imapper Package¶
errorbars
Module¶
-
errorbars.
dco_between
(zlo, zhi, cosmo)¶ Calculate the comoving distance [Mpc] between two redshifts in a given cosmology.
-
errorbars.
fwhm_to_sigma
(fwhm)¶ Calculate Gaussian sigma (standard deviation) from FWHM value.
The relation between them is: fwhm = sqrt(8ln2) * sigma
-
errorbars.
kmax_parallel
(zobs, nu_obs, dnu, cosmo)¶ Calculate maximum k (along line of sight) from frequency resolution
-
errorbars.
kmax_perpendicular
(d_comoving, sigma_beam)¶ Calculate maximum k (across sky) from angular resolution
Parameters: d_comoving :
comoving radial distance (pre-calculated from redshift) [Mpc]
sigma_beam :
arc length of beam width [radians]
-
errorbars.
num_modes
(k, vol)¶ Calculate the number of modes in a given volume as a function of k.
The result is premultiplied by a factor 1/2 because the 3D intensity map is real-valued, so only half the modes are independent.
-
errorbars.
powercyl_error
()¶
-
errorbars.
powersph_error
(power, tsys, nfeeds, tobs, xarclen, yarclen, fwhm, nu_min, nu_max, dnu, nu0, k, cosmo)¶ Get instrument sensitivity in power spectrum, provided a set of instrument parameters Required parameters for:
Parameters: power : ndarray
must have same length as k
tsys : float
System temperature [K]
nfeeds
Number of feeds
tobs
Total observing time [s]
xarclen
Length of FOV [arcmin]
fwhm
FWHM of beam [arcmin]
nu_min
minimum observing frequency [GHz]
nu_max
maximum observing frequency [GHz]
dnu
frequency resolution [GHz]
nu0
rest-frame line frequency [GHz]
k : array
a vector of k at which to calculate power noise
cosmo : astropy.cosmology object
For cosmology calculations
Returns: sigma_power : array
Expected error bars in power spectrum as a function of k. Units of [uK^2 * Mpc^3]. Same dimensions as k.
noise_power : array
nmodes : array
res_factor : array
-
errorbars.
res_damping
(k, kmax_par, kmax_prp, nmu=100)¶ Resolution-limit “damping” factor on the power spectrum, as a function of k
Parameters: k : ndarray
kmax_par : float
kmax_prp : float
nmu : int
-
errorbars.
sigma_radiometer
(area_surv, area_res, tobs, tsys, dnu, nfeeds)¶ Calculate sensitivity per voxel by evaluating the radiometer equation.
Parameters: area_surv [deg^2] : Area of full survey
area_res [arcmin^2] : Area of angular resolution (beam size)
tobs [s] : Total observing time
tsys [K] : System temperature
dnu [GHz] : Voxel width in frequency
nfeeds : Number of collecting feeds
Returns: sigma : expected temperature fluctuation per pixel [uK]
-
errorbars.
voxel_volume
(dco, sig_beam, nu_rest, nu_obs, dnu, cosmo)¶ Get comoving voxel volume
Parameters: dco :
comoving distance
sig_beam :
beam width
nu_rest :
rest frame line frequency
nu_obs :
observed frequency
dnu :
frequency channel width
cosmo :
astropy.cosmology object (contains cosmological info)
functions
Module¶
Helper functions for intensity mapping code.
-
functions.
angfreqbins_to_redshiftcube
(angfreq, nurest)¶ Parameters: angfreq : 3-tuple of 1d arrays
arrays of bin edges in (arcmin, arcmin, and [freq]) respectively
nurest : float
rest frame frequency of spectral line of interest
Returns: redshiftcube : 3d array
3d array of redshifts (will only vary in depth, aka z, direction)
-
functions.
angfreqbins_to_vol
(angfreqbins, nurest, cosmo)¶ Convert angxangxfreq bins to grid of comoving cell volumes.
Parameters: angfreqbins : 3-tuple of 1d arrays
arrays of bin edges in (arcmin, arcmin, and [freq]) respectively
nurest : float
rest frame frequency of spectral line of interest
cosmo :
Returns: vol : 3d array
3d array of volume elements, in Mpc^3
-
functions.
arcmin_to_comovingMpc
(arcmin, z, cosmo)¶ Convert arcmin to transverse comoving Mpc, assuming a given redshift and cosmology.
Parameters: arcmin : float or array-like
length in arcminutes
z : float
redshift
cosmo : astropy.cosmology object
assumed cosmology
Returns: dco : float or array-like
Comoving distance in Mpc
-
functions.
bin_lengths
(bin_edges)¶ Parameters: bin_edges : 1d array
n-element 1D array of monotonically increasing bin edges
Returns: bin_lengths : 1d array
(n-1)-element 1D array of bin lengths
-
functions.
bin_midpoints
(bin_edges, log=False)¶ Given an ordered sequence of bin edges, compute the midpoints
-
functions.
comov_to_angfreq
(comov, nurest, cosmo)¶ Convert comoving grid to angxangxfreq grid.
