6. Best Practices¶
6.1. Errors and uncertainties¶
There are several sources of errors that are often observed in CFD simulations. These include:
The model is described by the Navier-Stokes equations. The exact N-S equations are solved when Direct Numerical Simulations (DNS) are employed. However, when the RANS approach is involved, as in HydroUQ, this involves approximations that could lead to errors and uncertainties. Thus, selecting the correct parameters is paramount.
If the solution shows divergence, check the boundary conditions, grid, discretization, and convergence errors. Check whether the flow is steady or unsteady and the timestep used in this regard.
6.2. Froude number¶
One of the essential non-dimensional numbers that describe different flow regimes for open channel flow. It is a dimensionless quantity that is a ratio of the inertial and gravitational forces as \(Fr = \frac{V}{\sqrt{gD}}\). Here
V
is the water velocity,D
is the hydraulic depth across the cross-sectional area of the flow, andg
is the gravity.It is important to calculate if the flow is sub-critical (Fr < 1) or critical (Fr = 1) or supercritical (Fr > 1). Critical flows are often unstable and set up standing waves between sub and supercritical flows.
It is necessary to consider both the Froude number and Reynolds number to determine separation effects like breaking waves.
6.3. Spatial discretization¶
Mesh checking is always essential. HydroUQ app performs a mesh check, and the log is available for review after the simulation is complete. It is much recommended to review this.
Mesh convergence study is critical to ensuring good and reliable results using CFD simulations. Thus, it is strongly recommended to estimate the error by refining the mesh, if possible.
Using a fine grid throughout may reduce the convergence rate. Instead, use grid adaptation or refine the mesh in areas of a large gradient to reduce computational cost. Use grid refinement where local details are required.
HydroUQ app has a basic mesher available that generates hex grids. For complex geometries, it is recommended to create hybrid grids using external meshing tools. Such grids can generally use prism layer grids in the boundary layer, tetrahedral cells in the core flow region, and hex grids.
It is recommended that the aspect ratio be below 5 but can be up to 10 inside the boundary layer. Ensure that the change in grid size is gradual, and the maximum variation in grid spacing should be less than 20%.
# Avoid highly skewed cells so that the angles between gridlines are orthogonal or near orthogonal. Angles with less than 40-degrees or greater than 140-degrees may lead to numerical instabilities or unsatisfactory results.
6.4. Temporal discretization¶
It is suggested to take a small timestep to start with so that it can be automatically increased to check the influence of timesteps on the results.
The timestep size should be decided based on the Courant-Friedrichs-Lewy (CFL) condition . Yet, it should also be small enough to capture any transient phenomena of interest.
Using the log files, ensure that the simulation has converged at each time step. For temporal accuracy, it is recommended to use a second-order accurate discretization scheme like Crank-Nicolson.
6.5. Boundary conditions¶
The
EVT
requires one to provide six boundary conditions for the six standard patchesEntry
,Exit
,Right
,Left
,Bottom
andTop
.If no boundary condition is specified for a particular patch, it is assumed to be
type: empty
by default. Presently, HydroUQ app only allows specification of the velocity and pressure boundary conditions. If you would like to specify other parameters, please write to us at Bugs & Feature Requests.The inlet boundary condition should be used for patches where it has a weak influence on the downstream flow. Perform a sensitivity analysis on the inlet flow direction, magnitude, and profile. The exact inlet turbulence conditions are usually unknown. Thus, 1% turbulent intensity can be assumed for external flows.
The outlet boundary condition should be specified on the patch, which has a weak influence on the upstream flow. It is suggested to set the convective derivative normal to the outlet boundary face to be zero. However, for flow with strong pressure gradients, special non-reflecting boundary conditions would be required.
Ensure that the wall boundary conditions are specified for the solid walls.
6.6. SW-CFD domain sizes¶
Note that each degree of latitude is approximately 69 miles (111 km apart). At the Equator, the distance is 68.703 miles (110.567 km); at Tropic of Cancer and Capricorn, it is 68.94 miles (110.948 km), and at the poles, it is 69.94 miles (111.699 km).
60 minutes = 1 degree
For a 1-minute grid used in the SW-solver, this is approximately a 2 x 2 km grid (in terms of distances). This could still be a considerably large domain for the CFD simulation, depending on the topography and bathymetry.
If the simulation type is SW-CFD coupling, then there can be wave reflections. Such wave reflections can lead to unphysical fluid accumulation at the boundary.
6.7. Turbulence modeling¶
Compute the Reynolds number to determine if the flow is turbulent. Do not use turbulent models for laminar flows.
Estimate the y+ and the thickness of the first cell layer. The ideal distance of the first node from the wall \(\Delta y\) can be estimated to be
(6.7.1)¶\[\Delta y = L \cdot y^{+} \cdot \sqrt{74} \cdot {Re}_{L}^{-13/14}\]
where \(L\) is the characteristic length scale, \(y^{+}\) is the desired values, \({Re}_{L}\) is the Reynolds number. The non-dimensionalized velocity (\(u^{+}\)) and distance from the wall (\(y^{+}\)), the velocity profile of the boundary layers, takes on the form, as shown below by the red line in Fig. 6.7.1.
Various online calculators can be used to calculate the value of \(y^{+}\). Some examples of apps include: Google Play Store or Apple store .
If the flow is believed to be viscous, then the viscous sub-layers need to be resolved as shown in Fig. 6.7.2. When meshed correctly, a value of \(y^{+} \approx 1\) is desired. Alternatively, a wall model can be used bu having the first element in the region \(y^{+} > 30\). It is a good practice to avoid a \(y^{+}\) value between these values.
High Reynolds number flows (like aircraft, ships, etc.) will experience boundary layers that extend to several thousand \(y^{+}\) units. However, for flows with low Reynolds numbers, the upper limit can be as little as 100 \(y^{+}\) units. Thus, it is necessary to ensure that the first node does not fall outside this range.
HydroUQ app 1.0 supports \(k-\epsilon\) and \(k-\omega\) SST models. These are both good choices for general applications. The \(k-\epsilon\) model is very reliable and can often be used to get initial values for more sophisticated models.
The \(k-\epsilon\) model is inaccurate for flows with adverse pressure gradients. It does not allow integration of the conservation equations through the viscous sublayer where low Reynolds number corrections are recommended.
The \(k-\omega\) model is very sensitive to the freestream boundary conditions. However, it performs well for flows with variable pressure gradients.
6.8. User errors¶
Check for details in the geometry. Do not over-simplify the geometry without an understanding of the given problem.
Inaccurate use of boundary conditions, poor-quality grids are commonly observed user errors.
Ensure that the timestep sizes provided are reasonable.
6.9. Checking results¶
Check the overall mass balance.
Check whether the values and distribution of values of velocities, forces, and pressures are realistic.
Perform simple hand calculations in a smaller number of grids to check the orders of magnitude of variables. Alternatively, compare with similar problems or simplified versions of the same problem.
Perform a sensitivity analysis by changing the grid size, effects of boundary conditions, and turbulence models.


