Use the options below to import an existing wallet or create a new one.
When you create a new wallet, a new Nano seed will be generated which can be used to create brand new accounts on the Nano network.
Make sure you back up your seed, write it down, and keep it incredibly safe! There is NO way to recover it after creation, and all funds inside WILL be lost without it! You have been warned!
If you already have a Nano wallet, you can import it below. When you import a wallet, it replaces the previous one in the GUI but none of your existing accounts are affected since the wallet can be restored simply by importing it again. The seed is not stored anywhere besides in your local client so please make sure you have it stored elsewhere. Use the drop down below to select which type of import you want to use.
If you have saved your wallet to a file using Nault before, use the button below to import it.
Make sure you have the Nano app installed, then connect your ledger device via USB. Ledger/Nault User Guide
Your new Nano wallet has been created! Below is the seed and mnemonic phrase for your wallet, you can use whichever you prefer.
{{ (l * 4) + i + 1 }} {{ word }}
Copy mnemonic to clipboard
The last step is to set a new password for your wallet. Your password is used to encrypt the sensitive parts of your wallet when it is locked, which disables sending, receiving, creating accounts, and other operations.
Set your wallet password below:
Your wallet has been configured and you are ready to send and receive Nano!

ProTip: Press the Ledger status bar on the left side to reload your Ledger when connecting or disconnecting it.


The strength of JavaScript is that you can do anything. The weakness is that you will.
Reg Braithwaite: Author
Concepts
How does JavaScript compare to HTML and CSS?
HTML defines the structure of a page (eg: headings, paragraphs). CSS allows us to change its appearance (eg: green, sans serif font with a light blue background). JavaScript adds interactivity so that the page responds to user actions. An analogy is the human body: HTML is the skeleton, CSS is what it looks like and JavaScript is the muscles that permit movement.
Explain control flow and loops using an example process from everyday life, for example ‘waking up’ or ‘brushing your teeth’. Sequence refers to the order that things happen. An example is getting dressed. Do I put my trousers on then my shirt, or shirt first, followed by trousers? In that case, order does not really matter. However, when I’m putting on my shoes and socks, it’s better if I put on my socks before my shoes.
Control flow or selection means choosing an action depending on some test. ‘Is it sunny today?’ might be the test. If it is sunny, then an action could be: wear a sunhat; but if not, then wear a jacket.
Looping or iteration involves repeating an action. This can happen a predetermined number of times, while a condition is true, or until something happens. An everyday example might involve flossing teeth. Rub the floss over the inner surface of each tooth five times.
Explain the difference between accessing data from arrays and objects.
An array is a data structure that contains a list of values. Each value is accessed according to its position in the array. It is important to remember that arrays in JavaScript, as in most programming languages, are zero based. So the first item is at position zero, the second at position one, and so on.
An object is a data structure that contains both data and functions. The data is stored in key-value pairs. The most common way to access data is to use dot notation: objectName.key Bracket notation is also possible: objectName['key']
Explain what functions are and why they are useful.
A function is a piece of code designed to carry out a specific task. Functions can accept data, perform actions on that data, and return a result. The advantage of functions is that a block of code is written once, then it can be reused again and again without repeating the same code.