Parameters: comov : 3-tuple
a 3-tuple with 1D x, y, z arrays, respectively
nurest : float
rest frame frequency of spectral line of interest
cosmo :
Returns: xa : float array
x in units of arcmin
ya : float array
y in units of arcmin
zf : float array
z in units of frequency, same units as nurest
-
functions.
comovbins_to_vol
(comovbins, nurest)¶
-
functions.
comovingMpc_to_arcmin
(dco, z, cosmo)¶ Convert transverse comoving Mpc to arcmin, assuming a given redshift and cosmology.
Parameters: dco : float or array-like
Comoving distance in Mpc
z : float or array-like
redshift
cosmo : astropy.cosmology object
assumed cosmology
Returns: arcmin : float or array-like
length in arcminutes
-
functions.
comovingMpc_to_nu
(dco, nu0, cosmo)¶ Convert comoving radial distance to observed frequency, assuming a given rest-frame frequency.
Parameters: dco : float or array-like
Comoving distance in Mpc
nu0 : float
Rest frame frequency
cosmo : astropy.cosmology object
assumed cosmology
Returns: nu : float or array-like
Observed frequency, same units as nu0
-
functions.
comovingMpc_to_z
(dco, cosmo)¶ Convert comoving depth to redshift.
-
functions.
cut_halos
(halos, params)¶ - halos : HaloList object
- halo properties (x position, parent id, etc.)
- params :
- dictionary of parameter values
-
functions.
dnu_to_comovingMpc
(dnu, nu0, redshift, cosmo)¶ Convert frequency interval to comoving depth interval, given rest-frame frequency.
-
functions.
ensure_dir
(path)¶ Ensure that directory exists (create if it doesn’t)
-
functions.
is_evenly_spaced
(arr)¶ Check if an array has evenly spaced elements (linear)
-
functions.
load_cube
(params)¶
-
functions.
load_halos
(params, filenum=None, verbose=True)¶ Load halo catalog, and store halo properties in a HaloList object (see ‘halolist’ module).
- The location of the halo data should be stored in ‘params’ as a string. The file itself should in the *.npz format, and the halo properties included must be:
- x y z m ra dec ...[unfinished]
Parameters: params
dictionary containing all parameter values
Returns: halos : HaloList object
object containing halo properties
-
functions.
lsun_to_uk
(lum, nurest, vol, redshift, cosmo)¶ Convert line luminosity at a given frequency to Raleigh-Jeans temperature.
Parameters: lum : float or array
total luminosity within spectral bin [Lsun]
nurest : float
rest-frame line frequency (GHz)
vol : float or array
comoving volume [Mpc^3]
redshift : float or array
redshift
cosmo : astropy.cosmology object
Returns: temprj : float or array
Rayleigh-Jeans brightness temperature
-
functions.
save_cube
(x, y, z, t, params)¶ Save temperature cube to file.
-
functions.
save_data
(tcube_data, psph_data, pcyl_data, params)¶ Save data to
Parameters: tcube_data : dictionary
contains the keys ‘x’, ‘y’, ‘z’, ‘t’. xyz are 1D arrays, t is a 3D array.
psph_data : dictionary
contains the keys ‘ksph’, ‘psph’, ‘perr’, ‘pnoise’, ‘nmodes’, ‘wres’
pcyl_data : dictionary
contains the keys ‘kprp’, ‘kpar’, ‘pcyl’
-
functions.
save_paramfile
(params)¶
-
functions.
save_powercyl
(kprp, kpar, pcyl, params)¶
-
functions.
save_powerspectrum
(k, p, perr, pnoise, nmodes, fres, params)¶
-
functions.
save_powersph
(k, p, perr, pnoise, nmodes, fres, params)¶
-
functions.
uk_to_mjy
(t_uK, nu_GHz, th_arcmin)¶ Convert brightness temperature [uK] to flux density [mJy].
- See equation at https://science.nrao.edu/facilities/vla/proposing/TBconv:
- T = 1.36 * ( lambda[cm]^2 / theta[arcsec]^2 ) * S[mJy/beam]
Parameters: t_uK: brightness temperature in uK
nu_GHz: frequency in GHz th_arcmin: FWHM in arcmin
Returns: s_mJy (float): flux density in mJy
-
functions.
z_to_comovingMpc
(redshift, cosmo)¶ Convert redshift to comoving depth.
grid
Module¶
Module containing IMGrid, a class for grid objects, as well as helper functions
-
class
grid.
IMGrid
(abounds, da, fbounds, df, nurest, cosmo)¶ Bases:
object
Object storing intensity mapping grids.
This is useful for conserving memory in case repeated runs are necessary within the same volume (e.g. when sampling parameter space during an MCMC run).