domestic | environment | ventilation | 2010
Every
building
must be designed and
constructed
in such a way that
ventilation is provided so that the air quality inside the
building
is not
a threat to the
building
or the health of the occupants.
3.14.0 Introduction
Ventilation of a
dwelling
is required to maintain air quality and so contribute to
the health and comfort of the occupants. Without ventilation it is possible that
carbon dioxide, water vapour, organic impurities, smoking, fumes and gases
could reduce the air quality by humidity, dust and odours and also reduce the
or live in.
Well designed natural ventilation has many benefits, not least financial and
environmental, although it is also recognised that inside air quality can only
be as good as outside air quality and in some cases filtration may be
necessary. In other cases mechanical systems or systems that combine
natural with mechanical (hybrid) may provide the ventilation solution for the
Ventilation can also have a significant affect on energy consumption and
performance and so thorough assessment of natural, as against mechanical
ventilation, should be made, as the decision could significantly affect the
energy efficiency of the
building
(see section 6, Energy).
Ventilation should not adversely affect comfort and, where necessary,
designers might wish to consider security issues and protection against rain
penetration prevalent in naturally ventilated
buildings
when windows are
partially open to provide background ventilation.
Reducing air infiltration
Improved insulation and ‘tighter’
construction
of
buildings
will reduce the
number of natural air changes but can increase the risk of condensation.
However leaky
buildings
are draughty and uncomfortable. Sealing up air
leaks improves comfort and saves energy whilst proper ventilation keeps the
indoor air pleasant and healthy. If poor attention to detail occurs air leakage
can account for a substantial part of the heating costs. Energy savings from
building
‘tighter’ could make significant savings on energy bills. There is a
common perception that ‘tight’
construction
promotes indoor air pollution.
However both ‘tight’ and 'leaky'
buildings
can have air quality
problems. Though air leaks can dilute indoor pollutants, there is no control
over how much leakage occurs, when it occurs or where it comes from. BRE
GBG 67, ‘Achieving air tightness: General principles’ provides useful
BR GBG 67
Occupants should have the opportunity to dry washing other than by a
tumble dryer which uses a considerable amount of energy. Drying of
washing internally can generate large quantities of moisture that should be
removed before it damages the
building.
In the case of
conversions,
as specified in regulation 4, the
building
as
converted
shall meet the requirement of this standard (regulation 12,
schedule 6).
3.14
—
3.14.0
domestic | environment | ventilation | 2010
3.14.1 Ventilation generally
A
dwelling
should have provision for ventilation by either:
a. natural means; or
b. mechanical means; or
c. a combination of natural and mechanical means (mixed-mode).
Ventilation is the process of supplying outdoor air to an enclosed space and
removing stale air from the space. It can manage the indoor air quality by
both diluting the indoor air with less contaminated outdoor air and removing
the indoor contaminants with the exhaust air. Ventilation should have the
capacity to:
•
provide outside air to maintain indoor air quality sufficient for human
respiration;
•
remove excess water vapour from areas where it is produced in sufficient
quantities in order to reduce the likelihood of creating conditions that
support the germination and growth of mould, harmful bacteria, pathogens
and allergies;
•
remove pollutants that are a hazard to health from areas where they are
produced in significant quantities;
•
rapidly dilute pollutant odours, where necessary.
Additional ventilation
provision
This guidance relates to the provision of air for human respiration and is in
addition to, and should be kept separate from, any air supply needed for the
smoke ventilation of
escape routes
in the case of fire (section 2, Fire) and for
the safe operation of combustion appliances (see standards 3.21 and 3.22).
Small
rooms
There is no need to ventilate a
room
with a floor area of not more than
4 m².This is not intended to include a kitchen or utility
room
where ventilation
should be in accordance with the recommendations in table to clause 3.14.2.
Ventilation should be to the outside air. However clauses 3.14.5 and 3.14.7
explain where
ventilators
and
trickle ventilators
may be installed other than to
the external air.
Calculation of volume
For ventilation purposes, a
storey
should be taken as the total floor area of all
floor. Where an air change rate is recommended, the volume of the space to
be ventilated may be required. The volume of any space is the internal cubic
capacity of the space. Any volume more than 3 m above any floor level in
that space may be disregarded.
3.14.2 Ventilation of dwellings
All
buildings
leak air to a greater or lesser extent. However the movement of
uncontrolled infiltrating air through the fabric of a
building
can cause draughts
and can have a significant adverse effect on the energy efficiency of the
reduce this infiltrating air to lower levels that can improve energy efficiency
(see section 6, Energy).
Some
building
techniques may have little effect on air leakage and so allow
the uncontrolled infiltrating air to be taken into account in the
building's
ventilation provision. By
building
with techniques designed to reduce air
leakage there will need to be a reciprocal increase in the designed ventilation
provision to make up for the lower levels of infiltrating air.
3.14.1
—
3.14.2
domestic | environment | ventilation | 2010
Recommendations for trickle ventilation in the table below are made on the
basis that infiltrating air rates of 5 to 10 m
3
/h/m
2
@ 50 Pa will be achieved as
a matter of course in modern
dwellings
. However where the designer intends
to use low fabric infiltration air rates of less than 5 m
3
/h/m
2
@ 50 Pa in the
SAP calculations (see section 6 Energy) the areas of trickle ventilation shown
may not suffice to maintain air quality and therefore an alternative ventilation
solution should be adopted (see clause 3.14.10).
Recommended ventilation of a dwelling
Ventilation recommendations
Trickle
ventilation [1]
12,000 mm
2
either:
mechanical extraction capable
of at least 30 l/sec (intermittent)
above a hob [3]; or
mechanical extraction capable
of at least 60 l/sec (intermittent)
if elsewhere [3]; or
a passive stack ventilation
system [4].
10,000 mm
2
a.
b.
c.
Utility
room
either:
mechanical extraction capable
of at least 30 l/sec (intermittent)
[3]; or
a passive stack ventilation
system [4].
10,000 mm
2
a.
b.
either:
mechanical extraction capable
of at least 15 l/sec (intermittent);
or
a passive stack ventilation
system [4].
10,000 mm
2
a.
b.
either:
a
ventilator
with an opening area
of at least 1/30
th
of the floor area
it serves; or
mechanical extraction capable
of at least 3 air changes per hour.
10,000 mm
2
a.
b.
Notes:
1. Where the
trickle ventilator
is
ducted
, the recommended areas in the table
should be doubled (see clause 3.14.5).
2. The overall provision of trickle ventilation in a
dwelling
may be provided at
an average of 11,000 mm
2
each
apartment
.
3. Refer to guidance to standard 3.17 and OFTEC Technical Book 3 where
an extract fan is fitted in a
building
containing an
open-flued
combustion
appliance. Extract rates should be reduced.
4. Refer to section 2: Fire where a passive stack ventilation system is
3.14.2
—
3.14.2
domestic | environment | ventilation | 2010
installed in a
building
containing
flats and maisonettes.
and should be carefully considered during design.
Work on existing
often be the case in existing
buildings
, the size of
trickle ventilation
may be
Alternatively, the overall provision of
trickle ventilation
in a
dwelling
may be
provided at an average of 6000 mm
2
per
room
, with a minimum provision of
Height of
ventilator
To reduce the effects of stratification of the air in a
room,
some part of the
opening
ventilator
should be at least 1.75 m above floor level.
3.14.3 Ventilation of conservatories
With large areas of
glazing
,
conservatories
attract large amounts of the sun’s
radiation that can create unacceptable heat build-up. Efficient ventilation
therefore is very important to ensure a comfortable environment. A
conservatory
should have a
ventilator
or
ventilators
with an opening area of
at least 1/5
th
of the floor area it serves. Although this is the minimum
recommended area, a greater area can provide more comfortable conditions
particularly in sunny weather. Notwithstanding the recommended opening
height of 1.75 m for
ventilators
, high level or roof vents are best placed to
minimise the effects of heat build-up and reduce stratification.
3.14.4 Ventilation of areas designated for drying of washing
Where clothes are dried naturally indoors large quantities of moisture can be
released and this will need to be removed before it can damage the
building
.
Normally a utility
room
or bathroom is used and mechanical extract is the
usual method of removing moisture. Where a space other than a utility
room
or bathroom is designated, that space should be provided with either:
•
mechanical extraction capable of at least 15 l/s intermittent operation. The
fan should be connected through a humidistat set to activate when the
relative humidity is between 50 and 65%; or
•
a passive stack ventilation system provided in accordance with the
recommendations in clause 3.14.6.
Guidance to standard 3.11 gives information on the space recommended for
the drying of washing.
3.14.5 Trickle ventilators
A
trickle ventilator
, sometimes called 'background ventilation', is a small
ventilation opening, mostly provided in the head of a window frame, but not
always, and is normally provided with a controllable shutter. They should be
provided in naturally ventilated areas to allow fine control of air
movement. The area recommendations in the table to clause 3.14.2 may, in
some situations, be difficult to achieve in the window frame and other options
may need to be considered. A
permanent ventilator
is not recommended
since occupants like control over their environment and uncontrollable
ventilators
are usually permanently sealed up to prevent draughts.
Because
dwellings
produce so many variables and differing life styles,
ventilation of such
buildings
is not an exact science. The recommended
areas in the table to clause 3.14.2 therefore are based on the geometric
method (actual size of the opening formed in the window frame, in the case
of a slot vent) as being a simple method that will satisfy most conditions.
3.14.2
—
3.14.5
domestic | environment | ventilation | 2010
Where the
trickle ventilator
has to be
ducted
, e.g. to an internal
room
, the
geometric area of the
trickle ventilator
should be increased to double that
shown in the table to clause 3.14.2, to compensate for the reduced air flow
caused by friction. This may over-provide ventilation in some cases but can
be regulated by the fine control.
Non-proprietary
trickle
Fitting proprietary
trickle ventilators
is the preferred method of fine tuning
room
ventilation. However in some cases it may be acceptable for
background ventilation to be provided through small windows, such as top
hoppers, but other issues need to be considered if this method is to be
adopted:
•
a partially open window on a night latch is a possible point of forced entry
to a
dwelling
even when the window is locked in position and because of
this it is less likely to be left open at night or when the
dwelling
is empty,
even for short periods. Small, upper floor windows in a well lit, open
location that are difficult to access may be appropriate;
•
it tends to be windier where
flats
and
maisonettes
are at high level and
windows on night latches do not have fine adjustment to reduce draughts.
They are therefore more likely to be kept closed;
•
manufacturers will need to show that the opening area when on the night
latch is to the recommended sizes in the table to clause 3.14.2;
•
some windows might be too small to incorporate the recommended size of
trickle ventilator
in the frame and careful thought will need to be given to
the design and location of
trickle ventilators
in the window itself or
additional
trickle ventilators
through the
external wall
;
•
trickle ventilators
supply replacement air for mechanical extract and
passive stack ventilation systems and routes for extracting air provided by
mechanical input air systems. It is recommended that proprietary
trickle
ventilators
are used in
rooms
where such systems are installed since it is
more likely that they, rather than windows, will be left open.
Height of
trickle
A
trickle ventilator
should be so positioned that a part of it is at least 1.75 m
above floor level. This will allow at least some movement of air within the
dwelling
and reduce stratification.
Although ventilation should normally be to the external air, a
trickle ventilator
serving a bathroom or shower
room
may open into an area that does not
generate moisture, such as a bedroom or hallway, provided the area is fitted
with a
trickle ventilator
in accordance with the guidance in clause 3.14.2. In
these cases, noise transmission may need to be limited, see section 5.
A
trickle ventilator
should be provided in an area fitted with mechanical
extraction to provide replacement air and ensure efficient operation when
doors are closed. This will prevent moist air being pulled from other ‘wet
areas’. The
trickle ventilator
should be independent of the mechanical extract
so that replacement air can be provided when the extract fan is operating.
Consideration should be given to the location of the
ventilator
and the fan so
as to prevent short-circuiting of the air.
3.14.6 Passive stack ventilation systems
A passive stack ventilation system uses a
duct
running from a ceiling
any moisture-laden air. It operates by a combination of natural stack effect,
i.e. the movement of air due to the difference in temperature between inside
and outside temperatures and the effect of wind passing over the roof of the
building
.
3.14.5
—
3.14.6
domestic | environment | ventilation | 2010
A passive stack ventilation system should be installed in full compliance with
BRE Information Paper BRE IP 13/94. These systems are most suited for
maximum length of stack) as the stack effect will diminish as the air cools.
Every passive stack ventilation system should:
a. incorporate a ceiling mounted automatic humidity sensitive extract grille
that will operate when the relative humidity is between 50 and 65%; and
b. be insulated with at least 25 mm thick material having a thermal
conductivity of 0.04 W/mK where it passes through a
roof space
or other
unheated space or where it extends above the roof level. This will prevent
the walls of the
duct
from becoming too cold thus inhibiting the stack effect
and reducing the likelihood of condensation forming inside the
duct
.
stack ventilation system provided that either:
a. the appliance is a solid fuel appliance and is the primary source of
heating, cooking or hot water production; or
and the appliance's combustion air inlet and dilution air inlet are
permanently open, i.e. there is a path with no control dampers which could
block the flow, or the ventilation path can be left open when the appliance
is not in use; or
c. the appliance is an oil firing appliance which is a continually burning
vapourising appliance (only) such as a cooker or
room
heater and the
should be
non-combustible
. However this is not necessary where it passes
through a
roof space
.
3.14.7 Conservatories and extensions built over existing windows
Constructing
a
conservatory
or extension over an existing window, or
ventilator
, will effectively result in an internal
room
, restrict air movement and
could significantly reduce natural ventilation to that
room
. Reference should
be made to clause 3.16.2 relating to natural lighting, and to the guidance to
standards 3.21 and 3.22 on the ventilation of combustion appliances, as this
also may be relevant. There are other recommendations in section 2: Fire
relating to escape from
inner rooms
.
A
conservatory
may be
constructed
over a
ventilator
serving a
room
in a
dwelling
provided that the ventilation of the
conservatory
is to the outside air
and has an opening area of at least 1/30
th
of the total combined floor area of
the internal
room
so formed and the
conservatory
. The
ventilator
to the
of the
room
.
Trickle ventilators
should also be provided relevant to the overall
areas created.
Extensions
An extension may also be built over a
ventilator
but a new
ventilator
should
be provided to the
room
. Where this is not practicable, e.g. where there is no
external wall
, the new extension should be treated as part of the existing
extension will be more airtight than a
conservatory
and therefore the rate of
air change will be compromised. The opening area between the 2 parts of the
room
and the extension.
3.14.6
—
3.14.7
domestic | environment | ventilation | 2010
Moisture-producing
areas
If the
conservatory
or extension is
constructed
over an area that generates
mechanical extract, via a
duct
if necessary, or a passive stack ventilation
system should be provided direct to the outside air. Any existing system
disadvantaged by the
work
may require to be altered to ensure supply and
extracted air is still to the outside air.
3.14.8 Mechanical ventilation
Where a
dwelling
is mechanically ventilated it should be provided in
accordance with the recommendations of Section 3, Requirements of CIBSE
Guide B2: 2001, Ventilation and air conditioning.
Mechanical ventilation provided in line with this guidance should be to the
outside air but it may be via a
duct
or heat exchanger.
Where a mechanical ventilation system serves more than 1
dwelling
it should
have a duplicate motor and be separate from any other ventilation system
installed for any other purpose. Where the mechanical ventilation system
gathers extracts into a common
duct
for discharge to an outlet, no
connections to the system should be made between any exhaust fan and the
outlet. The use of non-return valves is not recommended.
Open-
flued
appliances
Care should be taken when installing mechanical extract systems where
guidance is provided in clause 3.17.8.
3.14.9 Control of legionellosis
An inlet to, and an outlet from, a mechanical ventilation system should be
installed such that their positioning avoids the contamination of the air supply
to the system. The system should be
constructed
and installed in accordance
with the recommendations in Legionnaires' Disease: The control of
legionnella bacteria in water systems – approved code of practice and
guidance - HSE L8, in order to ensure, as far as is
reasonably practicable
,
the avoidance of contamination by legionalla.
3.14.10 Mechanical ventilation and systems
A mechanical ventilation system should be designed, installed and
commissioned to perform in a way that is not detrimental to the health of the
occupants of the
building
and when necessary, is easily accessible for
regular maintenance. Very few
dwellings
are air-conditioned but the use of
continuously operated balanced supply and extract mechanical ventilation
systems and of heat recovery units are becoming more popular as a result of
the need to conserve energy and reduce greenhouse gas emissions. As
buildings
are
constructed
to lower infiltration rates, mechanical ventilation
may be necessary to deliver the effective ventilation needed to provide a
healthy living environment.
Simpler and more efficient systems are steadily being introduced that
augment, complement and/or improve the natural ventilation of
such a system should be used. The following are examples of mechanical
systems that will aid ventilation in a
dwelling
:
MVHR
a. continuously operating balanced supply and extract mechanical ventilation
systems. When combined with heat recovery these installations are
known as Mechanical Ventilation and Heat Recovery (MVHR) systems.
Installations should be in accordance with the guidance in BRE Digest
3.14.7
—
3.14.10
domestic | environment | ventilation | 2010
398. In hot weather windows can be opened to cool the
dwelling
while the
system is operating. Openable windows may also be needed for fire
escape purposes;
b. continuously operating mechanical extract ventilation installed in
accordance with the guidance in BRE Digest 398;
c. mechanical extract ventilation units (extract fans), either window or wall
mounted, in
rooms
where there is likely to be high humidity such as
recommendations in clause 3.14.2. Fans can be switched manually or
automatically via a humidistat control. Humidistat control is not
recommended for
rooms
containing a watercloset as odours may not be
removed.
Positive input systems
Mechanical input air ventilation systems have been successfully installed in
existing
dwellings
with the objective of overcoming problems of surface
condensation and mould growth. They can also improve air quality and
remove musty odours. The general principle of
building
tighter to reduce the
amount of uncontrolled air movement through the
building
fabric may have a
detrimental effect on the operation of input air ventilation systems and
therefore they may not be appropriate for installation in new
dwellings
.
Further information should be obtained from the product manufacturer.
•
In
houses
air is supplied to the hall via a low speed fan unit located in the
roof space
where it is allowed to circulate throughout the
house
before
being extracted to the outside normally through the
building
fabric or
•
In
flats
and
maisonettes
the air is drawn direct from the outside through
the fan unit before being discharged into the
dwelling
. The air supplied will
normally have a lower relative humidity than the air in the
dwelling
thus
removing harmful surface condensation and eliminating mould growth.
•
Where an input ventilation is proposed it should be installed in accordance
with the 'conditions of certification by a notified body'.
3.14.11 Ventilation of garages
The principal reason for ventilating garages is to protect the
building
users
from the harmful effects of toxic emissions from vehicle exhausts. Where a
garage is attached to a
dwelling
, the separating
construction
should be as air
tight as possible. Where there is a communicating door airtight seals should
be provided or a lobby arrangement may be appropriate.
Large garages
such structures is provided in the non-domestic Technical Handbook.
Small garages
Garages of less than 30 m
2
do not require the ventilation to be designed. It is
expected that a degree of fortuitous ventilation is created by the imperfect fit
of ‘up and over’ doors or pass doors. With such garages, it is inadvisable for
designers to attempt to achieve an airtight
construction
.
Open-
flued
appliances
Although not considered good practice, open-
flued
combustion appliances
are installed in garages. Ventilation should be provided in accordance with
the guidance to standards 3.21 and 3.22.
A garage with a floor area of at least 30 m
2
but not more than 60 m
2
used for
the parking of motor vehicles should have provision for natural or mechanical
ventilation. Ventilation should be provided in accordance with the following
guidance:
Natural ventilation
a. where the garage is naturally ventilated, by providing at least 2
permanent
3.14.10
—
3.14.11
domestic | environment | ventilation | 2010
they serve, positioned to encourage through ventilation with one of the
permanent ventilators
being not more than 600 mm above floor level; or
Mechanical ventilation
b. where the garage is mechanically ventilated, by providing a system:
•
capable of continuous operation, designed to provide at least 2 air
changes per hour; and
•
independent of any other ventilation system; and
•
constructed
so that two-thirds of the exhaust air is extracted from
outlets not more than 600 mm above floor level.
3.14.11
—
3.14.11