"""Line-like geometrical entities.
Contains
========
LinearEntity3D
Line3D
Ray3D
Segment3D
"""
from __future__ import division, print_function
from sympy.core import Dummy, S, nan
from sympy.functions.elementary.trigonometric import acos
from sympy.simplify.simplify import simplify
from sympy.solvers.solveset import solveset, linsolve
from sympy.geometry.exceptions import GeometryError
from sympy.core.compatibility import is_sequence, range
from .entity import GeometryEntity
from .point import Point3D
from .util import _symbol
[docs]class LinearEntity3D(GeometryEntity):
"""An base class for all linear entities (line, ray and segment)
in a 3-dimensional Euclidean space.
Attributes
==========
p1
p2
direction_ratio
direction_cosine
points
Notes
=====
This is a base class and is not meant to be instantiated.
"""
def __new__(cls, p1, p2, **kwargs):
p1 = Point3D(p1)
p2 = Point3D(p2)
if p1 == p2:
# if it makes sense to return a Point, handle in subclass
raise ValueError(
"%s.__new__ requires two unique Points." % cls.__name__)
return GeometryEntity.__new__(cls, p1, p2, **kwargs)
@property
def p1(self):
"""The first defining point of a linear entity.
See Also
========
sympy.geometry.point.Point3D
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2 = Point3D(0, 0, 0), Point3D(5, 3, 1)
>>> l = Line3D(p1, p2)
>>> l.p1
Point3D(0, 0, 0)
"""
return self.args[0]
@property
def p2(self):
"""The second defining point of a linear entity.
See Also
========
sympy.geometry.point.Point3D
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2 = Point3D(0, 0, 0), Point3D(5, 3, 1)
>>> l = Line3D(p1, p2)
>>> l.p2
Point3D(5, 3, 1)
"""
return self.args[1]
@property
def direction_ratio(self):
"""The direction ratio of a given line in 3D.
See Also
========
sympy.geometry.line.Line.equation
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2 = Point3D(0, 0, 0), Point3D(5, 3, 1)
>>> l = Line3D(p1, p2)
>>> l.direction_ratio
[5, 3, 1]
"""
p1, p2 = self.points
return p1.direction_ratio(p2)
@property
def direction_cosine(self):
"""The normalized direction ratio of a given line in 3D.
See Also
========
sympy.geometry.line.Line.equation
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2 = Point3D(0, 0, 0), Point3D(5, 3, 1)
>>> l = Line3D(p1, p2)
>>> l.direction_cosine
[sqrt(35)/7, 3*sqrt(35)/35, sqrt(35)/35]
>>> sum(i**2 for i in _)
1
"""
p1, p2 = self.points
return p1.direction_cosine(p2)
@property
def length(self):
"""
The length of the line.
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2 = Point3D(0, 0, 0), Point3D(3, 5, 1)
>>> l1 = Line3D(p1, p2)
>>> l1.length
oo
"""
return S.Infinity
@property
def points(self):
"""The two points used to define this linear entity.
Returns
=======
points : tuple of Points
See Also
========
sympy.geometry.point.Point3D
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2 = Point3D(0, 0, 0), Point3D(5, 11, 1)
>>> l1 = Line3D(p1, p2)
>>> l1.points
(Point3D(0, 0, 0), Point3D(5, 11, 1))
"""
return (self.p1, self.p2)
@staticmethod
[docs] def are_concurrent(*lines):
"""Is a sequence of linear entities concurrent?
Two or more linear entities are concurrent if they all
intersect at a single point.
Parameters
==========
lines : a sequence of linear entities.
Returns
=======
True : if the set of linear entities are concurrent,
False : otherwise.
Notes
=====
Simply take the first two lines and find their intersection.
If there is no intersection, then the first two lines were
parallel and had no intersection so concurrency is impossible
amongst the whole set. Otherwise, check to see if the
intersection point of the first two lines is a member on
the rest of the lines. If so, the lines are concurrent.
See Also
========
sympy.geometry.util.intersection
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2 = Point3D(0, 0, 0), Point3D(3, 5, 2)
>>> p3, p4 = Point3D(-2, -2, -2), Point3D(0, 2, 1)
>>> l1, l2, l3 = Line3D(p1, p2), Line3D(p1, p3), Line3D(p1, p4)
>>> Line3D.are_concurrent(l1, l2, l3)
True
>>> l4 = Line3D(p2, p3)
>>> Line3D.are_concurrent(l2, l3, l4)
False
"""
# Concurrency requires intersection at a single point; One linear
# entity cannot be concurrent.
if len(lines) <= 1:
return False
try:
# Get the intersection (if parallel)
p = lines[0].intersection(lines[1])
if len(p) == 0:
return False
# Make sure the intersection is on every linear entity
for line in lines[2:]:
if p[0] not in line:
return False
return True
except AttributeError:
return False
[docs] def is_parallel(l1, l2):
"""Are two linear entities parallel?
Parameters
==========
l1 : LinearEntity
l2 : LinearEntity
Returns
=======
True : if l1 and l2 are parallel,
False : otherwise.
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2 = Point3D(0, 0, 0), Point3D(3, 4, 5)
>>> p3, p4 = Point3D(2, 1, 1), Point3D(8, 9, 11)
>>> l1, l2 = Line3D(p1, p2), Line3D(p3, p4)
>>> Line3D.is_parallel(l1, l2)
True
>>> p5 = Point3D(6, 6, 6)
>>> l3 = Line3D(p3, p5)
>>> Line3D.is_parallel(l1, l3)
False
"""
if l1 == l2:
return True
a = l1.direction_cosine
b = l2.direction_cosine
# lines are parallel if the direction_cosines are the same or
# differ by a constant
rat = set()
for i, j in zip(a, b):
if i and j:
rat.add(i/j)
if len(rat) > 1:
return False
elif i or j:
return False
return True
[docs] def is_perpendicular(l1, l2):
"""Are two linear entities perpendicular?
Parameters
==========
l1 : LinearEntity
l2 : LinearEntity
Returns
=======
True : if l1 and l2 are perpendicular,
False : otherwise.
See Also
========
direction_ratio
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2, p3 = Point3D(0, 0, 0), Point3D(1, 1, 1), Point3D(-1, 2, 0)
>>> l1, l2 = Line3D(p1, p2), Line3D(p2, p3)
>>> l1.is_perpendicular(l2)
False
>>> p4 = Point3D(5, 3, 7)
>>> l3 = Line3D(p1, p4)
>>> l1.is_perpendicular(l3)
False
"""
a = sum([i*j for i, j in zip(l1.direction_ratio, l2.direction_ratio)])
if a == 0:
return True
else:
return False
[docs] def angle_between(l1, l2):
"""The angle formed between the two linear entities.
Parameters
==========
l1 : LinearEntity
l2 : LinearEntity
Returns
=======
angle : angle in radians
Notes
=====
From the dot product of vectors v1 and v2 it is known that:
``dot(v1, v2) = |v1|*|v2|*cos(A)``
where A is the angle formed between the two vectors. We can
get the directional vectors of the two lines and readily
find the angle between the two using the above formula.
See Also
========
is_perpendicular
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2, p3 = Point3D(0, 0, 0), Point3D(1, 1, 1), Point3D(-1, 2, 0)
>>> l1, l2 = Line3D(p1, p2), Line3D(p2, p3)
>>> l1.angle_between(l2)
acos(-sqrt(2)/3)
"""
v1 = l1.p2 - l1.p1
v2 = l2.p2 - l2.p1
return acos(v1.dot(v2)/(abs(v1)*abs(v2)))
[docs] def parallel_line(self, p):
"""Create a new Line parallel to this linear entity which passes
through the point `p`.
Parameters
==========
p : Point3D
Returns
=======
line : Line3D
See Also
========
is_parallel
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2, p3 = Point3D(0, 0, 0), Point3D(2, 3, 4), Point3D(-2, 2, 0)
>>> l1 = Line3D(p1, p2)
>>> l2 = l1.parallel_line(p3)
>>> p3 in l2
True
>>> l1.is_parallel(l2)
True
"""
d = self.direction_ratio
return Line3D(p, direction_ratio=d)
[docs] def perpendicular_line(self, p):
"""Create a new Line perpendicular to this linear entity which passes
through the point `p`.
Parameters
==========
p : Point3D
Returns
=======
line : Line3D
See Also
========
is_perpendicular, perpendicular_segment
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2, p3 = Point3D(0, 0, 0), Point3D(2, 3, 4), Point3D(-2, 2, 0)
>>> l1 = Line3D(p1, p2)
>>> l2 = l1.perpendicular_line(p3)
>>> p3 in l2
True
>>> l1.is_perpendicular(l2)
True
"""
p = Point3D(p)
if p in self:
raise NotImplementedError("Given point should not be on the line")
t = Dummy()
a = self.arbitrary_point(t)
b = [i - j for i, j in zip(p.args, a.args)]
c = sum([i*j for i, j in zip(b, self.direction_ratio)])
d = list(solveset(c, t))
e = a.subs(t, d[0])
return Line3D(p, e)
[docs] def perpendicular_segment(self, p):
"""Create a perpendicular line segment from `p` to this line.
The enpoints of the segment are ``p`` and the closest point in
the line containing self. (If self is not a line, the point might
not be in self.)
Parameters
==========
p : Point3D
Returns
=======
segment : Segment3D
Notes
=====
Returns `p` itself if `p` is on this linear entity.
See Also
========
perpendicular_line
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2, p3 = Point3D(0, 0, 0), Point3D(1, 1, 1), Point3D(0, 2, 0)
>>> l1 = Line3D(p1, p2)
>>> s1 = l1.perpendicular_segment(p3)
>>> l1.is_perpendicular(s1)
True
>>> p3 in s1
True
>>> l1.perpendicular_segment(Point3D(4, 0, 0))
Segment3D(Point3D(4/3, 4/3, 4/3), Point3D(4, 0, 0))
"""
p = Point3D(p)
if p in self:
raise NotImplementedError("Given point should not be on the line")
t = Dummy()
a = self.arbitrary_point(t)
b = [i - j for i, j in zip(p.args, a.args)]
c = sum([i*j for i, j in zip(b, self.direction_ratio)])
d = list(solveset(c, t))
e = a.subs(t, d[0])
return Segment3D(p, e)
[docs] def projection(self, o):
"""Project a point, line, ray, or segment onto this linear entity.
Parameters
==========
other : Point or LinearEntity (Line, Ray, Segment)
Returns
=======
projection : Point or LinearEntity (Line, Ray, Segment)
The return type matches the type of the parameter ``other``.
Raises
======
GeometryError
When method is unable to perform projection.
Notes
=====
A projection involves taking the two points that define
the linear entity and projecting those points onto a
Line and then reforming the linear entity using these
projections.
A point P is projected onto a line L by finding the point
on L that is closest to P. This point is the intersection
of L and the line perpendicular to L that passes through P.
See Also
========
sympy.geometry.point.Point3D, perpendicular_line
Examples
========
>>> from sympy import Point3D, Line3D, Segment3D, Rational
>>> p1, p2, p3 = Point3D(0, 0, 1), Point3D(1, 1, 2), Point3D(2, 0, 1)
>>> l1 = Line3D(p1, p2)
>>> l1.projection(p3)
Point3D(2/3, 2/3, 5/3)
>>> p4, p5 = Point3D(10, 0, 1), Point3D(12, 1, 3)
>>> s1 = Segment3D(p4, p5)
>>> l1.projection(s1)
[Segment3D(Point3D(10/3, 10/3, 13/3), Point3D(5, 5, 6))]
"""
tline = Line3D(self.p1, self.p2)
def _project(p):
"""Project a point onto the line representing self."""
if p in tline:
return p
l1 = tline.perpendicular_line(p)
return tline.intersection(l1)[0]
projected = None
if isinstance(o, Point3D):
return _project(o)
elif isinstance(o, LinearEntity3D):
n_p1 = _project(o.p1)
n_p2 = _project(o.p2)
if n_p1 == n_p2:
projected = n_p1
else:
projected = o.__class__(n_p1, n_p2)
# Didn't know how to project so raise an error
if projected is None:
n1 = self.__class__.__name__
n2 = o.__class__.__name__
raise GeometryError(
"Do not know how to project %s onto %s" % (n2, n1))
return self.intersection(projected)
[docs] def intersection(self, o):
"""The intersection with another geometrical entity.
Parameters
==========
o : Point or LinearEntity3D
Returns
=======
intersection : list of geometrical entities
See Also
========
sympy.geometry.point.Point3D
Examples
========
>>> from sympy import Point3D, Line3D, Segment3D
>>> p1, p2, p3 = Point3D(0, 0, 0), Point3D(1, 1, 1), Point3D(7, 7, 7)
>>> l1 = Line3D(p1, p2)
>>> l1.intersection(p3)
[Point3D(7, 7, 7)]
>>> l1 = Line3D(Point3D(4,19,12), Point3D(5,25,17))
>>> l2 = Line3D(Point3D(-3, -15, -19), direction_ratio=[2,8,8])
>>> l1.intersection(l2)
[Point3D(1, 1, -3)]
>>> p6, p7 = Point3D(0, 5, 2), Point3D(2, 6, 3)
>>> s1 = Segment3D(p6, p7)
>>> l1.intersection(s1)
[]
"""
if isinstance(o, Point3D):
if o in self:
return [o]
else:
return []
elif isinstance(o, LinearEntity3D):
if self == o:
return [self]
elif self.is_parallel(o):
if isinstance(self, Line3D):
if o.p1 in self:
return [o]
return []
elif isinstance(self, Ray3D):
if isinstance(o, Ray3D):
# case 1, rays in the same direction
if self.xdirection == o.xdirection and \
self.ydirection == o.ydirection and \
self.zdirection == o.zdirection:
return [self] if (self.source in o) else [o]
# case 2, rays in the opposite directions
else:
if o.source in self:
if self.source == o.source:
return [self.source]
return [Segment3D(o.source, self.source)]
return []
elif isinstance(o, Segment3D):
if o.p1 in self:
if o.p2 in self:
return [o]
return [Segment3D(o.p1, self.source)]
elif o.p2 in self:
return [Segment3D(o.p2, self.source)]
return []
elif isinstance(self, Segment3D):
if isinstance(o, Segment3D):
# A reminder that the points of Segments are ordered
# in such a way that the following works. See
# Segment3D.__new__ for details on the ordering.
if self.p1 not in o:
if self.p2 not in o:
# Neither of the endpoints are in o so either
# o is contained in this segment or it isn't
if o in self:
return [o]
return []
else:
# p1 not in o but p2 is. Either there is a
# segment as an intersection, or they only
# intersect at an endpoint
if self.p2 == o.p1:
return [o.p1]
return [Segment3D(o.p1, self.p2)]
elif self.p2 not in o:
# p2 not in o but p1 is. Either there is a
# segment as an intersection, or they only
# intersect at an endpoint
if self.p1 == o.p2:
return [o.p2]
return [Segment3D(o.p2, self.p1)]
# Both points of self in o so the whole segment
# is in o
return [self]
else: # unrecognized LinearEntity
raise NotImplementedError
else:
# If the lines are not parallel then solve their arbitrary points
# to obtain the point of intersection
t = t1, t2 = Dummy(), Dummy()
a = self.arbitrary_point(t1)
b = o.arbitrary_point(t2)
dx = a.x - b.x
c = linsolve([dx, a.y - b.y], t).args[0]
d = linsolve([dx, a.z - b.z], t).args[0]
if len(c.free_symbols) == 1 and len(d.free_symbols) == 1:
return []
e = a.subs(t1, c[0])
if e in self and e in o:
return [e]
else:
return []
return o.intersection(self)
[docs] def arbitrary_point(self, parameter='t'):
"""A parameterized point on the Line.
Parameters
==========
parameter : str, optional
The name of the parameter which will be used for the parametric
point. The default value is 't'. When this parameter is 0, the
first point used to define the line will be returned, and when
it is 1 the second point will be returned.
Returns
=======
point : Point3D
Raises
======
ValueError
When ``parameter`` already appears in the Line's definition.
See Also
========
sympy.geometry.point.Point3D
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2 = Point3D(1, 0, 0), Point3D(5, 3, 1)
>>> l1 = Line3D(p1, p2)
>>> l1.arbitrary_point()
Point3D(4*t + 1, 3*t, t)
"""
t = _symbol(parameter)
if t.name in (f.name for f in self.free_symbols):
raise ValueError('Symbol %s already appears in object '
'and cannot be used as a parameter.' % t.name)
x = simplify(self.p1.x + t*(self.p2.x - self.p1.x))
y = simplify(self.p1.y + t*(self.p2.y - self.p1.y))
z = simplify(self.p1.z + t*(self.p2.z - self.p1.z))
return Point3D(x, y, z)
[docs] def is_similar(self, other):
"""
Return True if self and other are contained in the same line.
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2, p3 = Point3D(0, 0, 0), Point3D(1, 1, 1), Point3D(2, 2, 2)
>>> l1 = Line3D(p1, p2)
>>> l2 = Line3D(p1, p3)
>>> l1.is_similar(l2)
True
"""
if isinstance(other, Line3D):
if self.direction_cosine == other.direction_cosine and other.p1 in self:
return True
else:
return False
raise NotImplementedError()
def __contains__(self, other):
"""Return a definitive answer or else raise an error if it cannot
be determined that other is on the boundaries of self."""
result = self.contains(other)
if result is not None:
return result
else:
raise Undecidable(
"can't decide whether '%s' contains '%s'" % (self, other))
[docs] def contains(self, other):
"""Subclasses should implement this method and should return
True if other is on the boundaries of self;
False if not on the boundaries of self;
None if a determination cannot be made."""
raise NotImplementedError()
[docs]class Line3D(LinearEntity3D):
"""An infinite 3D line in space.
A line is declared with two distinct points or a point and direction_ratio
as defined using keyword `direction_ratio`.
Parameters
==========
p1 : Point3D
pt : Point3D
direction_ratio : list
See Also
========
sympy.geometry.point.Point3D
Examples
========
>>> import sympy
>>> from sympy import Point3D
>>> from sympy.abc import L
>>> from sympy.geometry import Line3D, Segment3D
>>> L = Line3D(Point3D(2, 3, 4), Point3D(3, 5, 1))
>>> L
Line3D(Point3D(2, 3, 4), Point3D(3, 5, 1))
>>> L.points
(Point3D(2, 3, 4), Point3D(3, 5, 1))
"""
def __new__(cls, p1, pt=None, direction_ratio=[], **kwargs):
if isinstance(p1, LinearEntity3D):
p1, pt = p1.args
else:
p1 = Point3D(p1)
if pt is not None and len(direction_ratio) == 0:
pt = Point3D(pt)
elif len(direction_ratio) == 3 and pt is None:
pt = Point3D(p1.x + direction_ratio[0], p1.y + direction_ratio[1],
p1.z + direction_ratio[2])
else:
raise ValueError('A 2nd Point or keyword "direction_ratio" must '
'be used.')
return LinearEntity3D.__new__(cls, p1, pt, **kwargs)
[docs] def plot_interval(self, parameter='t'):
"""The plot interval for the default geometric plot of line. Gives
values that will produce a line that is +/- 5 units long (where a
unit is the distance between the two points that define the line).
Parameters
==========
parameter : str, optional
Default value is 't'.
Returns
=======
plot_interval : list (plot interval)
[parameter, lower_bound, upper_bound]
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2 = Point3D(0, 0, 0), Point3D(5, 3, 1)
>>> l1 = Line3D(p1, p2)
>>> l1.plot_interval()
[t, -5, 5]
"""
t = _symbol(parameter)
return [t, -5, 5]
[docs] def equation(self, x='x', y='y', z='z', k='k'):
"""The equation of the line in 3D
Parameters
==========
x : str, optional
The name to use for the x-axis, default value is 'x'.
y : str, optional
The name to use for the y-axis, default value is 'y'.
z : str, optional
The name to use for the x-axis, default value is 'z'.
Returns
=======
equation : tuple
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2 = Point3D(1, 0, 0), Point3D(5, 3, 0)
>>> l1 = Line3D(p1, p2)
>>> l1.equation()
(x/4 - 1/4, y/3, zoo*z, k)
"""
x, y, z, k = _symbol(x), _symbol(y), _symbol(z), _symbol(k)
p1, p2 = self.points
a = p1.direction_ratio(p2)
return (((x - p1.x)/a[0]), ((y - p1.y)/a[1]),
((z - p1.z)/a[2]), k)
[docs] def contains(self, o):
"""Return True if o is on this Line, or False otherwise.
Examples
========
>>> from sympy import Line3D
>>> a = (0, 0, 0)
>>> b = (1, 1, 1)
>>> c = (2, 2, 2)
>>> l1 = Line3D(a, b)
>>> l2 = Line3D(b, a)
>>> l1 == l2
False
>>> l1 in l2
True
"""
if is_sequence(o):
o = Point3D(o)
if isinstance(o, Point3D):
sym = list(map(Dummy, 'xyz'))
eq = self.equation(*sym)
a = [eq[i].subs(sym[i], o.args[i]) for i in range(3)]
a = [i for i in a if i != nan]
if len(a) == 1:
return True
first = a.pop(0)
for i in a:
rv = first.equals(i)
if not rv:
return rv
return True
elif not isinstance(o, LinearEntity3D):
return False
elif isinstance(o, Line3D):
return all(i in self for i in o.points)
[docs] def distance(self, o):
"""
Finds the shortest distance between a line and a point.
Raises
======
NotImplementedError is raised if o is not an instance of Point3D
Examples
========
>>> from sympy import Point3D, Line3D
>>> p1, p2 = Point3D(0, 0, 0), Point3D(1, 1, 1)
>>> s = Line3D(p1, p2)
>>> s.distance(Point3D(-1, 1, 1))
2*sqrt(6)/3
>>> s.distance((-1, 1, 1))
2*sqrt(6)/3
"""
if not isinstance(o, Point3D):
if is_sequence(o):
o = Point3D(o)
if o in self:
return S.Zero
a = self.perpendicular_segment(o).length
return a
[docs] def equals(self, other):
"""Returns True if self and other are the same mathematical entities"""
if not isinstance(other, Line3D):
return False
return Point3D.are_collinear(self.p1, other.p1, self.p2, other.p2)
[docs]class Ray3D(LinearEntity3D):
"""
A Ray is a semi-line in the space with a source point and a direction.
Parameters
==========
p1 : Point3D
The source of the Ray
p2 : Point or a direction vector
direction_ratio: Determines the direction in which the Ray propagates.
Attributes
==========
source
xdirection
ydirection
zdirection
See Also
========
sympy.geometry.point.Point3D, Line3D
Examples
========
>>> import sympy
>>> from sympy import Point3D, pi
>>> from sympy.abc import r
>>> from sympy.geometry import Ray3D
>>> r = Ray3D(Point3D(2, 3, 4), Point3D(3, 5, 0))
>>> r
Ray3D(Point3D(2, 3, 4), Point3D(3, 5, 0))
>>> r.points
(Point3D(2, 3, 4), Point3D(3, 5, 0))
>>> r.source
Point3D(2, 3, 4)
>>> r.xdirection
oo
>>> r.ydirection
oo
>>> r.direction_ratio
[1, 2, -4]
"""
def __new__(cls, p1, pt=None, direction_ratio=[], **kwargs):
if isinstance(p1, LinearEntity3D):
p1, pt = p1.args
else:
p1 = Point3D(p1)
if pt is not None and len(direction_ratio) == 0:
pt = Point3D(pt)
elif len(direction_ratio) == 3 and pt is None:
pt = Point3D(p1.x + direction_ratio[0], p1.y + direction_ratio[1],
p1.z + direction_ratio[2])
else:
raise ValueError('A 2nd Point or keyword "direction_ratio" must'
'be used.')
return LinearEntity3D.__new__(cls, p1, pt, **kwargs)
@property
def source(self):
"""The point from which the ray emanates.
See Also
========
sympy.geometry.point.Point3D
Examples
========
>>> from sympy import Point3D, Ray3D
>>> p1, p2 = Point3D(0, 0, 0), Point3D(4, 1, 5)
>>> r1 = Ray3D(p1, p2)
>>> r1.source
Point3D(0, 0, 0)
"""
return self.p1
@property
def xdirection(self):
"""The x direction of the ray.
Positive infinity if the ray points in the positive x direction,
negative infinity if the ray points in the negative x direction,
or 0 if the ray is vertical.
See Also
========
ydirection
Examples
========
>>> from sympy import Point3D, Ray3D
>>> p1, p2, p3 = Point3D(0, 0, 0), Point3D(1, 1, 1), Point3D(0, -1, 0)
>>> r1, r2 = Ray3D(p1, p2), Ray3D(p1, p3)
>>> r1.xdirection
oo
>>> r2.xdirection
0
"""
if self.p1.x < self.p2.x:
return S.Infinity
elif self.p1.x == self.p2.x:
return S.Zero
else:
return S.NegativeInfinity
@property
def ydirection(self):
"""The y direction of the ray.
Positive infinity if the ray points in the positive y direction,
negative infinity if the ray points in the negative y direction,
or 0 if the ray is horizontal.
See Also
========
xdirection
Examples
========
>>> from sympy import Point3D, Ray3D
>>> p1, p2, p3 = Point3D(0, 0, 0), Point3D(-1, -1, -1), Point3D(-1, 0, 0)
>>> r1, r2 = Ray3D(p1, p2), Ray3D(p1, p3)
>>> r1.ydirection
-oo
>>> r2.ydirection
0
"""
if self.p1.y < self.p2.y:
return S.Infinity
elif self.p1.y == self.p2.y:
return S.Zero
else:
return S.NegativeInfinity
@property
def zdirection(self):
"""The z direction of the ray.
Positive infinity if the ray points in the positive z direction,
negative infinity if the ray points in the negative z direction,
or 0 if the ray is horizontal.
See Also
========
xdirection
Examples
========
>>> from sympy import Point3D, Ray3D
>>> p1, p2, p3 = Point3D(0, 0, 0), Point3D(-1, -1, -1), Point3D(-1, 0, 0)
>>> r1, r2 = Ray3D(p1, p2), Ray3D(p1, p3)
>>> r1.ydirection
-oo
>>> r2.ydirection
0
>>> r2.zdirection
0
"""
if self.p1.z < self.p2.z:
return S.Infinity
elif self.p1.z == self.p2.z:
return S.Zero
else:
return S.NegativeInfinity
[docs] def distance(self, o):
"""
Finds the shortest distance between the ray and a point.
Raises
======
NotImplementedError is raised if o is not a Point
Examples
========
>>> from sympy import Point3D, Ray3D
>>> p1, p2 = Point3D(0, 0, 0), Point3D(1, 1, 2)
>>> s = Ray3D(p1, p2)
>>> s.distance(Point3D(-1, -1, 2))
sqrt(6)
>>> s.distance((-1, -1, 2))
sqrt(6)
"""
if not isinstance(o, Point3D):
if is_sequence(o):
o = Point3D(o)
if o in self:
return S.Zero
s = self.perpendicular_segment(o)
if not isinstance(s, Point3D):
non_o = s.p1 if s.p1 == o else s.p2
if self.contains(non_o):
return Line3D(self).distance(o) # = s.length but simpler
# the following applies when neither of the above apply
return self.source.distance(o)
[docs] def plot_interval(self, parameter='t'):
"""The plot interval for the default geometric plot of the Ray. Gives
values that will produce a ray that is 10 units long (where a unit is
the distance between the two points that define the ray).
Parameters
==========
parameter : str, optional
Default value is 't'.
Returns
=======
plot_interval : list
[parameter, lower_bound, upper_bound]
Examples
========
>>> from sympy import Point3D, Ray3D, pi
>>> r = Ray3D(Point3D(0, 0, 0), Point3D(1, 1, 1))
>>> r.plot_interval()
[t, 0, 10]
"""
t = _symbol(parameter)
return [t, 0, 10]
[docs] def contains(self, o):
"""Is other GeometryEntity contained in this Ray?"""
if isinstance(o, Ray3D):
return (Point3D.are_collinear(self.p1, self.p2, o.p1, o.p2) and
self.xdirection == o.xdirection and
self.ydirection == o.ydirection and
self.zdirection == o.zdirection)
elif isinstance(o, Segment3D):
return o.p1 in self and o.p2 in self
elif is_sequence(o):
o = Point3D(o)
if isinstance(o, Point3D):
if Point3D.are_collinear(self.p1, self.p2, o):
if self.xdirection is S.Infinity:
rv = o.x >= self.source.x
elif self.xdirection is S.NegativeInfinity:
rv = o.x <= self.source.x
elif self.ydirection is S.Infinity:
rv = o.y >= self.source.y
elif self.ydirection is S.NegativeInfinity:
rv = o.y <= self.source.y
elif self.zdirection is S.Infinity:
rv = o.z <= self.source.z
else:
rv = o.z <= self.source.z
if rv == True or rv == False:
return bool(rv)
raise Undecidable(
'Cannot determine if %s is in %s' % (o, self))
else:
# Points are not collinear, so the rays are not parallel
# and hence it is impossible for self to contain o
return False
# No other known entity can be contained in a Ray
return False
[docs] def equals(self, other):
"""Returns True if self and other are the same mathematical entities"""
if not isinstance(other, Ray3D):
return False
return self.source == other.source and other.p2 in self
[docs]class Segment3D(LinearEntity3D):
"""A undirected line segment in a 3D space.
Parameters
==========
p1 : Point3D
p2 : Point3D
Attributes
==========
length : number or sympy expression
midpoint : Point3D
See Also
========
sympy.geometry.point.Point3D, Line3D
Examples
========
>>> import sympy
>>> from sympy import Point3D
>>> from sympy.abc import s
>>> from sympy.geometry import Segment3D
>>> Segment3D((1, 0, 0), (1, 1, 1)) # tuples are interpreted as pts
Segment3D(Point3D(1, 0, 0), Point3D(1, 1, 1))
>>> s = Segment3D(Point3D(4, 3, 9), Point3D(1, 1, 7))
>>> s
Segment3D(Point3D(1, 1, 7), Point3D(4, 3, 9))
>>> s.points
(Point3D(1, 1, 7), Point3D(4, 3, 9))
>>> s.length
sqrt(17)
>>> s.midpoint
Point3D(5/2, 2, 8)
"""
def __new__(cls, p1, p2, **kwargs):
# Reorder the two points under the following ordering:
# if p1.x != p2.x then p1.x < p2.x
# if p1.x == p2.x then p1.y < p2.y
# The z-coordinate will not come into picture while ordering
p1 = Point3D(p1)
p2 = Point3D(p2)
if p1 == p2:
return Point3D(p1)
if (p1.x > p2.x) == True:
p1, p2 = p2, p1
elif (p1.x == p2.x) == True and (p1.y > p2.y) == True:
p1, p2 = p2, p1
return LinearEntity3D.__new__(cls, p1, p2, **kwargs)
[docs] def plot_interval(self, parameter='t'):
"""The plot interval for the default geometric plot of the Segment gives
values that will produce the full segment in a plot.
Parameters
==========
parameter : str, optional
Default value is 't'.
Returns
=======
plot_interval : list
[parameter, lower_bound, upper_bound]
Examples
========
>>> from sympy import Point3D, Segment3D
>>> p1, p2 = Point3D(0, 0, 0), Point3D(5, 3, 0)
>>> s1 = Segment3D(p1, p2)
>>> s1.plot_interval()
[t, 0, 1]
"""
t = _symbol(parameter)
return [t, 0, 1]
@property
def length(self):
"""The length of the line segment.
See Also
========
sympy.geometry.point.Point3D.distance
Examples
========
>>> from sympy import Point3D, Segment3D
>>> p1, p2 = Point3D(0, 0, 0), Point3D(4, 3, 3)
>>> s1 = Segment3D(p1, p2)
>>> s1.length
sqrt(34)
"""
return Point3D.distance(self.p1, self.p2)
@property
def midpoint(self):
"""The midpoint of the line segment.
See Also
========
sympy.geometry.point.Point3D.midpoint
Examples
========
>>> from sympy import Point3D, Segment3D
>>> p1, p2 = Point3D(0, 0, 0), Point3D(4, 3, 3)
>>> s1 = Segment3D(p1, p2)
>>> s1.midpoint
Point3D(2, 3/2, 3/2)
"""
return Point3D.midpoint(self.p1, self.p2)
[docs] def distance(self, o):
"""
Finds the shortest distance between a line segment and a point.
Raises
======
NotImplementedError is raised if o is not a Point3D
Examples
========
>>> from sympy import Point3D, Segment3D
>>> p1, p2 = Point3D(0, 0, 3), Point3D(1, 1, 4)
>>> s = Segment3D(p1, p2)
>>> s.distance(Point3D(10, 15, 12))
sqrt(341)
>>> s.distance((10, 15, 12))
sqrt(341)
"""
if is_sequence(o):
o = Point3D(o)
if isinstance(o, Point3D):
seg_vector = self.p2 - self.p1
pt_vector = o - self.p1
t = seg_vector.dot(pt_vector)/self.length**2
if t >= 1:
distance = Point3D.distance(self.p2, o)
elif t <= 0:
distance = Point3D.distance(self.p1, o)
else:
distance = Point3D.distance(
self.p1 + Point3D(t*seg_vector.x, t*seg_vector.y,
t*seg_vector.y), o)
return distance
raise NotImplementedError()
[docs] def contains(self, other):
"""
Is the other GeometryEntity contained within this Segment?
Examples
========
>>> from sympy import Point3D, Segment3D
>>> p1, p2 = Point3D(0, 1, 1), Point3D(3, 4, 5)
>>> s = Segment3D(p1, p2)
>>> s2 = Segment3D(p2, p1)
>>> s.contains(s2)
True
"""
if is_sequence(other):
other = Point3D(other)
if isinstance(other, Segment3D):
return other.p1 in self and other.p2 in self
elif isinstance(other, Point3D):
if Point3D.are_collinear(self.p1, self.p2, other):
if other.distance(self.p1) + other.distance(self.p2) == self.length:
return True
else:
return False
return False


