_find_runs_flat(self):
x = array([0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0])
assert_equal(arg_find_runs(x, order="flat"), [[0, 3], [3, 7], [7, 11]])
def test_arg_find_runs_descending(self):
x = array([30, 41, 40, 39, 38, 37, 12])
assert_equal(arg_find_runs(x, order="descending"), [[0, 1], [1, 6], [6, 7]])
def test_arg_find_runs_none(self):
x = array([])
assert_equal(arg_find_runs(x), [])
x = array([12, 15, 27])
assert_equal(arg_find_runs(x), [[0, 1], [1, 2], [2, 3]])
def test_arg_find_runs_end(self):
x = array([18, 23, 24, 25])
assert_equal(arg_find_runs(x), [[0, 1], [1, 4]])
def test_arg_find_runs_start(self):
x = array([3, 4, 5, 12, 9, 17])
assert_equal(arg_find_runs(x), [[0, 3], [3, 4], [4, 5], [5, 6]])
def test_arg_find_runs_middle(self):
x = array([0, 8, 7, 8, 9, 2, 3, 4, 10])
assert_equal(arg_find_runs(x), [[0, 1], [1, 2], [2, 5], [5, 8], [8, 9]])