Saint Altar:
The Altar of Saints reacts to the Blood of Saint. You're starting to feel better. The altar appears depleted. It's time to move on.


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View the code Grid (generated with generate-grid mixin - see the documentation on SASS Framework - Mixins Subsection)
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Grid Cell Content
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Grid Cell Content
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Grid Cell Content
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Grid Cell Content
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Grid Cell Content
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Grid Cell Content
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Grid Cell Content
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Grid Cell Content
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View the code Section
Section Content -
View the code IT Products
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View the code Section Variations
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Free (without Margins) Section Content
-
Padded Section Content
-
Vertical Section Content
-
Horizontal Section Content
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Left Section Content
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Right Section Content
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Top Section Content
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Bottom Section Content
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Full-Width Section Content - use it when you want a full-width (100%) section
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Tesco selling fleece bedding this winter for just £6
This will definitely keep you toasty on those frost nights
by Rebecca CarterTesco is selling fleece bedding for just £6 to keep you warm over the winter months.
As frosty nights kick in, the supermarket has unveiled it has dropped the price on the Silentnight teddy fleece bedding sets from £25 to just £6.25 for a single.
One shopper shared a photo of the bedding on offer to Facebook page Extreme Couponing and Bargains UK at one store and people can't get enough.
Read more: You can now buy heated underwear to keep you warm this winter
The shopper wrote: "Tesco in Oxford don't know if its all Tesco."
One person commented: "Oh wow," while another said: "Wish they had these in Tesco's in Scotland... need them this time of year!"
A third gushed: "If it’s in my Tesco I’m getting one!" followed by heart eyes emojis.
The description of the bedding says on the Tesco website: "The Silentnight Teddy Fleece Duvet set is perfect for those colder months as you snuggle up in bed.
"The super cosy style provides ultimate warmth and comfort to your bed. The soft fluffy textured fabric is beautifully crafted from soft touch polyester making it warm and inviting for those cosy nights in."
Last month, we revealed that B&M is selling glow-in-the-dark fleece bedding.
The product comes in three different designs including a pink one covered in unicorns, a grey one, and a navy one both covered in stars.
The sets cost £15 and includes a duvet cover and a pillow case.
The website says: "Make bedtime a magical time for children with this cosy faux fur duvet set.
"Wool-like, sherpa fabric offers a luxuriously soft feel while the duvet's reverse features fleece material, keeping kids warm and snuggly on chilly nights."
Read more: M&S shoppers delighted by Snow Globe Clementine Gin for Christmas
And bedding isn't the only thing that can keep you warm this winter.
Earlier this week, we revealed that Amazon sells heated underwear to keep you cosy.
Smart Heated Panties aren't exactly the most attractive knickers in the world, but they will definitely keep you toasty over the next few months.
The undies are £41, high-waisted and have a 12-hour life span on the "winter warmer" setting. Oh yes!
Leave us a comment on our Facebook page @EntertainmentDailyFix and let us know what you think of this story.