How the web works
You and your computer connect to the Internet which uses HTTP to connect to servers.
You have to tell the have to tell your computer what you want your website to look like.
Webpages are text documents written is a language called HTML - Hypertext Markup Langauage.
HTML is made up of
We learned a lot about how Markup uses tags, elements, attributes, and sources to create our webpage.
HTML tags are code that describe how a web page is formatted. They are defined by the characters inside a set of brackets. Most tags come in a set of 2, an opening tag < >and a closing tag < / >.
Elements are compiled of opening tags, content and closing tags.
Attributes provide additional information about an element.
Source elements are used to define the media resource for your pictures and videos.
We touched on inline and block tags along with Span and Div elemements but we"ll learn more about those later.4> We also learned that if we can't remember all the tags go to
GOOGLE
HTML documents are made up of more than tags. They contain a head and body sections. The head contains metadata and other random stuff.
The body contains all the actual contents of the document. This diagram shows the structure of an HTML Document.
Boxes - everything on your website will be in a box. You have boxes inside of boxes.
By selecting different attributes of the box you can change how the box looks. It can look like a circle, rectangle or triangle.
CSS styling is what is used to select the color, size and styles of the website. It sets the Font color and size, if text is bold or italic.
It sets the shape and color of objects that are loaded into the webite. This is done using attributes and selectors.
Beware of repetition. Repetition is repeating code in places where it has no meaning/value. This makes it difficult to read and troubleshoot what should actually be happening.
3 things you need to remember when coding:


