def combine(lines, increment):
# we return a new PolyLine which is a composite (summed horizontally) of inputs
composite = PolyLine()
# find the range defined by the curves
minY = None
maxY = None
for l in lines:
minY = PolyLine.min(minY, l.min_y())
maxY = PolyLine.max(maxY, l.max_y())
# special case if the lines are already horizontal or None
if minY == maxY:
minSumX = None
maxSumX = None
for line in lines:
minX = None
maxX = None
for point in line.points:
minX = PolyLine.min(minX, point.x)
maxX = PolyLine.max(maxX, point.x)
minSumX = PolyLine.sum(minSumX, minX)
maxSumX = PolyLine.sum(maxSumX, maxX)
composite.add(Point(minSumX, minY))
if minX != maxX:
composite.add(Point(maxSumX, maxY))
return composite
# create an array of ys in equal increments, with highest first
# this is assuming that price decreases with increase in demand (buyers!)
# but seems to work with multiple suppliers?
ys = sorted(np.linspace(minY, maxY, num=increment), reverse=True)
# print ys
# print minY, maxY
# now find the cumulative x associated with each y in the array
# starting with the highest y
for y in ys:
xt = None
for line in lines:
x = line.x(y, left=np.nan)
# print x, y
if x is not None:
xt = x if xt is None else xt + x
composite.add(Point(xt, y))
return composite
def combine(lines, increment):
# we return a new PolyLine which is a composite (summed horizontally) of inputs
composite = PolyLine()
# find the range defined by the curves
minY = None
maxY = None
for l in lines:
minY = PolyLine.min(minY, l.min_y())
maxY = PolyLine.max(maxY, l.max_y())
# special case if the lines are already horizontal or None
if minY == maxY:
minSumX = None
maxSumX = None
for line in lines:
minX = None
maxX = None
for point in line.points:
minX = PolyLine.min(minX, point.x)
maxX = PolyLine.max(maxX, point.x)
minSumX = PolyLine.sum(minSumX, minX)
maxSumX = PolyLine.sum(maxSumX, maxX)
composite.add(Point(minSumX, minY))
if minX != maxX:
composite.add(Point(maxSumX, maxY))
return composite
# create an array of ys in equal increments, with highest first
# this is assuming that price decreases with increase in demand (buyers!)
# but seems to work with multiple suppliers?
ys = sorted(np.linspace(minY, maxY, num=increment), reverse=True)
# print ys
# print minY, maxY
# now find the cumulative x associated with each y in the array
# starting with the highest y
for y in ys:
xt = None
for line in lines:
x = line.x(y, left=np.nan)
# print x, y
if x is not None:
xt = x if xt is None else xt + x
composite.add(Point(xt, y))
return composite
def test_poly_line_max_second_none():
max = PolyLine.max(1,None)
assert max == 1
def test_poly_line_max_first_none():
max = PolyLine.max(None,2)
assert max == 2
def test_poly_line_max():
max = PolyLine.max(1,2)
assert max == 2
def test_poly_line_max_second_none():
max = PolyLine.max(1, None)
assert max == 1
def test_poly_line_max_first_none():
max = PolyLine.max(None, 2)
assert max == 2
def test_poly_line_max():
max = PolyLine.max(1, 2)
assert max == 2