| DOSE: |
52 tablets |
oral |
DXM |
(pill / tablet) |
[Erowid Warning: Most Coricidin contains CPM (Chlorpheniramine Maleate) which can be dangerous in high doses. See DXM Brand Warnings for more info.]
One night I was trying to commit suicide so I took 52 pills of Coricidin Cough & Cold tablets. Anyway, I took these pills and passed out.  We decided to set up a session that afternoon.  They freaked out and called the hospital and got me a room in behavioral medicine (like a mental hospital). I was the second time I had been there.
Well, anyway, they took my blood, then made me pee in a cup. I kept having to talk with my psychiatrists medical assistant, staff, and my therapist there because they thought I took PCP. I kept telling them NO I've never took PCP in my life. So, after telling everyone that, they had to do a little research of their own. My therapist had to call a Drug Specialist and ask if DXM can show up as PCP in drug tests. He said that if DXM is taken in large doses it definitely can show up as PCP.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Library: Algorithms
Function
An algorithm that removes consecutive duplicates from a range of values and places the resulting unique values into the result
#include <algorithm> namespace std { template<class ForwardIterator> ForwardIterator unique(ForwardIterator start, ForwardIterator finish); template<class ForwardIterator, class BinaryPredicate> ForwardIterator unique(ForwardIterator start, ForwardIterator finish, BinaryPredicate binary_pred); template<class InputIterator, class OutputIterator> OutputIterator unique_copy(InputIterator start, InputIterator finish, OutputIterator result); template <class InputIterator, class OutputIterator, class BinaryPredicate> OutputIterator unique_copy(InputIterator start, InputIterator finish, OutputIterator result, BinaryPredicate binary_pred); }
The unique() algorithm moves through a sequence and eliminates all but the first element from every consecutive group of equal elements. There are two versions of the algorithm -- one that tests for equality and a second that tests adjacent elements against a binary predicate. An element is unique if it does not meet the corresponding condition listed here:
*i == *(i - 1)
or
binary_pred(*i, *(i - 1)) == true.
If an element is unique, it is copied to the front of the sequence, overwriting the existing elements. Once all unique elements have been identified. The remainder of the sequence is left unchanged, and unique() returns the end of the resulting range.
The unique_copy() algorithm copies the first element from every consecutive group of equal elements to an output iterator. The unique_copy() algorithm also has two versions -- one that tests for equality and a second that tests adjacent elements against a binary predicate.
unique_copy() returns the end of the resulting range.
For unique_copy(), exactly (finish - start) - 1 applications of the corresponding predicate are performed.
// // unique.cpp // #include <algorithm> #include <vector> #include <iostream> typedef std::vector<int, std::allocator<int> > vector_t; typedef std::insert_iterator<vector_t > v_iter_t; typedef std::ostream_iterator<int, char, std::char_traits<char> > os_iter_t; int main () { // Initialize two vectors. int a1[20] = {4, 5, 5, 9, -1, -1, -1, 3, 7, 5, 5, 5, 6, 7, 7, 7, 4, 2, 1, 1}; vector_t v(a1+0, a1+20), result; // Create an insert_iterator for results. v_iter_t ins (result, result.begin ()); // Demonstrate includes. std::cout << "The vector: " << std::endl << " "; std::copy (v.begin (), v.end (), os_iter_t (std::cout, " ")); // Find the unique elements. std::unique_copy(v.begin(), v.end(), ins); // Display the results. std::cout << std::endl << std::endl << "Has the following unique elements:" << std::endl << " "; std::copy (result.begin (), result.end (), os_iter_t (std::cout, " ")); std::cout << std::endl; return 0; } Program Output:
The vector: 4 5 5 9 -1 -1 -1 3 7 5 5 5 6 7 7 7 4 2 1 1 Has the following unique elements: 4 5 9 -1 3 7 5 6 7 4 2 1
ISO/IEC 14882:1998 -- International Standard for Information Systems -- Programming Language C++, Section 25.2.8


The Montage toolkit provides a broad array of tools for manipulating astronomical images and in particular supports mapping between projections and coordinate systems, background matching within a set of overlapping images, and mosaicking of large numbers of images into a single view. The Montage mViewer module makes it easy to visualize these images and associated spatial data.
|
The documentation menu on the left provides details on how to use mViewer in different environments:
|


Before Change
from distutils.core import setup
setup(name="hyper-tools",
version="1.1",
py_modules=["plot_coords", "hyperalign"],
install_requires=["numpy", "scipy", "matplotlib", "seaborn", "scikit-learn"]
)
After Change
from setuptools import setup, find_packages
with open("readme.md") as f:
readme = f.read()
// NEED TO ADD IN LICENSE
with open("LICENSE") as f:
license = f.read()
setup(
name="hypertools",
version="1.0.0",
description="Python package for manipulating and visualizing high dimensional data",
long_description=readme,
author="Contextual Dynamics Lab",
<EMAIL_ADDRESS>url="https://github.com/ContextLab/pyfingerprint",
license=license,
packages=find_packages(exclude=("tests", "docs", "examples"))
)


{% extends "global/Page.html" %} {% load otree static %} {% block title %} Results {% endblock %} {% block content %}
| You contributed: | {{ player.contribution }} |
| Other participants contributed: | |
| {{ p.contribution }} | |
| Total contribution: | {{ group.total_contribution }} |
| Total earnings from the project: | {{ total_earnings }} |
| Your earnings from the project: | {{ group.individual_share }} |
| Thus in total you earned: | {{ player.payoff }} |


Wednesday, March 12, 2008
1:00pm-2:30pm
Location: 4-149
Resumes, CVs, and Cover Letters...what are the most effective ways to use these tools to get noticed by the most selective employers in today's industry? What is involved in writing a cover letter that stands out? Please bring two copies of your resume/CV and cover letter as well as a job description. Be prepared to participate and practice!
Status: Space Available
Registration for this workshop requires an MIT account. Please visit the the MIT Careers Office Workshops page (web.mit.edu/career/www/events/ workshops.html) from a desktop or laptop computer to register.


Morten Høfft
I am a software developer who love machine learning, JavaScript and computer vision. Besides my master I have a bachelor in philosophy and a bachelor in architecture. Say Hello.
This site
This site works as documentation and motivation to complete undertakings, which previously have had a tendency to get lost over time. It is first and foremost for learning and the joy of it, but some projects might turn out to have the interest of other people.
I tried to keep things simple and spent little time on frameworks and design. It seemed overkill to spent time on a beautiful production line when I - as of writing this - have no content. The blue color is lifted of Coderwall. The navigation bar is inspired by the Cicero blog theme. The header by the magazine Nautilus.


Visao is a technologically equipped white cane that uses the latest sensor and GPS technology to support the visually impaired in addressing the problem of independent navigation and location positioning in the event of ‘getting lost’. We value customer safety and therefore provide an additional feature called Visao Plus which is a cane with the facility of the sensor as well as a GPS tracker. This tracker has an SOS button incorporated on the cane, which sends the location of the user to the three pre registered family members in case of emergency.
Our vision is to serve the visually impaired by making them independent while still retaining the support and confidence of their family.
Our mission is to maximise the lives of the visually - impaired by developing a hi- tech cane incorporating the very latest GPS and sensor technologies.
Ayswarya Salil - Managing Director Contact : +447821712020
Shikha Singh - Marketing Contact : +447823712012
Vivek Gupta - Operations Contact : +447840121035
Sumukh Chhabria - Sales Contact : +447438027868
Adrian Arionovici - Finance Contact : +447496657335
+44<PHONE_NUMBER> / +44<PHONE_NUMBER>


Once we are confident in our hypothesis, we can export this code into backtesting. One way to accomodate this model into research is to create a scheduled event which uses our model to pick stocks and goes long.
private List<string> _asset = new List<string>{"SHY", "TLT", "IEI", "SHV", "TLH", "EDV", "BIL", "SPTL", "TBT", "TMF", "TMV", "TBF", "VGSH", "VGIT", "VGLT", "SCHO", "SCHR", "SPTS", "GOVT"}; public override void Initialize() { // 1. Required: Five years of backtest history SetStartDate(2014, 1, 1); // 2. Required: Alpha Streams Models: SetBrokerageModel(BrokerageName.AlphaStreams); // 3. Required: Significant AUM Capacity SetCash(1000000); // 4. Required: Benchmark to SPY SetBenchmark("SPY"); SetPortfolioConstruction(new InsightWeightingPortfolioConstructionModel()); SetExecution(new ImmediateExecutionModel()); // Add Equity ------------------------------------------------ foreach(var ticker in _asset) { AddEquity(ticker, Resolution.Minute); } // Set Scheduled Event Method For Our Model Schedule.On(DateRules.EveryDay(), TimeRules.BeforeMarketClose("SHY", 5), EveryDayBeforeMarketClose); }
def Initialize(self) -> None: #1. Required: Five years of backtest history self.SetStartDate(2014, 1, 1) #2. Required: Alpha Streams Models: self.SetBrokerageModel(BrokerageName.AlphaStreams) #3. Required: Significant AUM Capacity self.SetCash(1000000) #4. Required: Benchmark to SPY self.SetBenchmark("SPY") self.SetPortfolioConstruction(InsightWeightingPortfolioConstructionModel()) self.SetExecution(ImmediateExecutionModel()) self.assets = ["SHY", "TLT", "IEI", "SHV", "TLH", "EDV", "BIL", "SPTL", "TBT", "TMF", "TMV", "TBF", "VGSH", "VGIT", "VGLT", "SCHO", "SCHR", "SPTS", "GOVT"] # Add Equity ------------------------------------------------ for i in range(len(self.assets)): self.AddEquity(self.assets[i], Resolution.Minute) # Set Scheduled Event Method For Our Model self.Schedule.On(self.DateRules.EveryDay(), self.TimeRules.BeforeMarketClose("SHY", 5), self.EveryDayBeforeMarketClose)
Now we export our model into the scheduled event method. We will remove qb
and replace methods with their QCAlgorithm
counterparts as needed. In this example, this is not an issue because all the methods we used in research also exist in QCAlgorithm
.
Now we export our model into the scheduled event method. We will switch qb
with self
and replace methods with their QCAlgorithm
counterparts as needed. In this example, this is not an issue because all the methods we used in research also exist in QCAlgorithm
.
private void EveryDayBeforeMarketClose() { // Fetch history on our universe var history = History(Securities.Keys, 30, Resolution.Daily); if (history.Count() < 0) return; // Extract close prices for each Symbol from Slice data var closes = new Dictionary<Symbol, List<Decimal>>(); foreach(var slice in history){ foreach(var symbol in slice.Keys){ if(!closes.ContainsKey(symbol)){ closes.Add(symbol, new List<Decimal>()); } closes[symbol].Add(slice.Bars[symbol].Close); } } // Get the 30-day rolling mean, standard deviation series, z-score and filtration for each Symbol var rollingMean = new Dictionary<string, double>(); var rollingStd = new Dictionary<string, double>(); var filter = new Dictionary<string, bool>(); var zScore = new Dictionary<string, double>(); foreach(var kvp in closes) { var symbol = kvp.Key; if(!rollingMean.ContainsKey(symbol)){ rollingMean.Add(symbol, decimal.ToDouble(kvp.Value.Average())); rollingStd.Add(symbol, Math.Sqrt(kvp.Value.Average(v => Math.Pow(decimal.ToDouble(v-kvp.Value.Average()), 2)))); zScore.Add(symbol, (decimal.ToDouble(kvp.Value.Last()) - rollingMean[symbol]) / rollingStd[symbol]); filter.Add(symbol, zScore[symbol] < -1); } } // Calculate the expected return and its probability, then calculate the weight var magnitude = new Dictionary<Symbol, double>(); var confidence = new Dictionary<Symbol, double>(); var weights = new Dictionary<Symbol, double>(); foreach(var kvp in rollingMean) { var symbol = kvp.Key; if(!magnitude.ContainsKey(symbol)){ magnitude.Add(symbol, -zScore[symbol] * rollingStd[symbol] / decimal.ToDouble(closes[symbol].Last())); confidence.Add(symbol, Normal.CDF(0, 1, -zScore[symbol])); // Filter if trade or not var trade = filter[symbol] ? 1d : 0d; weights.Add(symbol, trade * Math.Max(confidence[symbol] - 1 / (magnitude[symbol] + 1), 0)); } } // Normalize the weights, then emit insights var sum = weights.Sum(x => x.Value); if (sum == 0) return; foreach(var kvp in weights) { var symbol = kvp.Key; weights[symbol] = kvp.Value / sum; var insight = new Insight(symbol, TimeSpan.FromDays(1), InsightType.Price, InsightDirection.Up, magnitude[symbol], confidence[symbol], null, weights[symbol]); EmitInsights(insight); } }
def EveryDayBeforeMarketClose(self) -> None: qb = self # Fetch history on our universe df = qb.History(qb.Securities.Keys, 30, Resolution.Daily) if df.empty: return # Make all of them into a single time index. df = df.close.unstack(level=0) # Calculate the truth value of the most recent price being less than 1 std away from the mean classifier = df.le(df.mean().subtract(df.std())).iloc[-1] if not classifier.any(): return # Get the z-score for the True values, then compute the expected return and probability z_score = df.apply(zscore)[[classifier.index[i] for i in range(classifier.size) if classifier.iloc[i]]] magnitude = -z_score * df.std() / df confidence = (-z_score).apply(norm.cdf) # Get the latest values magnitude = magnitude.iloc[-1].fillna(0) confidence = confidence.iloc[-1].fillna(0) # Get the weights, then zip together to iterate over later weight = confidence - 1 / (magnitude + 1) weight = weight[weight > 0].fillna(0) sum_ = np.sum(weight) if sum_ > 0: weight = (weight) / sum_ selected = zip(weight.index, magnitude, confidence, weight) else: return # ============================== insights = [] for symbol, magnitude, confidence, weight in selected: insights.append( Insight.Price(symbol, timedelta(days=1), InsightDirection.Up, magnitude, confidence, None, weight) ) self.EmitInsights(insights)