I'am graduated from vocational scholl in SMK FADILAH Tangerang, majoring in software engineering
Here is some more information about this product that is only revealed once clicked on.
Here is some more information about this product that is only revealed once clicked on.


class: center, middle, inverse, title-slide #
Getting Started in R an introduction to data analysis and visualisation
## Tidy ### Réka Solymosi, Henry Partridge & Sam Langton ### 4 July 2018 --- class: inverse, center, middle ![tidyr](img/tidyr.png) --- ### Tidy data Tidy data are structured for use in R and satisfy three rules: 1. Each variable must have its own column 2. Each observation must have its own row 3. Each value must have its own cell. (Grolemund and Wickham 2017:149) There are two of tidy data formats: wide and long. --- ### Tidy data ![](http://garrettgman.github.io/images/tidy-1.png)<!-- --> [Source: Data Science with R, Garrett Grolemund](http://garrettgman.github.io/tidying/) --- ### Why tidy data? “Tidy datasets are all alike but every messy dataset is messy in its own way.” – Hadley Wickham --- ### Data ```r wide <- data.frame(Date = c("01-01-2017","02-01-2017","03-01-2017"), Burglary = c(7,5,13), Drugs = c(1,3,9), Robbery = c(9,0,9), Shoplifting = c(4,5,1)) wide ``` ``` ## Date Burglary Drugs Robbery Shoplifting ## 1 01-01-2017 7 1 9 4 ## 2 02-01-2017 5 3 0 5 ## 3 03-01-2017 13 9 9 1 ``` --- ### `gather()` For when your columns are values, not variables (wide to long) ```r long <- gather(wide, category, count, -Date) long ``` ``` # Date category count # 1 01-01-2017 Burglary 7 # 2 02-01-2017 Burglary 5 # 3 03-01-2017 Burglary 13 # 4 01-01-2017 Drugs 1 # 5 02-01-2017 Drugs 3 # 6 03-01-2017 Drugs 9 # 7 01-01-2017 Robbery 9 # 8 02-01-2017 Robbery 0 # 9 03-01-2017 Robbery 9 # 10 01-01-2017 Shoplifting 4 # 11 02-01-2017 Shoplifting 5 # 12 03-01-2017 Shoplifting 1 ``` --- ### `spread()` For when observations have multiple rows (long to wide) ```r wide <- spread(long, category, count) wide ``` ``` # Date Burglary Drugs Robbery Shoplifting # 1 01-01-2017 7 1 9 4 # 2 02-01-2017 5 3 0 5 # 3 03-01-2017 13 9 9 1 ``` --- ### `separate()` Split columns ```r split <- separate(wide, Date, c("Day", "Month", "Year"), sep = "-") split ``` ``` # Day Month Year Burglary Drugs Robbery Shoplifting # 1 01 01 2017 7 1 9 4 # 2 02 01 2017 5 3 0 5 # 3 03 01 2017 13 9 9 1 ``` --- ### `unite()` Join columns ```r united <- unite(split, Date, c(Day, Month, Year), sep = "-") united ``` ``` # Date Burglary Drugs Robbery Shoplifting # 1 01-01-2017 7 1 9 4 # 2 02-01-2017 5 3 0 5 # 3 03-01-2017 13 9 9 1 ```


