/usr/include/openturns/swig/Staircase_doc.i is in libopenturns-dev 1.7-3.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | %feature("docstring") OT::Staircase
"Staircase.
Available constructors:
Staircase(*data, legend=' '*)
Staircase(*data, color, lineStyle, lineWidth, pattern, legend=' '*)
Staircase(*data, color, lineStyle, pattern, legend=' '*)
Parameters
----------
data : 2-d sequence of float
Points from which the Staircase is built, must be of dimension 2: the
discontinuous points and their corresponding height.
legend : str
Legend of the Staircase.
color : str
Color of the curve. If not specified, by default it is 'blue'.
lineStyle : str
Style of the curve. If not specified, by default it is 'solid'.
lineWidth : int
Width of the curve. If not specified, by default it is 1.
pattern : str
Pattern which is 'S' or 's'. By default the pattern is equal to 's'. Going
from :math:`(x_1, y_1)` to :math:`(x_2, y_2)` with :math:`x_1<x_2`,
pattern='s' moves first horizontal then vertical, whereas pattern='S' moves
the other way around.
Examples
--------
>>> import openturns as ot
>>> distribution = ot.Normal([0.5], [2.], ot.CorrelationMatrix(1))
>>> sample = distribution.getSample(200)
>>> # Construct empirical CDF for the sample
>>> data = ot.NumericalSample(20, 2)
>>> cursor = ot.NumericalPoint(2)
>>> for i in range(20):
... cursor[0] = 13. * i / 20 - 6.5
... count = 0.
... for j in range(200):
... if(sample[j, 0] < cursor[0]):
... count += 1.
... cursor[1] = count / 200
... data[i] = cursor
>>> # Create an empty graph
>>> myGraph = ot.Graph('A staircase', 'x1', 'x2', True, 'topleft')
>>> # Create the staircase
>>> myStaircase = ot.Staircase(data, 'blue', 'solid', 's', 'Normal CDF')
>>> myGraph.add(myStaircase)"
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