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Greetings! I live in Westlake with my husband and rambunctious cat name Clemmie. To keep myself out of trouble, I work at CWRU in the social work library. I like to read, do Zumba and yoga, and explore Cleveland neighborhoods during my free time.


|
Contiki 2.5
|
This file contains the USB endpoint 0 management routines corresponding to the standard enumeration process (refer to chapter 9 of the USB specification. This file calls routines of the usb_specific_request.c file for non-standard request management. The enumeration parameters (descriptor tables) are contained in the usb_descriptors.c file. More...
Go to the source code of this file.
Defines | |
| #define | Is_device_enumerated() ((usb_configuration_nb!=0) ? TRUE : FALSE) |
| Returns true when device connected and correctly enumerated with an host. | |
Functions | |
| void | usb_process_request (void) |
| usb_process_request. |
This file contains the USB endpoint 0 management routines corresponding to the standard enumeration process (refer to chapter 9 of the USB specification. This file calls routines of the usb_specific_request.c file for non-standard request management. The enumeration parameters (descriptor tables) are contained in the usb_descriptors.c file.
*************************************************
Definition in file usb_standard_request.h.
| #define Is_device_enumerated | ( | ) | ((usb_configuration_nb!=0) ? TRUE : FALSE) |
Returns true when device connected and correctly enumerated with an host.
The device high level application should tests this before performing any applicative requests
Definition at line 78 of file usb_standard_request.h.
Referenced by PROCESS_THREAD(), and usb_eth_send().
| void usb_process_request | ( | void | ) |
usb_process_request.
This function reads the SETUP request sent to the default control endpoint and calls the appropriate function. When exiting of the usb_read_request function, the device is ready to manage the next request.
< un-supported request => call to user read request
Definition at line 118 of file usb_standard_request.c.
References CLEAR_FEATURE, Is_usb_receive_setup, SET_FEATURE, Usb_ack_in_ready, Usb_ack_receive_out, Usb_ack_receive_setup, Usb_enable_stall_handshake, Usb_read_byte, Usb_select_endpoint, and usb_user_read_request().
Referenced by usb_mass_storage_csw().


Summary
Describes how spatial region boundaries are handled.
Description
The golden rule for spatial region filtering was first enunciated by
Leon VanSpeybroeck in 1986:
Each photon will be counted once, and no photon will be counted
more than once.
This means that we must be careful about boundary conditions. For
example, if a circle is contained in an annulus such that the inner
radius of the annulus is the same as the radius of the circle, then
photons on that boundary must always be assigned to one or the other
region. That is, the number of photons in both regions must equal the
sum of the number of photons in each region taken separately.
With this in mind, the rules for determining whether a boundary image
pixel or table row are assigned to a region are defined below.
Image boundaries : radially-symmetric shapes (circle, annuli, ellipse)
or image filtering, pixels whose center is inside the boundary are
included. This also applies non-radially-symmetric shapes. When a
pixel center is exactly on the boundary, the pixel assignment rule is:
- the outer boundary of a symmetric shape does not include such pixels
- the inner boundary of a symmetric shape (annulus) includes such pixels
In this way, an annulus with radius from 0 to 1, centered exactly on a
pixel, includes the pixel on which it is centered, but none of its
neighbors.
These rules ensure that when defining concentric shapes, no pixels are
omitted between concentric regions and no pixels are claimed by two
regions. When applied to small symmetric shapes, the shape is less
likely to be skewed, as would happen with non-radially-symmetric
rules. These rules differ from the rules for box-like shapes, which
are more likely to be positioned adjacent to one another.
Image Boundaries: non-radially symmetric shapes (polygons, boxes)
For image filtering, pixels whose center is inside the boundary are
included. This also applies radially-symmetric shapes. When a pixel
center is exactly on the boundary of a non-radially symmetric region,
the pixel is included in the right or upper region, but not the left
or lower region. This ensures that geometrically adjoining regions
touch but don't overlap.
Other pages of interest:
Last updated: August 7, 2015


Brewers trade Anderson, Thames becomes free agent
by Stephanie OlsonMILWAUKEE - The Milwaukee Brewers are making some roster moves.
Pitcher Chase Anderson has been traded to Toronto in exchange for infielder Chad Spanberger.
The crew has exercised the 2020 club option for catcher Manny Pina and declined Eric Thames' club option.
Thames will now become a free agent.
Good news for Milwaukee, as the team has reinstated pitcher Corey Knebel and Bobby Wahl from the 60-day injury list.
Knebel missed all of the 2019 season after having Tommy John surgery.


having met with distinction the high standards of education,experience and demonstrated knoledge established by the Global Innovation Institute (GInI), has been certified as a


Red Wings assign Smith to Grand Rapids
DETROIT (AP) - The Detroit Red Wings have removed forward Givani Smith from injured reserve and assigned him to Grand Rapids of the AHL.
The Red Wings announced the move Friday.
The 21-year-old Smith has appeared in five games with the Red Wings this season. He also has three goals and four assists in 10 games for Grand Rapids.
Smith was a second-round draft pick by the Red Wings in 2016.
The Red Wings play at New Jersey on Saturday night.
More AP NHL: https://apnews.com/NHL and https://twitter.com/AP_Sports
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Copyright © 2019 The Washington Times, LLC.
Please read our comment policy before commenting.


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Encrypt-it is a simple program to encrypt and decrypt messages in the browser.
NCAWQM-5MVSPN-GJ3IX6-HNMCVM-ZN3EC6-3PNDOL-ROCK


Welcome to three-particle !
Click below links to view demo
Based on three.js and three-particle.js,
you only need to add several lines of code to implement these effects.
{{demo.url}}


curtains.js
easy WebGL tool to animate images and videos
What is it ?
Shaders are the new front-end web development big thing, with the ability to create very powerful 3D interactions and animations. A lot of very good javascript libraries already handle WebGL but with most of them it's kind of a headache to position your meshes relative to the DOM elements of your web page.
curtains.js was created with just that issue in mind. It is a small vanilla WebGL javascript library that converts HTML elements containing images, videos and canvases into 3D WebGL textured planes, allowing you to animate them via shaders.
You can define each plane size and position via CSS, which makes it super easy to add WebGL responsive planes all over your pages.
You can also add post processing effects to your scene to spice up the whole thing.
Be sure to check the documentation and examples to see what's possible.
Examples
All the examples are fully commented: do not hesitate to have a look at the source code.
Images
Vertex coordinates helper
Plane properties and transformations cheat sheet
Simple plane
Slideshow with a displacement shader
Multiple planes
Multiple planes scroll effect : rotation, scale and parallax
Asynchronous textures loading
AJAX navigation with plane removal
Videos
Simple video plane
Multiple video textures with a displacement shader
Canvas
Simple canvas plane
Text planes using canvas
Post processing
Post processing displacement effect
Post processing multiple passes
Post processing scrolling wheel with custom transform origin
Advanced render targets usage
Ping pong shading / FBOs swapping flowmap example
Selective shader passes using render targets
GSAP click to fullscreen gallery
Custom scroll
Knowledge and technical requirements
It is easy to use but you will of course have to possess good basics of HTML, CSS and javascript.
If you've never heard about shaders, you may want to learn a bit more about them on The Book of Shaders for example. You will have to understand what are the vertex and fragment shaders, the use of uniforms as well as the GLSL syntax basics.
Installation
Using npm:
Load ES modules:
See the documentation for a complete list of all classes availables.
In a browser, you can use the UMD files located in the 'dist' directory:
Usage with React & Vue
Note that if you are using React or Vue, you might want to try react-curtains or vue-curtains, curtains.js official React and Vue packages.
About
This library is released under the MIT license which means it is free to use for personnal and commercial projects.
All images used in the examples were taken by Marion Bornaz during the Mirage Festival.
All examples video footages were shot by Analogue Production.
Many thanks to webglfundamentals.org tutorials which helped me a lot.
Author of this library is Martin Laxenaire, a french creative front-end developper based in Lyon.
Found a bug ? Have questions ? Do not hesitate to email me, fill an issue on Github or send me a tweet : @webdesign_ml.
Showcase
Here you'll find websites that use curtains.js with their own custom shaders. You can also check all the Awwwards' submitted websites using it.


Little Flash Charges In 40 Seconds Thanks To Super Capacitors
by Gerrit CoetzeeWe’ve all committed the sin of making a little arduino robot and running it off AA batteries. Little Flash is better than that and runs off three 350 F capacitors.
In fact, that’s the entire mission of the robot. [Mike Rigsby] wants people to know there’s a better way. What’s really cool is that 10 A for 40 seconds lets the robot run for over 25 minutes!
The robot itself is really simple. The case is 3D printed with an eye towards simplicity. The brains are an Arduino nano and the primary input is a bump sensor. The robot runs around randomly, but avoids getting stuck with the classic reverse-and-turn on collision.
It’s cool to see how far these capacitors have come. We remember people wondering about these high priced specialty parts when they first dropped on the hobby scene, but they’re becoming more and more prevalent compared to other solutions such as coin-cells and solder tab lithium batteries for PCB power solutions.
The HackadayPrize2019 is Sponsored by:


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outdated or invalid links, or to change their order.