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UKCloud Limited (“UKC”) and Virtual Infrastructure Group Limited (“VIG”) (together “the Companies”) – in Compulsory Liquidation
On 25 October 2022, the Companies were placed into Liquidation with the Official Receiver appointed as Liquidator and J Robinson and A M Hudson simultaneously appointed as Special Managers to manage the liquidation process on behalf of the Official Receiver.
Further information regarding the Liquidations can be found here: https://www.gov.uk/government/news/virtual-infrastructure-group-limited-and-ukcloud-limited-information-for-creditors-and-interested-parties
Contact details:
For any general queries relating to the Liquidations please email<EMAIL_ADDRESS>For customer related queries please email<EMAIL_ADDRESS>For supplier related queries please email<EMAIL_ADDRESS>How to create a service principal name for Azure Stack Hub using the Azure portal
This document explains how to create a service principal name (SPN) to manage Azure and Azure Stack Hub using the Azure portal.
It will guide you through the creation of:
An Azure application
A service principal name
Role assignment
Permissions
What is a service principal name?
An Azure SPN is a security identity used by user-created applications, services, and automation tools to access specific Azure resources. Think of it as a 'user identity' (username and password or certificate) with a specific role, and tightly controlled permissions. It only needs to be able to do specific things, unlike a general user identity. It improves security if you grant it only the minimum permissions level needed to perform its management tasks.
To log in and manage your resources via SPN you'll need to create an Azure application and then assign an SPN to it. Only then will you be able to perform tasks against your environment.
Prerequisites
An active Azure subscription
Create an SPN
Log in to the public Azure portal.
In the favourites panel, select Azure Active Directory.
In the Azure Active Directory blade, select App registrations.
On the App registrations page, click the + New registration button.
In the Register an application blade, enter the following information:
Name - The name of the application. Should have a minimum of four characters.
Supported account types - Lets you decide who can use the service principal.
Redirect URI (optional) - The URL which the authentication response is sent to. In this instance, you can leave it blank.
Click Register.
Gathering SPN credentials
On the blade that has now opened, copy the Application (client) ID and store it somewhere secure. This value is sometimes referred to as the SPN Client ID.
On the blade menu, click the Certificates & secrets button.
Under Client secrets, click the + New client secret button.
Enter a description for the key, select a expiry duration, then click Add.
Copy the displayed value for the key and store it somewhere secure. This value is referred to as the SPN Client Secret.
Important
It is not possible to retrieve the secret value again after navigating away from this screen. Therefore, you should make sure you have taken a copy of it before moving on.
Configure role-based access control for the SPN on Azure Stack Hub
Log in to the UKCloud Azure Stack Hub portal.
For more detailed instructions, see the Getting Started Guide for UKCloud for Microsoft Azure.
Navigate to the resource you want to give the SPN access to. In this example we are adding the SPN to the subscription resource to give it permission to all resources.
View your subscription by clicking All services in the favourites panel, then selecting Subscriptions under the General section.
Select your subscription.
On your subscription's blade, select Access Control (IAM).
On the Access Control (IAM) blade, click the + Add button and then click Add role assignment
Select the role you want to add your SPN to.
Enter the name of the SPN in the Select field, select the SPN when it appears then click Save
The SPN will now have the appropriate permissions assigned to it and is ready for use.
Feedback
If you find a problem with this article, click Improve this Doc to make the change yourself or raise an issue in GitHub. If you have an idea for how we could improve any of our services, send an email to feedback@ukcloud.com.


This wizard will walk you through the process of generating a workable schedule for the NHS blood drive. The generation itself is automated; you merely need to provide inputs and configuration.
To begin, press the Next button under the navigation landmark, then navigate down to the main landmark.


'ZeroMQ' is a well-known library for high-performance asynchronous messaging in scalable, distributed applications. This package provides high level R wrapper functions to easily utilize 'ZeroMQ'. We mainly focus on interactive client/server programming frameworks. For convenience, a minimal 'ZeroMQ' library (4.2.2) is shipped with 'pbdZMQ', which can be used if no system installation of 'ZeroMQ' is available. A few wrapper functions compatible with 'rzmq' are also provided.
| Version: | 0.3-3 |
| Depends: | R (≥ 3.2.0) |
| Published: | 2018-05-05 |
| Author: | Wei-Chen Chen [aut, cre], Drew Schmidt [aut], Christian Heckendorf [aut] (file transfer), George Ostrouchov [aut] (Mac OSX), Whit Armstrong [ctb] (some functions are modified from the rzmq package for backwards compatibility), Brian Ripley [ctb] (C code of shellexec, and Solaris), R Core team [ctb] (some functions are modified from the R source code), Philipp A. [ctb] (Fedora), Elliott Sales de Andrade [ctb] (sprintf), Spencer Aiello [ctb] (windows conf) |
| Maintainer: | Wei-Chen Chen <wccsnow at gmail.com> |
| BugReports: | https://github.com/snoweye/pbdZMQ/issues |
| License: | GPL-3 |
| Copyright: | See files AUTHORS, COPYING, COPYING.LESSER, and MAINTAINERS in 'pbdZMQ/inst/zmq_copyright/' for the 'ZeroMQ' source files in 'src/zmq_src/' which are under GPL-3. |
| URL: | http://r-pbd.org/ |
| NeedsCompilation: | yes |
| SystemRequirements: | Linux, Mac OSX, and Windows, or 'ZeroMQ' library >= 4.0.4. Solaris 10 needs 'ZeroMQ' library 4.0.7 and 'OpenCSW'. |
| Citation: | pbdZMQ citation info |
| Materials: | README ChangeLog INSTALL |
| CRAN checks: | pbdZMQ results |
| Reference manual: | pbdZMQ.pdf |
| Vignettes: |
pbdZMQ-guide |
| Package source: | pbdZMQ_0.3-3.tar.gz |
| Windows binaries: | r-devel: pbdZMQ_0.3-3.zip, r-release: pbdZMQ_0.3-3.zip, r-oldrel: pbdZMQ_0.3-3.zip |
| OS X binaries: | r-release: pbdZMQ_0.3-3.tgz, r-oldrel: pbdZMQ_0.3-3.tgz |
| Old sources: | pbdZMQ archive |
| Reverse depends: | JuniperKernel |
| Reverse imports: | IRkernel, remoter |
| Reverse enhances: | pbdMPI, pbdRPC |
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Download paper here
Simulation study of wave propagation in structures can provide insights for structural health monitoring system design, developing an efficient simulation toolbox for the purpose thus becomes very essential. This paper addresses the practical issue of simulating guided wave propagation in an infinite domain using non-reflective boundary (NRB) techniques, based on the simulation framework of local interaction simulation approach (LISA) that is currently being developed in our lab. Existing NRB methods can be divided into two categories, i.
Download paper here
The acoustic black hole (ABH) effect produces drastic wave compression and energy trapping in thin-walled structures. Recent research has shown that the reflected wave in realistic ABH structures can be reduced by attaching specific wave concentration areas with thin absorbing layer. In this paper, the novel design and implementation of one-dimensional (1D) functionally graded acoustic black hole (FGABH) are presented, as an alternative to achieve low reflection effect.
Download paper here
Recent research has shown that the acoustic black hole (ABH) effect provides wave focalization and dissipation in thin-walled structures. The design and implementation of functionally graded acoustic black hole (FG-ABH) are presented in this work. Two kinds of the FG-ABHs are demonstrated, which are axially graded ABHs and the thickness graded ABHs, respectively. The FG-ABHs are capable to be manufactured by 3D printing tech using the Objet Connex 500 printer.
Download paper here
The paper presents a damage characterization framework based on a simulation library and matching pursuit algorithm to estimate damage features in typical aerospace structures. The large damage database is generated by numeric simulation. The recent development of the University of Michigan’s Local Interaction Simulation Approach (UM/LISA) is an ideal tool for generating such a damage database in a very efficient manner. It includes capability for piezoelectric coupled field simulation, non-reflective boundary techniques, and contact penalty method for nonlinear guided wave simulation, and can execute on multiple-GPU platform for fast computation.
Download paper here
Phased array methods are a promising approach to damage detection by enabling guided wave steering and beam focusing leading to improved localization and sizing of structural damage. Due to the costs and challenges to addressing piezoelectric arrays in parallel, most phased array methods actuate piezoelectric elements one at a time in round-robin fashion with postprocessing algorithms used to synthetically steer and focus the guided waves. In this study, true parallel excitation and sensing of ceramic piezoelectric actuators is implemented in a standard structural health monitoring data acquisition system without requiring highly specialized and expensive ultrasonic data acquisition equipment.
Download paper here
A novel d36-type piezoelectric wafer fabricated from lead magnesium niobate-lead titanate (PMN-PT) is explored for the generation of in-plane horizontal shear waves in plate structures. The study focuses on the development of a linear phased array (PA) of PMN-PT wafers to improve the damage detection capabilities of a structural health monitoring (SHM) system. An attractive property of in-plane horizontal shear waves is that they are nondispersive yet sensitive to damage.
Download paper here
Local interaction simulation approach (LISA) is a highly parallelizable numerical scheme for guided wave simulation in structural health monitoring (SHM). This paper addresses the issue of simulating wave propagation in unbounded domain through the implementation of non-reflective boundary (NRB) in LISA. In this study, two different categories of NRB, i.e., the non-reflective boundary condition (NRBC) and the absorbing boundary layer (ABL), have been investigated in the parallelized LISA scheme.
Download paper here
This paper presents the theoretical formulation and initial experimental investigation of static and dynamic strain sensing using the Composite Long-range Variable-direction Emitting Radar (CLoVER) transducers. CLoVER Transducers are manufactured using the piezoelectric fibers integrated with the interdigitated electrodes with wedge-shaped sectors arranged in a circular way. A coupled-field analytical model was developed based on the piezoelectricity constitutive equations with the consideration of the anisotropic material properties of CLoVER transducers.
To verify and evaluate the performance of a space robot controller, kinematics and dynamics of the system have to be formed beforehand for computer simulation. The paper is devoted to develop a new kinematic notation for space robots and to come up with an open source of Matlab subroutines for the propose of obtaining the proper dynamics equations of space robots in symbolic forms automatically. For the new kinematic notation, we will present the general form and two special cases.


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|
BTK Python wrapper
0.3dev.0
Python bindings for the Biomechanical ToolKit library (BTK)
|
Extracts only the points corresponding to the given type (without cloning the extracted points). More...
Public Member Functions | |
| def | GetInput |
| def | GetInputNumber |
| def | GetOutput |
| def | GetOutputNumber |
| def | GetPointType |
| def | GetTimestamp |
| def | GetValidInputNumber |
| def | ResetState |
| def | SetInput |
| def | SetPointType |
| def | Update |
Extracts only the points corresponding to the given type (without cloning the extracted points).
Extracts only the points corresponding to the given type (without cloning the extracted points). The type is set by the SetPointType() method. By default, if no type is set, this filter extract markers.
| def btk.btkSpecializedPointsExtractor.GetInput | ( | self | ) |
GetInput(self) -> btkAcquisition Gets the input registered with this process.
| def btk.btkSpecializedPointsExtractor.GetInputNumber | ( | self | ) |
GetInputNumber(self) -> int Returns the number of inputs.
| def btk.btkSpecializedPointsExtractor.GetOutput | ( | self | ) |
GetOutput(self) -> btkPointCollection Returns the output created with this process.
| def btk.btkSpecializedPointsExtractor.GetOutputNumber | ( | self | ) |
GetOutputNumber(self) -> int Returns the number of outputs.
| def btk.btkSpecializedPointsExtractor.GetPointType | ( | self | ) |
GetPointType(self) -> btkPoint_impl::Type Returns the type of points to extract.
| def btk.btkSpecializedPointsExtractor.GetTimestamp | ( | self | ) |
GetTimestamp(self) -> unsigned long Returns the timestamp of the object.
| def btk.btkSpecializedPointsExtractor.GetValidInputNumber | ( | self | ) |
GetValidInputNumber(self) -> int Returns the number of inputs which are valid (i.e. not null).
| def btk.btkSpecializedPointsExtractor.ResetState | ( | self | ) |
ResetState(self) Reset the state of the process. Usefull when an exception was thrown during the generation of the data.
| def btk.btkSpecializedPointsExtractor.SetInput | ( | self, | args | ) |
SetInput(self, input) Sets the input required with this process.
| def btk.btkSpecializedPointsExtractor.SetPointType | ( | self, | args | ) |
SetPointType(self, btk.btkPoint.Type) Sets the type of points to extract.
| def btk.btkSpecializedPointsExtractor.Update | ( | self | ) |
Update(self) Update the pipeline and then all the data inside. Recursive method which 1) determines the processes to update 2) generate the data by using the GenerateData() method.


Before Change
for m in range(0, self.img.shape[4]):
shifted_image = []
for n in range(0, self.neigh+1):
new_img = np.multiply(self.seg, self.img[..., m:m+1, 0:1])
new_img = ndimage.shift(new_img, shifts[n], order=0)
if np.count_nonzero(new_img) > 0:
flattened_new = np.flatten(new_img)
flattened_seg = np.flatten(self.seg)
After Change
for n in range(0, self.neigh):
for i in range(0, shifted_image[0].size):
glcm[shifted_image[0][i], shifted_image[n+1][i], n] += 1
glcm[:,:,n] = glcm[:,:,n] / np.sum(glcm[:,:,n])
multi_mod_glcm.append(glcm)
return multi_mod_glcm


You can spot Mexican and Central American immigrants everywhere in New York City. Teenagers guard the outdoor flower displays in front of Korean grocery stores, whose goods mostly come from Colombia, where they leave behind a trail of ecological destruction. If you walk around the West Twenties and Thirties you see Mexican women on their way to sweatshop jobs and on the subways the men are headed to or returning from low-wage construction jobs. They are the fastest-growing group of immigrants in the city right now and have almost no political influence, unlike the comparatively well-organized Dominicans. They are also the poorest.
Young film-maker David Riker made the audacious decision to construct "La Ciudad" (The City) around this population, using a largely unprofessional cast. It is a New York that is invisible in Woody Allen's movies or television shows like "Seinfeld."  His New York is the Bronx, where the stores advertise in Spanish and sell beepers or advice on how to get a green card. Filmed in a gritty black-and-white, the movie consists of street scenes filmed on location of neighborhoods where the average New Yorker, including me, never visits. Riker spent five years from 1992 to 1997 working with this community and gaining their trust. The result is an audacious and powerful film that is clearly in the neo-realist tradition of "The Bicycle Thief."
"La Ciudad" is constructed around four separate stories that are connected together by intermezzi of immigrants being photographed in a studio, posing for a picture that we might assume is being sent home to a loved one. Their faces, like the faces of Riker's cast, express a mixture of uncertainty and hope.
In the first story we follow a group of ten day laborers who are lured into a job that supposedly pays $50 for a day's work, but when they arrive at the site, they discover that instead they will clean individual bricks from a pile of rubble for fifteen cents each. At first they resist, but eventually go about their task. Their anger toward the man who hired them is displaced toward each other.
In the next we meet a young man who has just arrived from Puebla, the most economically devastated state in Mexico. He is trying to find an uncle, but with no success. He wanders the streets of the Bronx until he hears the sounds of Latin music coming from a private party in a dance hall. He crashes the party and strikes up a conversation with a young woman, who is not only from Puebla herself, but the very same town. The possibility for love and economic deliverance in the strange new city turn out to be difficult to achieve.
Then we meet a father and his young daughter who live in their car near the East River. He runs a one-man puppet show on the vacant lots in the neighborhood. At night he reads to her from an illustrated fairy tale and his only hope is to enroll her in a local school. He is ably played by Josť Rabelo, a Cuban-American, and one of the few professional actors in the cast. As I left the theatre, Rabelo was on the sidewalk passing out flyers to help publicize the film. I congratulated him on his performance and took a handful that I will leave around Columbia University. He introduced me to David Riker, who was also on the sidewalk nearby. He mentioned that he is very involved with solidarity efforts in Chiapas and will likely be visiting there in the next few months.
The final vignette is the most effective. It depicts the plight of a young mother who works on a sewing machine in a sweatshop run by a Chinese husband and wife, which actually describes the class demographics at work in New York City today. The workers have not been paid in weeks, but are assured by the bosses that they will get money as soon as they make final delivery on the clothing to a potential customer. In effect, the Latinos have no choice except to take a chance whether they will be paid or not. Like the men cleaning bricks in the first story, the only guarantee is that if they don't work they will starve. The young mother needs to be paid because her daughter needs emergency medical care that costs $400. In the final scene she confronts the bosses and discovers that the class ties that bind her to the rest of the workers in the sweatshop prove decisive.
"La Cidudad" has received positive reviews in the NY Times and Village Voice, which is encouraging. Both of these newspapers thrive on presenting a view of New York that is totally at odds with the one depicted in Riker's film, one that is geared to successful whites looking for an evening's entertainment. Riker's film has an entirely different agenda. The pleasure you receive is in knowing about the full gamut of human experience in one of the worlds' most powerful and wealthy metropolises. By making the invisible visible, Riker has fulfilled one of the greatest demands that can be put on any artist: to tell the truth. "La Ciudad" is playing now at the Quad Cinema on 13th street between 5th and 6th and at the American Museum of the Moving Image in Queens. I strongly urge people to see this film and to spread the word.
--Louis Proyect
(For Marxist discussion: www.panix.com/~lnp3/marxism.html)
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


--- layout: default title: Meeting Minutes ---
This was the flyer from the first infoEnergy meeting
We used to broadcast parts of our meetings and archive basic notes publicly on our google plus page and maybe we will again someday.
March 28, 2014: No Meeting March 14, 2014


Opening a breadboard is very simple. Click on the "File" menu then click on "Open" menu item. Then an open diolog box will appear. Simply navigate to where you saved your breadboard, then double click it. The file was save with a .vbb extention so you can find it easily.


Have you watched all Netflix recommendations already? Then try enjoying the time you have to read on of these cult books that are as good as your series!
FAQ
What if i don't like the books given here?
Luckily there are a lot of books out there that you probably haven't read! You can always let us know the types of books you like and we'll get back to you with some of our favorite recommendations.
I don't want to spend any money on books?
There are lots of ways today that you don't have to spend a lot of money on books. Even if libraries are closed these days Amazon sells second-hand books from 0.98 pounds on already!
GET IN TOUCH
If you would like to share what you have been up to, or submit ideas with a chance of being featured on our website, get in touch with us below.
The Culture Map - Erin Meyer
In a world that is led by different cultures interacting with each other in a business environment, communication is key.
In het book the Culture Map, Erine Meyer helps you navigate the workspace where people from different backgrounds are expected
to work with each other. If you think of it Amercians for example they will usually give some nice comments post a negative one.
Dutch, Germans and Israeli's will go straight to the point however and indicate that was awful. Therefore, even if english is
commonly used there are other factors that are important to succeed in business.
The Four- Scott Halloway
Have you ever wondered how Google, Facebook, Amazon and Apple infiltrated in our lives? Ever thought that instead of going to church
a large number of people ask Google? Than this book is for you! A very intersting view on how they are part of our lives. The book reads
very easily and is comprehensibly written.
Outside Insight: Navigating in a world drawn in data
A book written by Jorn Lyseggen that gives an interesting view on how business should make decison making processes by adapting to a
new digital age. The book contains 17 chapters and is using real time cases to illustrate why business can not solely rely on internal data
and stresses the importance of analysis that contain industry-wide, external data.
 We learn how early memories leave an impact at even a yougn age
and that failure is only a feeling before it actually becomes true:"Failure is a feeling long before it becomes an actual result. It’s
vulnerability that breeds with self-doubt and then is escalated, often deliberately, by fear." Attending Princeton Michelle Obama
often wondered who or what she was representing. She shares with us why she chose to stand by her husband during the presidential
elections even though she was never a fan of politics. A book that shows the strengh and determination of Michelle Obama in her own words,
a book worth reading.