Diacritícál
Bahá’í Term Suggestion Script
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Suggestion Report for "Dawn-Breakers"
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--- layout: default footerlogos: yes title: "Agenda – Day 2" lang: en ---
29.4.2017
Saturday at betahaus
The second day is our community day, which means we would like to include all of you: our OK-lab members, NGO representatives, and public administrators.
We will have lectures on current political implications, judicial obstacles and data lessons learned. Workshops will focus on election and public transport data, Wikidata, uncovering money flows and a design consulting crash course, as well as a window of opportunity to tackle any issues you can think of in our Barcamps.
Registration starts at 10, the program will start at 11.
Transparency in public expenditure data substantially increases a politician’s accountability. In their workshop, Anna Alberts and Michael Peters will show you their newly restructured platform OffenerHaushalt.de. Using exemplary data we will interactively visualize spending data.
For whom:everyone
Form: Workshop
Necessities: Notebook if available
Topic: Fiscal data, Transparency
The OK Lab Stuttgart with their citizen science project luftdaten.info is dedicated to measuring fine dust and will install self-made sensors on the back of the building. The sensor generates data for luftdaten.info and produces an automatized map for the entire region. This way fine dust can be made visible. Everyone can participate and Jan Lutz will show you how. We want to have as many sensors as possible in Germany and all over the World.
For whom: everyone
Form: Workshop
Necessities: Nothing. Assembly kits will be provided.
Topic: Civic Tech, Environment
How is data actually created? How does a physical event translate into an electronic number? And how can we use this to discover our environment? These are the questions that Maximilian Voigt will tackle together with you, while also building a measurement station detecting the “work atmosphere”. This will be achieved using a microcontroller with sensors and should enable you to collect data yourself after the workshop.
For whom:everyone with an interest in electronics
Form: Workshop
Necessities: Notebook
Topic: Electronics, Physical Computing
…or analysis and visualization using digital humanities tools.
Open data does not only work for numbers and tables, but can also be used for evaluating text in a structuralized way. Using online-tools from the digital humanities Markus Neuschäfer will experiment by analyzing and visualizing texts.
For whom: everyone
Form: Workshop
Necessities: Notebook
Topic: Digital Humanities, Text Analysis, Visualization
Discover the powerful query tool of Wikidata! With a few lines of SPARQL, you can browse any information contained in Wikidata, create wonderful list such as the list of inventors killed by their own inventions, or the list of the biggest cities having female mayors. Build maps, graphs, and other datavisualizations based on open knowledge.
For whom: developers
Form: Workshop
Necessities: Notebook
Topic: Wikidata, SPARQL, Datavis
TBD: a storytelling workshop to focusing on your own Open Data projects; a election data workshop, that aims to convene and foster all projects regarding the upcoming general election in Germany and a a data journalism workshop.
Schools are institutions where social transformation occurs. How the German School of Data
collected data on over 30.000 schools from 16 federal states and what should be considered
regarding digital projects in the field of education will be discussed in our workshop. After
mentioning the lessons learned we want to hear your input on how data can make the educational system more transparent.
For whom: everyone
Form: Project Presentation & Discussion
Necessities: Nichts.
Topic: Open Data, Data Literacy, Education
Using the freedom of information (FOI) for your political work! The freedom of information act enables all citizens in Germany the right to request documents such as treaties, correspondences and certificates from the government. Arne Semsrott. will illustrate how you can use these tools to start campaigns and involve followers.
For whom: everyone
Form: Lecture / Workshop
Necessities: Notebook
Topic: Freedom of Information, Transparency, Politics
Bring your own data! You want to start your own digital project, but aren’t sure how? In the data clinic sponsored by our Datenschule Team (school of data) we offer consulting on how to plan your project, discover interesting datasets and offer an ethical handling of information in our digital world.
For whom: NGOs
Form: Consulting
Necessities: Datasets, Ideas, Questions
Topic: Data Literacy
Deutsche Bahn Open Data answers all your questions regarding already open datasets such as our railroad network, Stuttgart 21 geodata or other datasets of interest.
You are missing something in our program and want to start your own Barcamp? Great. Do not hesitate and plan one now. You do not know what a Barcamp is? Click here for an explanation.
At 7 PM we will open the gates to our courtyard and turn the music on. Nonetheless, continuous hacking is encouraged.


SPAD Simulation
Recovery time =
Photon rate =
Threshold voltage =
Recovery Time = The time that it takes for the avalanche diode to recharge into its original state
Photon rate = The number of incident photons per unit time
Threshold voltage = The threshold voltage of the digital buffer connected to the avalanche diode's output
Run = continuous run
Single = single step run
Join = join CH1 and CH2 traces
Split = split CH1 and CH2 traces
CH1 = Channel 1 connected to the output of avalanche diode showing an analog output
CH2 = Channel 2 connected to the output of the digital buffer showing an digital output
See the Github repository for the detail
Danial Chitnis 2020 copyright MIT license


|
Function argument checking. There are three methods of argument checking:
Type 0
Don't do any argument checking. This speeds up the code but corrupted parameters would not be detected and could crash the system. This is only recommandet for well tested embedded systems.
Type 1
Do a minimum set of argument checking. For example, NULL pointers will be detected. This is recommanded for a release version of the operating system.
Type 2
Do the full set of argument checking, including magic number tests in internal data structures. This is the recommanded setting for a debug version of the operating system.
|


2 references to CombineVariableWithPartialPath
System.Management.Automation (2)
engine\CommandCompletion\CompletionAnalysis.cs (1)
1859
? CompletionCompleters.
CombineVariableWithPartialPath
(
engine\CommandCompletion\CompletionCompleters.cs (1)
6992
string strValue =
CombineVariableWithPartialPath
(variableAst, null, executionContext);


On this page:
To read messages in the Chat Room:
Chat Room
. You will
enter the default room (as specified by the site leader). To change
rooms, click Change Room
at the top, and select the room you'd
like to enter.
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Only
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Date nor Time
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All Messages
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history
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, you will
see only messages posted after you made this selection.)
To post a message:
Chat Room
.
Add message
.
Note: No one can see your message
until you click Add message
, but once you do, only an
instructor or a participant with special permission can delete your
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Clear
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To delete a Chat Room message that you have sufficient permission
to delete, click the trash can icon next to the posting, and
then click Delete
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Note: If you don't see a trash can icon, you don't have permission to delete the message.
To permanently delete all messages from a chat room, click
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. Click
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to confirm.


Cacti - T. pachanoi
As I have had a difficult time finding experiences of people trying mescaline whilst taking antidepressants I have decided to write this.
Doses
nortiptyline :20 mg (daily)
mescaline :approx Ĺ trip
(based on a 75cm piece of san pedro 10 cm in diameter containing 4 trips)
We started the day by preparing the pedro. First we removed the husks and cut off all the green slime. This was then boiled for approximately 4 hrs stirring occasionally. The mixture was then strained through a cloth and the liquid was divided between the 4 of us. I had read about the additive effect of tricyclics on hallucinogenic drugs so I only wanted to at the most take Ĺ a trip on this occasion.
It was my 20th birthday and I was in a pretty excited but nervous state of mind. I wondered if it would end up turning out bad (mabey ending up in hospital) but I felt safe in the fact that I had my friends to look after me if anything went wrong. At the same time I thought that hallucinogenic drugs were probably talked up quite a bit but if they werenít I'd have a blast. It was a party atmosphere where my friends were drinking and having a fun time.
(time 0) I decided to only take ľ of a trip (just to be safe) and drank the vile tasting liquid (not as bad as I had been told though) in several goes. I then walked round the house to wait for it to start to kick in.
(time 45 mins) A short time after I had taken it I felt quite queasy, I had sensations that my body was heavy and things just didnít feel quite right. The only time I have felt this feeling before is when I was put on a new prescription medication and they were non-compatible. After 10 mins or so this sensation had left me apart from things not feeling quite right (probably the drug starting to kick in).
(time 1 hr) Nothing much had happened to this point,I was starting to think I had been screwed. I had seen an aura behind one of my friends but that was all.
(time 1 Ĺ hrs) I decided that if it was going to kick in it would have kicked in by then so I took the other ľ of my trip and then ate a few spoons full of cookies (cookies are the pulp left in the muslin after straining) and played the waiting game.
(time 2hrs) The trip had now kicked in. I was running round the house yelling and screaming about stuff (like distorted reflections in a window) and I was unable to stop laughing. I would see something,and in my mind it was the most hilarious thing that I had ever seen. I was almost rolling round on the floor because things were so funny. Not many visual effect to this point though.
(time rest of trip) After the uncontrollable laughing stopped I started to get quite cool visual effects. These included, my shoes talking to each other (one was happy one was angry), having posters winking at me, running through a forest of trees with facial expressions (while I was sitting on the couch), seeing Diablo and seeing a blue tunnel that wanted me to walk down it when I closed my eyes or hid under a blanket (it protected me from the outside world the blanket that is).
In general my experience was far more intense than any of my friends who took full trips. They didnít get anywhere near as intense hallucinations as I did. But they did get some mild effects.
This experience has changed my life. I didnít know that anything could be as intense or as funny as that. I had my best birthday to date (and probably forever) and it will never be forgotten.
Note To Reader:
This was just my own personal experience and there was nothing scientific(or medical) about the above experience. I am only writing this to show people who are on tricyclics to be careful when trying hallucinogenic drugs.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Replication
Moped has full support for replica sets including automatic failover and node discovery.
Automatic Failover
Moped will automatically retry lost connections and attempt to detect dead connections before sending an operation. Note, that it will not retry individual operations! For example, these cases will work and not raise any exceptions:
session[:users].insert(name: "John") # kill primary node and promote secondary session[:users].insert(name: "John") session[:users].find.count # => 2.0 # primary node drops our connection session[:users].insert(name: "John")
However, you'll get an operation error in a case like:
# primary node goes down while reading the reply session.with(safe: true)[:users].insert(name: "John")
And you'll get a connection error in a case like:
# primary node goes down, no new primary available yet session[:users].insert(name: "John")
If your session is running with eventual consistency, read operations will never raise connection errors as long as any secondary or primary node is running. The only case where you'll see a connection failure is if a node goes down while attempting to retrieve more results from a cursor, because cursors are tied to individual nodes.
When two attempts to connect to a node fail, it will be marked as down.
This removes it from the list of available nodes for
:down_interval
(default 30 seconds). Note that the
:down_interval
only applies to normal operations; that is,
if you ask for a primary node and none is available, all nodes will be
retried. Likewise, if you ask for a secondary node, and no secondary
or primary node is available, all nodes will be retreied.
Node Discovery
The addresses you pass into your session are used as seeds for setting up replica set connections. After connection, each seed node will return a list of other known nodes which will be added to the set.
This information is cached according to the :refresh_interval
option (default: 5 minutes). That means, e.g., that if you add a new node
to your replica set, it should be represented in Moped within 5 minutes.