Factions:
Warning
Warning
Nuclear launch detected.
| P |
Fact |
Bid |
2nd |
Harm |
Cost |
FinalCost |
About
This site implements a sealed-bid 'second price' auction to assign a faction and cost to each player. Good luck and have fun!
Game Setup
- Choose factions in game using any method.
- Use winter board with random clearing nations.
- Place factions in random seating order and randomly determine the starting faction.
- Players will know the complete turn order before bidding.
- Deal a hand of 4 cards to each player.
- Bid. Get faction assignments and costs.
- Each player takes their assigned faction board and pieces.
- SUB 30: Subtract your cost (if not 0) from 30 and place your VP marker on that number.
- The first time you would hit 30, go to 0 instead.
- Discard 1 card from each player, facedown to the deck and reshuffle.
- Do faction setup (A/B/C...) Play as usual.


Do you want to delete the role "{{value['rolename']}}"?
Do you want to delete the role "{{value['username']}}"?


&productName; suggests Spring entities when a language is injected (for example, bean names or resource paths).
Click the light bulb icon or press &shortcut:ShowIntentionActions;, choose Inject language or reference, and then select Spring Bean Name:


Snappy Process
We don’t want you worrying about high monthly costs. Our prices may be low,
but we still offer the best coverage possible.
Affordable Prices
Our application process can be completed in minutes, not hours. Don’t get
stuck filling in tedious forms.
People First
Our plans aren’t full of conditions and clauses to prevent payouts. We make
sure you’re covered when you need it.


Create A reply:
content:
userID:
postID:
Read Replies:
ReadAll Replies for a Post:
Delete A Reply:
replyID:
Update A Reply:


Dane County medical examiner identifies victim killed in Beltline crash
by Brandon ArbuckleMADISON, Wis. - The Dane County Medical Examiner's Office has identified the victim killed in a fatal Beltline crash Tuesday.
The news release said Leroy C. Barnes Virghes Jr., 19, of Madison, was pronounced dead at the scene from injuries he suffered in the crash.
The crash happened in the westbound lanes of the 1200 block of Highway 12 in the city of Monona and was reported to officials at around 12:50 p.m. The autopsy was completed Wednesday.
Additional testing is underway, and an investigation is ongoing.


List Pods List Depolyment Kubernetes Web App List services Delete all resources
Output will be shown here ...


A summary contains information about objects in a summarized format. Instead of having data of every object, information are grouped by object type. Each object type is represented by a row, whereas the first column reflects the object type, the second column the number of objects of this type, and the third column the size of all of these objects. The output looks like the following:
| types | # objects | total size |
|---|---|---|
| <type ‘dict’> | 2 | 560 |
| <type ‘str’> | 3 | 126 |
| <type ‘int’> | 4 | 96 |
| <type ‘long’> | 2 | 66 |
| <type ‘list’> | 1 | 40 |


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Post by: Jean-Michel Vilain, Greenhorn
on Sep 20, 2013 20:20:35
This exception:
java.lang.InterruptedException
at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireInterruptibly(AbstractQueuedSynchronizer.java:1219)
at java.util.concurrent.locks.ReentrantLock.lockInterruptibly(ReentrantLock.java:340)
at java.util.concurrent.ArrayBlockingQueue.put(ArrayBlockingQueue.java:321)
at faeria.world.action.WorldScheduler.schedule(WorldScheduler.java:78)
at faeria.game.core.FaeriaGame.run(FaeriaGame.java:131)
at java.lang.Thread.run(Thread.java:724)
My beautifully simple Scheduler's code:
Why? Happens very rarely... Where should I be looking for the cause?
Post by: Steve Luke, Bartender
on Sep 21, 2013 07:00:49
The thread which called the schedule method gets interrupted. We don't have any information about where schedule gets called, or what might be happening in and to that thread, so it is impossible for us to say. If you aren't sure of the sequence then start peppering your code with tons of log statements so you can see exactly the flow and what happens at or around the thread being interrupted.
edit: And remember: the interrupt doesn't have to happen while the put() operation is in progress, it just has to happen some time before the operation and not be cleared (using the Thread#interrupted() method, for example).
Post by: Jean-Michel Vilain, Greenhorn
on Sep 21, 2013 11:11:29
Thanks a lot for your clarifications Steve.
In my mind the put is almost instant so I found it very unlikely to have the thread interrupted right at this moment.
Helps a lot!!
All times above are in ranch (not your local) time.
The current ranch time is Dec 13, 2013 16:40:30.


Preparation time
less than 30 mins
Cooking time
30 mins to 1 hour
Serves
Serves 4
Dietary
A warming bowl of this hearty, healthy soup recipe is filling enough for dinner.
Heat 60ml/2¼fl oz of the oil in a heavy-based pan over a medium heat. Add the onion, garlic and chilli flakes and fry for 2-3 minutes, or until softened.
Add all of the mixed vegetables (except the peas, if using) and the dried mixed herbs to the pan. Season, to taste, with salt and freshly ground black pepper. Fry for 2-3 minutes, or until the vegetables have softened.
Reduce the heat to medium, cover the pan with a lid and continue to fry for 10-15 minutes, stirring regularly, or until the vegetables have softened and are pale golden-brown.
Add the stock, pasta, beans, bay leaves and peas (if using), then bring the mixture to the boil. Return the mixture to a simmer and continue to simmer, covered, for 20-25 minutes, or until the vegetables are tender and the pasta has absorbed some of the liquid and is tender. Remove from the heat and set aside to cool slightly before serving.
Meanwhile, in a bowl, mix together the parmesan, chopped tomatoes and the remaining 30ml/1fl oz of olive oil until well combined.
To serve, spoon the pasta e fagioli into four serving bowls. Spoon over the parmesan and tomato mixture. Season, to taste, with freshly ground black pepper. Drizzle a splash of olive oil over each serving.


Africa is the world's second largest continent covering about over 30 million square kilometers. The Sahara is the largest desert in the world and is bigger than the continental USA.
Africa is home to many of the world's most famous fauna in human culture such as lions‚ rhinos‚ cheetahs‚ giraffes‚ hippos, leopards, zebras‚ African elephants among many others.
African culture is expressed in its arts and crafts, folklore and religion, clothing, cuisine, music and languages. Expressions of culture are abundant within Africa, with large amounts of cultural diversity being found not only across different countries but also within single countries.


As Maha equations change, Raut talks about naya mausam
by PTIAmid the current political stalemate in Maharashtra, Shiv Sena leader Sanjay Raut on Saturday cryptically said the advent of "new weather" is letting him forget "old pain".
Politics in Maharashtra took an unexpected turn after the Shiv Sena walked away from its longtime ally BJP over sharing the chief ministerial post after Assembly results were declared on October 24.
The two parties fell out after having contested the October 21 Assembly polls in alliance coming up with 161 seats together in the 288-member House.
At present, the Shiv Sena is in the process of working out a new equation with erstwhile rivals, NCP and Congress, as it tries to form government in the state.
"Yaaron naye mausam ne ye ahsaan kiya hai. Yaad Mujhe dard purane nahi aate (the new weather has done favour, friends. I do not remember the old pain now)," Raut tweeted the lines of noted Urdu poet Bashir Badr, without naming anyone or any party.
Maharashtra has been under President's rule since November 12 amid an impasse in government formation.


HTML to Temple
Convert HTML snippets to Temple/Elixir code.
HTML
Shorter snippets may be more useful.
Temple
Provided as best effort, applying
mix format
is recommended.
Thank you,
Tree-sitter
,
Tree-sitter HTML
and
Temple
.
See
rktjmp/html-to-temple
, built roughly, adjust expectations accordingly.


Do you remember that guy in Africa which deliver water to animals ? We believe that Blockchain can help people doing similar things.
Birdy is installed in Prague, Czech Republic and it's budget is made up of small voluntary contributions by people which want to support birds in local area.
Birdy's sensor counts birds flying in and uses that number in the smart contract, so your reward is equal to how many birds were attracted by the seeds and grains you brought.
Feeder sends every hour how many birds has visited. Weather information in Prague, where is feeder placed is obtained from Yahoo Wather API. Data are recorded not only on Ethereum Blockchain, but also in Google Spreadsheet.
Please submit UID of RFID card you will use and also Ethereum address on Kovan network where you want to receive reward. You need to have browser extension MetaMask. To get UID of your RFID you can use an Android phone with RFID Reader app.
Feeder runs on board SODAQ ExpLoRer which handles bird counting, connection to the LoRa network, RFID reader and also power management. Feeder is connected to charger every evening and battery is stored in five 18650s.
No one is in charge of the money, the smart contract itself is. Source code can be seen here
Feeder sends its data over LoRa. Connectivity has been kindly supplied by Ceske Radiokomunikace
Birdy is located in Paper Hub. Paper Hub is a Prague-based coworking space for liberal-minded, innovative freelancers and startups interested in decentralization, cryptotechnologies and digital freedom in general. With a coffee bar, hackerspace and a think-tank it makes an "all inclusive package" of Paralelni Polis, the Ztohoven group project.
This project wouldn't be possible without those people.


Neural Computation (2006) 18:245-282
Eugene M. Izhikevich
The Neurosciences Institute,
10640 John Jay Hopkins Drive,
San Diego, CA, 92121.
Abstract. We present a minimal spiking network that can polychronize, i.e., exhibit reproducible time-locked but not synchronous firing patterns with millisecond precision, as in synfire braids. The network consists of cortical spiking neurons with axonal conduction delays and spike-timing-dependent plasticity (STDP); a ready-to-use MATLAB program and C++ program code is included. It exhibits sleep-like oscillations, gamma (40 Hz) rhythms, conversion of firing rates to spike-timings, and other interesting regimes. Due to the interplay between the delays and STDP, the spiking neurons spontaneously self-organize into groups and generate patterns of stereotypical polychronous activity. To our surprise, the number of co-existing polychronous groups far exceeds the number of neurons in the network, resulting in an unprecedented memory capacity of the system. We speculate on the significance of polychrony to the theory of neuronal group selection (TNGS, Neural Darwinism), cognitive neural computations, binding and gamma rhythm, mechanisms of attention, and consciousness as "attention to memories".
Full text in PDF file,
To find polychronous groups, first run spnet.m for sufficiently long period of time and then save the workspace in a file, e.g., write 'save 18000'. Then, use this file name in the program polychron.m to find all groups. Uncomment the line that shuffles excitatory->excitatory connections and run polychron.m again to see how many groups are expected by chance.
For example, the program spnet.m was run for 18000 seconds and the workspace was saved in the file 18000.mat. Then, polychron.m found 1973 groups (only 211 for shuffled synapses). Using less stringent requirement for groups (i.e., setting min_group_path=6 in polychron.m) results in 6071 groups.
Note: The MATLAB and C programs are similar but not equivalent. MATLAB program misses some of the groups.
The quickest way to start is to download polychron.m, polygroup.m, and 18000.mat into the same folder. Then, run polychron.m and enjoy the show.


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When the Flink system is started, it bring up the JobManager and one or more TaskManagers. The JobManager is the coordinator of the Flink system, while the TaskManagers are the worksers that execute parts of the parallel programs. When starting the systen in local mode, a single JobManager and TaskManager are brought up within the same JVM.
When a program is submitted, a client is created that performs the pre-processing and turns the program into the parallel data flow form that is executed by the JobManager and TaskManagers. The figure below illustrates the different actors in the system very coarsely.
An alternative view on the system is given by the stack below. The different layers of the stack build on top of each other and raise the abstraction level of the program representations they accept:
The runtime layer receive a program in the form of a JobGraph. A JobGraph is a generic parallel data flow with arbitrary tasks that consume and produce data streams.
The optimizer and common api layer takes programs in the form of operator DAGs. The operators are specific (e.g., Map, Join, Filter, Reduce, ...), but are data type agnostic. The concrete types and their interaction with the runtime is specified by the higher layers.
The API layer implements multiple APIs that create operator DAGs for their programs. Each API needs to provide utilities (serializers, comparators) that describe the interaction between its data types and the runtime.
The Flink system code is divided into multiple sub-projects. The goal is to reduce the number of dependencies that a project implementing a Flink progam needs, as well as to faciltate easier testing of smaller sub-modules.
The individual projects and their dependencies are shown in the figure below.
In addition to the projects listed in the figure above, Flink currently contains the following sub-projects:
flink-dist
: The distribution project. It defines how to assemble the compiled code, scripts, and other resources
into the final folder structure that is ready to use.
flink-addons
: A series of projects that are in an early version. Currently contains
among other things projects for YARN support, JDBC data sources and sinks, hadoop compatibility,
graph specific operators, and HBase connectors.
flink-quickstart
: Scripts, maven archetypes, and example programs for the quickstarts and tutorials.


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:: com :: sun :: star :: xml :: input ::
|
| unpublished |
interface XRoot |
|
|
|
- Usage Restrictions
- not published
- Description
- Root interface being passed to SaxDocumentHandler service upon
instantiation.
@internal
|
| Methods' Details |
startDocument
- Description
- Receives notification of the beginning of a document.
- Parameter xMapping
- mapping to obtain ids out of XML namespace URIs
and vice versa
|
|
endDocument
- Description
- Receives notification of the end of a document.
|
|
processingInstruction
| void |
| processingInstruction( |
[in] string |
target, |
| [in] string |
data ) |
| raises( |
::com::sun::star::xml::sax::SAXException ); |
- Description
- Receives notification of a processing instruction.
- Parameter target
- target
- Parameter data
- data
|
|
setDocumentLocator
- Description
- Receives an object for locating the origin of SAX document events.
- Parameter locator
- locator
|
|
startRootElement
- Description
- Called upon root element.
- Parameter uid
- namespace uid of element
- Parameter localName
- localname of element
- Parameter xAattributes
- attributes of element
|
|
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Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


dicealyzer.pools.dice module¶
A module to represent dice pools consisting of one type of dice.
-
class
dicealyzer.pools.dice.
DiceTypePool
(sides, amount=1)[source]¶ Bases:
dicealyzer.pools.base.AbstractDicePool
A class to represent a dicepool with multiple of one dice.
-
roll
()[source]¶ Roll the dice in this pool, and return the result. Also returns the values of all rolled dice as a list.
-
property
values
¶ All the possible values that this dice pool can produce, as a set. Ascending order is preferred, but not required.
-
-
class
dicealyzer.pools.dice.
DiceDropPool
(sides, amount=2, drop=1, highest=False)[source]¶ Bases:
dicealyzer.pools.dice.DiceTypePool
A class to represent a dicepool where the lowest or highest dice are dropped.
-
roll
()[source]¶ Roll the dice in this pool, and return the result. Also returns the values of all rolled dice as a list.
-
property
values
¶ All the possible values that this dice pool can produce, as a set. Ascending order is preferred, but not required.
-


Builtin CPOs can be listed with listCPO()
.
NULLCPO
is the neutral element of %>>%
. It is returned by some functions when no other CPO or Retrafo is present.
A simple CPO with one parameter which gets applied to the data as CPO. This is different from a multiplexer in that its parameter is free and can take any value that behaves like a CPO. On the downside, this does not expose the argument’s parameters to the outside.
cpa = cpoWrap()
print(cpa, verbose = TRUE)
head(iris %>>% setHyperPars(cpa, wrap.cpo = cpoScale()))
head(iris %>>% setHyperPars(cpa, wrap.cpo = cpoPca()))
# attaching the cpo applicator to a learner gives this learner a "cpo" hyperparameter
# that can be set to any CPO.
getParamSet(cpoWrap() %>>% makeLearner("classif.logreg"))
Combine many CPOs into one, with an extra selected.cpo
parameter that chooses between them.
cpm = cpoMultiplex(list(cpoScale, cpoPca))
print(cpm, verbose = TRUE)
head(iris %>>% setHyperPars(cpm, selected.cpo = "scale"))
# every CPO's Hyperparameters are exported
head(iris %>>% setHyperPars(cpm, selected.cpo = "scale", scale.center = FALSE))
head(iris %>>% setHyperPars(cpm, selected.cpo = "pca"))
A CPO that builds data-dependent CPO networks. This is a generalized CPO-Multiplexer that takes a function which decides (from the data, and from user-specified hyperparameters) what CPO operation to perform. Besides optional arguments, the used CPO’s Hyperparameters are exported as well. This is a generalization of cpoMultiplex
; however, requires
of the involved parameters are not adjusted, since this is impossible in principle.
s.and.p = cpoCase(pSS(logical.param: logical),
export.cpos = list(cpoScale(),
cpoPca()),
cpo.build = function(data, target, logical.param, scale, pca) {
if (logical.param || mean(data[[1]]) > 10) {
scale %>>% pca
} else {
pca %>>% scale
}
})
print(s.and.p, verbose = TRUE)
The resulting CPO s.and.p
performs scaling and PCA, with the order depending on the parameter logical.param
and on whether the mean of the data’s first column exceeds 10. If either of those is true, the data will be first scaled, then PCA’d, otherwise the order is reversed. The all CPOs listed in .export
are passed to the cpo.build
.
cbind
other CPOs as operation. The cbinder
makes it possible to build DAGs of CPOs that perform different operations on data and paste the results next to each other.
scale = cpoScale(id = "scale")
scale.pca = scale %>>% cpoPca()
cbinder = cpoCbind(scaled = scale, pcad = scale.pca, original = NULLCPO)
# cpoCbind recognises that "scale.scale" happens before "pca.pca" but is also fed to the
# result directly. The summary draws a (crude) ascii-art graph.
print(cbinder, verbose = TRUE)
head(iris %>>% cbinder)
cpoTransformParams
wraps another CPO
and sets some of its hyperparameters to the value of expressions depending on other hyperparameter values. This can be used to make a transformation of parameters similar to the trafo
parameter of a Param
in ParamHelpers
, but it can also be used to set multiple parameters at the same time, depending on a single new parameter.
cpo = cpoTransformParams(cpoPca(), alist(pca.scale = pca.center))
retr = pid.task %>|% setHyperPars(cpo, pca.center = FALSE)
getCPOTrainedState(retr)$control # both 'center' and 'scale' are FALSE
mplx = cpoMultiplex(list(cpoIca(export = "n.comp"), cpoPca(export = "rank")))
!mplx
mtx = cpoTransformParams(mplx, alist(ica.n.comp = comp, pca.rank = comp),
pSS(comp: integer[1, ]), list(comp = 1))
head(iris %>>% setHyperPars(mtx, selected.cpo = "ica", comp = 2))
head(iris %>>% setHyperPars(mtx, selected.cpo = "pca", comp = 3))
Implements the base::scale
function.
Dummy encoding of factorial variables. Optionally uses the first factor as reference variable.
Select to use only certain columns of a dataset. Select by column index, name, or regex pattern.
Drops constant features or numerics, with variable tolerance
Drops unused factors and makes sure prediction data has the same factor levels as training data.
Creates columns indicating missing data. Most useful in combination with cpoCbind.
Apply an univariate function to data columns
Convert (non-numeric) features to numeric
Combine low prevalence factors. Set max.collapsed.class.prevalence
how big the combined factor level may be.
Specify which columns get used, and how they are transformed, using a formula
.
Multiply features to set the maximum absolute value.
There are two general and many specialised imputation CPOs. The general imputation CPOs have parameters that let them use different imputation methods on different columns. They are a thin wrapper around mlr
’s impute()
and reimpute()
functions. The specialised imputation CPOs each implement exactly one imputation method and are closer to the behaviour of typical CPOs.
cpoImpute
and cpoImputeAll
both have parameters very much like impute()
. The latter assumes that all columns of its input is somehow being imputed and can be preprended to a learner to give it the ability to work with missing data. It will, however, throw an error if data is missing after imputation.
impdata %>>% cpoImpute(cols = list(b = imputeMedian())) # NAs remain
impdata %>>% cpoImputeAll(cols = list(b = imputeMedian())) # error, since NAs remain
missing.task = makeRegrTask("missing.task", impdata, target = "b")
# the following gives an error, since 'cpoImpute' does not make sure all missings are removed
# and hence does not add the 'missings' property.
train(cpoImpute(cols = list(a = imputeMedian())) %>>% makeLearner("regr.lm"), missing.task)
There is one for each imputation method.
There is one general and many specialised feature filtering CPOs. The general filtering CPO, cpoFilterFeatures
, is a thin wrapper around filterFeatures
and takes the filtering method as its argument. The specialised CPOs each call a specific filtering method.
Most arguments of filterFeatures
are reflected in the CPOs. The exceptions being: 1. for filterFeatures
, the filter method arguments are given in a list filter.args
, instead of in ...
2. The argument fval
was dropped for the specialised filter CPOs. 3. The argument mandatory.feat
was dropped. Use affect.*
parameters to prevent features from being filtered.


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