Moving coil actuators are often called electrodynamic actuators and a proportional behaviour between force and current is expressed by a converter constant (see ConstantActuator). However, in a simple moving coil actuator as presented in this example there is an additional non-linear force component that is due to the increase of the inductance when the armature coil moves into the ferromagnetic stator. A simple PermeanceActuator can be used to describe this non-linear force component.
| Name | Description |
|---|---|
| ForceCurrentBehaviour | Comparison of the force-current characteristics of both converter models with armature blocked at mid-position |
| ForceStrokeBehaviour | Force-stroke characteristic of the permeance model at constant current |
| ArmatureStroke | Armature stroke of both moving coil actuator models after a voltage step at time t=0 |
| Components | Components to be used in examples |


I am a creative type that makes sure to enjoy what I do. I've found joy in engineering, cello 🎻 (there's only a violin emoji), bikes 🚲, and petting dogs 🐶.
Currently a web developer at the American Lung Association, I take on tasks such as building new features, creating interactive content, data visualization, and managing <forms>, just to name a few.
At work, I use a ton of AJAX, promises async/await, and basic sorting functions.
- Javascript
- React
- VueJS
- NodeJS
- ASP.NET Core MVC
- C#
- CSS
- Sass, Less
- Swiftype Elastic Search (crawler & API)
- Kentico CMS
- Luminate CMS
I also make applications using NodeJS via AWS and Digital Ocean.


| Class | Description |
|---|---|
| DeployConstrainedExertionTest |
This test verifies that an exertion can be deployed to a specific machine, and also that an exertion will not be
deployed.
|
| DeployExertionTest | |
| DeploymentIdFactory |
Utility to create deployment ids
|
| FileResolverHandler | |
| OperationalStringFactory |
Create an
OperationalString from an Exertion . |
| OperationalStringFactoryTest | |
| ProvisionManagerTest |
Test
ProvisionManager interactions |
| ProvisionMonitorCache |
Utility to provide a cache of known
ProvisionMonitor s. |
| ServiceDeployment |
Attributes related to signature based deployment.
|
| ServiceElementFactory |
Create a
ServiceElement from a ServiceSignature . |
| ServiceElementFactoryTest | |
| ServiceUtil |
Utility for waiting on service deployments and/or services
|


Elder Filaur:
I don't know exactly what these Wererats are up to, but since they infested the area, a powerful evil aura has crept over the Mithril Mine. People who approached it carelessly have nearly been killed!
As a result, the Gray Pillar Guild has shut down certain areas of the Mithril Mine and limited access to other areas.
"That's terrible!"


Eager to learn. Ready to take on complex problems.
CRUD Operations: Create, read, update, drink. React, Node, Express, Massive, Redux. Dynamic user content
Want to get away? Search for the cheapest flights from your nearest airport with Wayz. React, Node, Express, Massive, Redux
Find all the shows for all of your favorites artists at once. React, Node, Express, Bandsintown API
Keep track of all the restaurant specials you and your friends love. React, Express, Node, Redux, Maps API, Firebase


QATrack+ Administrators Guide¶
The admin guide is intended for use by anyone who will be responsible for configuring tests and test lists, modifying references & tolerances or managing users and user permissions.
To access the admin site, log into QATrack+ and then choose the Admin option from the dropdown at the top right hand corner of the page (where your username is displayed).
A walk through tutorial (with screenshots) on going from a blank QATrack+ install to a fully configured, performable test list is available on the tutorials page. Reading through this tutorial is a great way to familiarize yourself with QATrack+ configuration.
Initial Configuration¶
Before you start defining tests and test lists for the first time it is a good idea to begin by doing some initial configuration.
Admin Operations¶
A step-by-step tutorial to walk you through the process of configuring a new test list and assigning it to a unit is available on our tutorial page.
- Test Configuration
- Test List Configuration
- Test List Cycles
- Assigning a test list or test list cycle to a unit
- Setting references and tolerances for a test
- Copying references and tolerances from one unit to another
- Configuring test statuses
- Configuring test frequencies
- Configuring test tolerances
- Creating a new Unit
- Managing Users, Groups and permissions
- Managing contact numbers
- Setting up email notifications
- Auto Schedule management command
Admin Tutorials¶
For a list of tutorials avaialable please visit our tutorial page.


Autoencoder
27 Oct 2020Definition
a neural network that is trained to attempt to copy its input to its output.
Encoder(deterministic functions): \(h = f(x)\)
Decoder(stochastic mappings): \(r = g(h)\)
So, learning to set \(g(f(x)) = x\)
However, autoencoders are designed to be unable to learn to copy perfectly
Objective : h taking on useful properties(features).
useful featrues from the autoencoder is to constrain \(h\) to have a smaller dimension than \(x\).
Usage : feature learning (feature extraction), dimensionality reduction
Modern Autoencoders
Encoder => Deterministic functions : \(p_{encoder}(h|x)\)
Decoder => Stochastic mappings : \(P_{decoder}(x|h)\)
So, autoencoders + latent variable models => generative modeling.
-
Latent Variable(as opposed to observable variables)
:= the variables that are not directly observed but are rather inferred from other variables that are observed. -
Autoencoder training
- minibatch gradient descent
- recirculation
:= a learning algorithm based on comparing the activations of the network on the original input to the activations on the reconstructed input.
The learning process
\[min({L(x,g(f(x)))})\]\(L\) is a loss function penalizing \(g(f(x))\)
Undercomplete Autoencoders
an autoencoder whose hidden code (\(h\)) dimension is less than the input dimension.
- undercomplete with (decoder = linear), (\(L\) = MSE)
- learns to span the same subspace as PCA
- trained to perform the copying task has learnt the princple subspace of the training data as a side effect
- undercomplete with (encoder = nonlinear), (decoder = nonlinear)
- learn a more powerful nonlinear generalization of PCA
- DON’T allows too much capacity
-about the distribution of the data, feature extracting 대신에 copying 함
Overcomplete Autoencoders
an autoencoder whose hidden code (\(h\)) dimension is greater than the input dimension.
- overcomplete with (encoder = linear), (decoder = linear)
- learn to copy the input to the output without learning anything useful about the data distribution.
Regularized Autoencoders
get ability to choose the code dimension and the capacity of the encoder and decoder based on the complexity of distribution to be modeled.
Rather than limiting the model capacity by keeping the encoder and decoder shallow and the code size small.
Objective : use a loss function that encourages the model to have other properties include sparsity of the representation, smallness of the derivative of the representation, and robustness to noise or to missing inputs.
- Regularized + Overcomplete = Undercomplete
(in terms of feature extraction)- can be nonlinear and overcomplete but still learn something useful about the data distribution, even if the model capacity is great enough to learn a trivial identity function.
Particular form of Autoencoder (regularized autoencoders 관련된 모델들)
- nearly any generative model with latent variables
- equipped with an inference procedure (for computing latent representations given input)
-
Two generative modeling approaches that emphasize this connection with autoencoders are the descendants of the Helmholtz machine
-
Helmholtz machine
- variational autoencoder (section 20.10.3 in deep learning book)
- generative stochastic networks (section 20.12 in deep learning book)
- These models naturally learn high-capacity, overcomplete encodings of the input and do not require regularization for these encodings to be useful.
- there encodings are naturally useful because the models were trained to approximately maximize the probability of the training data rather than to copy to input to the output.
-
Sparse Autoencoders
an autoencoder whose training criterion involves a sparsity penalty \(\Omega(h)\) on the code layer \(h\), in addition to the reconstruction error
\[L(x,g(f(x))) + \Omega(h)\]usage : learn features for another task (e.g. classification)
- copying task(vanila autoencoder) + sparsity penalty 목적
- yield a model that has learnt useful features(unique statistical features) as a byproduct.
- \(\Omega(h)\) is sort of Regularizer
- However, there is not a straightforward Bayesian interpretation
-
training with weight decay(= regularizer) and other regularization penalties can be intpreted as a MAP approximation to Bayesian inference, with the added regularizing penalty corresponding to a prior probability distribution over the model parameters.
\(\begin{equation} \begin{split} i.e.\;\; MAP\;approxiamtion &\approx Bayesian\;inference + regularizing\;panelty \\ &\approx training + regularizing\;penalty \end{split}\end{equation}\)
In this view, \(\begin{equation}\begin{split} regularized\;maximum\;likelihood &= max\;p(\theta|x) \\ &= max\;(MAP\;Estimation(p(\theta|x))) \\ &= max\;(log(MAP(p(\theta|x)))) \\ &= max\;(log\:p(x|\theta)p(\theta)) \\ &= max\;(log\:p(x|\theta)+log\;p(\theta)) \\ &Equivalent,\\ &= max\;(log\;likelihood + prior\;distribution) \\ \end{split}\end{equation}\) where,
\(p(\theta|x)\) is conditonal probability
\(p(x|\theta)\) is likelihood
all \(\theta\) is independent
prior distribution can implicitly expressed as a preference over functions-
MAP inference using a gaussian prior on W (Maximum A Posteriori)
- Bayes theorem (conditional probability)
evidence = (likelihood * prior P) / (posterior P)
- MAP method
- posterior P를 최대화 시킨다.
- 장점: leveraging information that is brought by the prior and cannot be found in the training data.
(this additional information helps to reduce the variance in the MAP point estimate) - 단점: the price of increased bias
(e.g.)
z = 머리카락 발견
남자것일 확률: \(p(male|z)\)
여자것일 확률: \(p(female|z)\)비교 후, 큰 값을 갖는 클래스(성별) 찾는 방법
\[\begin{equation} \begin{split} p(female|z) &= \frac {p( female \cap z)} {p(female \cap z) + p(male \cap z)} \\ &= \frac {p(z|female)p(z)} {p(z|female)p(z) + p(z|male)p(z)} \\ &\;Since,\;the\;summation\;of\;all\;probablities\;is\;1 \\ &(male\;and\;female\;are\;independent) \\ &= p(z|female)p(z) \end{split}\end{equation}\]Maximum likelihood Maximum A Posteriori class 비율 고려X class 비율 고려O - MAP Estimation
choose the point of maximal posterior probability
\(\theta_{MAP} = arg\;max_\theta\;p(\theta|x) = arg\;max_\theta\;log\:p(x|\theta) + log\:p(\theta)\)
- Bayes theorem (conditional probability)
-
However, Regularized autoencoders defy such an interpretation because the regularizer \(\Omega(h)\)는 데이터에 의존하므로 정의상 단어의 공식적인 의미에서 a prior이 아닙니다.
So, Rather than thinking of the sparsity penalty as a regularizer for the copying task, we can think of the entire sparse autoencoder framework as approximating maximum likelihood training of a generative model that has latent variables. Again,
- explicit joint distribution \(p_{model}(h,x)=p_{model}(h)p_{model}(x|h)\)
where, h is latent varibles and x is visible variables - \(p(\theta)\) encodes our beliefs about the model’s parameters before we have seen the training data.
Thus, log-likelihood can be decomposed as
\[log\;p_{model}(x)=log\displaystyle \sum_h p_{model}(h,x)\]p(x)가 exp함수이면 log likelihood의 softmax의 loss 함수 꼴
- 이러면, autoencoder를 approximating this sum with a point estimate for just one highly likely value for \(h\)
(sparse coding generative model이랑 비슷하다)


import os
from typing import Union
from python_pachyderm.experimental import Client
from python_pachyderm.experimental.pfs import Commit
from python_pachyderm.experimental.service import pps_proto, pfs_proto
[docs]def put_files(
client: Client,
source_path: str,
commit: Union[tuple, dict, Commit, pfs_proto.Commit],
dest_path: str,
**kwargs
) -> None:
"""Utility function for inserting files from the local `source_path`
into Pachyderm. Roughly equivalent to ``pachctl put file [-r]``.
Parameters
----------
client : Client
A python_pachyderm client instance.
source_path : str
The file/directory to recursively insert content from.
commit : Union[tuple, dict, Commit, pfs_proto.Commit]
The open commit to add files to.
dest_path : str
The destination path in PFS.
**kwargs : dict
Keyword arguments to forward. See
``ModifyFileClient.put_file_from_filepath()`` for more details.
Examples
--------
>>> source_dir = "data/training/
>>> with client.commit("repo_name", "master") as commit:
>>> python_pachyderm.put_files(client, source_dir, commit, "/training_set/")
...
>>> with client.commit("repo_name", "master") as commit2:
>>> python_pachyderm.put_files(client, "metadata/params.csv", commit2, "/hyperparams.csv")
>>> python_pachyderm.put_files(client, "spec.json", commit2, "/")
.. # noqa: W505
"""
with client.modify_file_client(commit) as mfc:
if os.path.isfile(source_path):
mfc.put_file_from_filepath(dest_path, source_path, **kwargs)
elif os.path.isdir(source_path):
for root, _, filenames in os.walk(source_path):
for filename in filenames:
source_filepath = os.path.join(root, filename)
dest_filepath = os.path.join(
dest_path, os.path.relpath(source_filepath, start=source_path)
)
mfc.put_file_from_filepath(dest_filepath, source_filepath, **kwargs)
else:
raise Exception("Please provide an existing directory or file")
[docs]def parse_json_pipeline_spec(j: str) -> pps_proto.CreatePipelineRequest:
"""Parses a string of JSON into a `CreatePipelineRequest` protobuf.
Parameters
----------
j : str
Pipeline spec as a JSON-like string.
Returns
-------
pps_proto.CreatePipelineRequest
A protobuf object that contains the spec info necessary to create a
pipeline.
Examples
--------
Useful for going from Pachyderm spec to creating a pipeline. Pachyderm
spec: https://docs.pachyderm.com/latest/reference/pipeline_spec/
>>> spec = '''{
... "pipeline": {
... "name": "foobar"
... },
... "description": "A pipeline that performs image edge detection by using the OpenCV library.",
... "input": {
... "pfs": {
... "glob": "/*",
... "repo": "images"
... }
... },
... "transform": {
... "cmd": [ "python3", "/edges.py" ],
... "image": "pachyderm/opencv"
... }
... }'''
>>> req = python_pachyderm.parse_json_pipeline_spec(spec)
>>> client.create_pipeline_from_request(req)
.. # noqa: W505
"""
return pps_proto.CreatePipelineRequest().from_json(j)
[docs]def parse_dict_pipeline_spec(d: dict) -> pps_proto.CreatePipelineRequest:
"""Parses a dict of serialized JSON into a `CreatePipelineRequest` protobuf.
Parameters
----------
d : dict
Pipeline spec as a dictionary.
Returns
-------
pps_proto.CreatePipelineRequest
A protobuf object that contains the spec info necessary to create a
pipeline.
Examples
--------
Useful for going from Pachyderm spec to creating a pipeline. Pachyderm
spec: https://docs.pachyderm.com/latest/reference/pipeline_spec/
>>> spec = '''{
... "pipeline": {
... "name": "foobar"
... },
... "description": "A pipeline that performs image edge detection by using the OpenCV library.",
... "input": {
... "pfs": {
... "glob": "/*",
... "repo": "images"
... }
... },
... "transform": {
... "cmd": [ "python3", "/edges.py" ],
... "image": "pachyderm/opencv"
... }
... }'''
>>> req = python_pachyderm.parse_dict_pipeline_spec(json.loads(spec))
>>> client.create_pipeline_from_request(req)
.. # noqa: W505
"""
return pps_proto.CreatePipelineRequest().from_dict(d)


Returns a dense Tensor
as input layer based on given feature_columns
.
tf.compat.v1.feature_column.input_layer( features, feature_columns, weight_collections=None, trainable=True, cols_to_vars=None, cols_to_output_tensors=None )
Generally a single example in training data is described with FeatureColumns.
At the first layer of the model, this column oriented data should be converted
to a single Tensor
.
price = numeric_column('price') keywords_embedded = embedding_column( categorical_column_with_hash_bucket("keywords", 10K), dimensions=16) columns = [price, keywords_embedded, ...] features = tf.io.parse_example(..., features=make_parse_example_spec(columns)) dense_tensor = input_layer(features, columns) for units in [128, 64, 32]: dense_tensor = tf.compat.v1.layers.dense(dense_tensor, units, tf.nn.relu) prediction = tf.compat.v1.layers.dense(dense_tensor, 1)
features
: A mapping from key to tensors. _FeatureColumn
s look up via these
keys. For example numeric_column('price')
will look at 'price' key in
this dict. Values can be a SparseTensor
or a Tensor
depends on
corresponding _FeatureColumn
.feature_columns
: An iterable containing the FeatureColumns to use as inputs
to your model. All items should be instances of classes derived from
_DenseColumn
such as numeric_column
, embedding_column
,
bucketized_column
, indicator_column
. If you have categorical features,
you can wrap them with an embedding_column
or indicator_column
.weight_collections
: A list of collection names to which the Variable will be
added. Note that variables will also be added to collections
tf.GraphKeys.GLOBAL_VARIABLES
and ops.GraphKeys.MODEL_VARIABLES
.trainable
: If True
also add the variable to the graph collection
GraphKeys.TRAINABLE_VARIABLES
(see tf.Variable
).cols_to_vars
: If not None
, must be a dictionary that will be filled with a
mapping from _FeatureColumn
to list of Variable
s. For example, after
the call, we might have cols_to_vars =
{_EmbeddingColumn(
categorical_column=_HashedCategoricalColumn(
key='sparse_feature', hash_bucket_size=5, dtype=tf.string),
dimension=10): [<tf.Variable 'some_variable:0' shape=(5, 10),
<tf.Variable 'some_variable:1' shape=(5, 10)]}
If a column creates no variables, its value will be an empty list.cols_to_output_tensors
: If not None
, must be a dictionary that will be
filled with a mapping from '_FeatureColumn' to the associated
output Tensor
s.A Tensor
which represents input layer of a model. Its shape
is (batch_size, first_layer_dimension) and its dtype is float32
.
first_layer_dimension is determined based on given feature_columns
.
ValueError
: if an item in feature_columns
is not a _DenseColumn
.


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Kyle I S Harrington /<EMAIL_ADDRESS>Hebb's learning rule: fire together, wire together
$\Delta w_{kj} = \eta x_j y_k$
change weight $i$ proportinally to the product of the input and the output
$\Delta w_{kj} = \eta x_j y_k$
Problems?
How do we find weights that can produce a particular output?
$\Delta w_{kj} = \eta ( t_k - o_k ) i_j$
start with some $w_{(0)}$
do:
$w^{(t+1)} = w^{(t)} - \eta_t \nabla F(w^{(t)})$
until $||w^{(t+1)}-w^{(t)}|| \leq \epsilon$
Given a stream of input/output samples
Update weights after each sample (online learning)
Notebook!
Predict a binary class, $y$, given a feature value, $x$
$P(y=1|x) > P(y=0|x)$
Rewrite $P(y=1|x) > P(y=0|x)$
As log-odds: $log \frac{P(y=1|\textbf{x})}{P(y=0|\textbf{x})} > 0$
$P(y|\textbf{x})$ is generally either unknown or estimated from samples
Linear approximation $log \frac{P(y=1|\textbf{x})}{P(y=0|\textbf{x})}$ as
$f(x;w) = w_o + x \cdot w_1$
$log \frac{P(y=1|\textbf{x})}{P(y=0|\textbf{x})} = w_o + x \cdot w_1$
Instead we use
$P(y=1|x_i, w_{0,i} , w_{1,i} ) = g( w_{0,i} + x \cdot w_{1,i} )$
$g(z) = \frac{1}{(1+e^{-z})}$
"Squishing function"
$f(x) = \frac{1}{1+e^{-x}}$
Learn the weights with a penalty, $w$:
$\text{argmax}_{w} \displaystyle \sum^m_{i=1} P(y_i=1|x_i, w ) - \alpha R(w) $
Regularization term, $R(w)$, forces parameters to be small when $\alpha>0$
L1: $R(w) = ||w||_1 = \displaystyle \sum^n_{i=1} |w_i|$
L2: $R(w) = ||w||_2 = \displaystyle \sum^n_{i=1} w_i^2$
L2 tends to be better at shrinking weightsDue March 7 (Monday)
Clustering


This Project Was Maintained and Developed By DIVAKARAN
Github Link :-
Source Code
Contact :-
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Shadow Import
Flexible, simple, and powerful.
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Green (Component Method)
Red (Component Attrs)


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"What a mindless wonder!" US Rep. Maxine Waters on Jefferson Sessions 08 Nov 2019, 23:25 by Jason Weisberger I love Maxine Waters.


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