Contains the following attributes - angfreqbins: ang x ang x freq bins - lumcube: luminosities in each grid cell (not necessarily defined at creation) The binning in each should be equivalent (i.e. objects in the ijk-th bin of the ang-ang-freq grid should also be in the same ijk-th bin of the comoving grid).
-
grid.
angfreq_to_comov_grid
(angfreqbins, nurest, cosmo)¶ Convert a field on an (ang x ang x freq) grid to a 3D comoving grid
Parameters: angfreqbins : tuple or list of arrays, length (M+1, N+1, P+1)
bin edges of angular and frequency directions
nurest : float
observed (redshifted) frequency of mapped line at z=0
cosmo :
-
grid.
getangfreqbins
(abounds, da, fbounds, df)¶ Get data cube bins in angular and frequency coordinates.
The 3D data cube is assumed to have 2 angular (x,y) and 1 frequency (z) dimensions. Units are arcmin for angle, GHz for frequency.
Parameters: abounds
da
fbounds
df
Returns: xbins : 1D array
Angular bins edges in x direction [arcmin]
ybins : 1D array
Angular bins edges in y direction [arcmin]
zbins : 1D array
Frequency bins edges in z direction [GHz]
halolco
Module¶
Module for calculating line luminosities from halos.
Broadly speaking, halos come in, line luminosities go out.
-
halolco.
co_sled
(j, mode='thermal')¶ Returns luminosity normalization factor L(j -> j-1)/L(1 -> 0)
-
halolco.
lidz11
(mass)¶ LCO(M) of Lidz+11 at z~7
-
halolco.
lir_to_lcoprime
(lir, alpha=1.37, beta=-1.74)¶ Compute LCO’ from LIR assuming a power-law relation between them.
- Assumed LIR-LCO’ relation of the form:
- log(LIR) = alpha * log(LCO’) + beta
This function inverts that relation. alpha=1.37, beta=-1.74 are values from Carilli+Walter13.
-
halolco.
logscatter
(x, dexscatter)¶ Return array x, randomly scattered by a log-normal distribution with sigma=dexscatter.
Note: scatter maintains mean in linear space (not log space).
-
halolco.
lprime_to_l
(lprime, nurest)¶ Convert L’ (integrated brightness temperature) to L (luminosity)
Parameters: lprime : float or array
Area- and velocity-integrated brightness temperature [K km/s pc^2]
nurest : float
Rest-frame line frequency [GHz]
-
halolco.
mhalo_to_sfr
(*args, **kw)¶ DEPRECATED
-
halolco.
powerlaw
(x, pow, prefac)¶
-
halolco.
pullen13A
(mass)¶ LCO(M) of Pullen+13A at z=2.4
-
halolco.
pullen13B
(mass)¶ LCO(M) of Pullen+13B at z=2.4, as linearly approximated by Breysse+2014
-
halolco.
righi08
(mass)¶ LCO(M) of Righi+2008, as linearly approximated by Breysse+2014
-
halolco.
sfr_bwc13
(mass, redshift, mode=None)¶ SFR(M,z) relation of Behroozi, Wechsler, and Conroy 2013
Takes in Mhalo and redshift, returns an interpolated SFR
Parameters: redshift : float
redshift at which to interpolate
mass : float array
halo masses
mode : None or str
None : default mode, uses ‘sfr_release’ values from paper ‘lo’ : uses sfr - error ‘hi’ : uses sfr + error
-
halolco.
sfr_bwc13_scatter
(mass, redshift, scatter=0.25, mode='dex')¶
-
halolco.
sfr_to_lco
(*args, **kw)¶ DEPRECATED
-
halolco.
sfr_to_lco_shortcut1
(*args, **kw)¶ DEPRECATED
-
halolco.
sfr_to_lir
(sfr, deltamf=1.5)¶ Convert SFR to LIR using Kennicutt98 relation.
-
halolco.
visbal10
(mass)¶ LCO(M) of Visbal+10 at z=2.4
-
halolco.
visbal10_z6
(mass)¶
imapping
Module¶
-
imapping.
get_halo_cellidx
(hxa, hya, hzf, angfreqbins)¶ Get the cell indices of each halo
Parameters: hxa : 1D float array
halo x-coordinates, angular units (RA)
hya : 1D float array
halo y-coordinates, angular units (Dec)
hzf : 1D float array
halo z-coordinates, frequency units (observed frequency)
angfreqbins : list or tuple
3 arrays of the bin edges in the x,y,z directions. RA, Dec, and frequency bin edges are given by
angfreqbins[0,1,2]
respectively.Returns: cellidx :
[UNFINISHED]
-
imapping.
lcube_to_tcube
(lcube, angfreqbins, nurest, cosmo)¶
-
imapping.
lhalo_to_lcube
(hxa, hya, hzf, hlco, angfreqbins, nurest, cosmo, hbinidx=None, verbose=True)¶ [placeholder]
mapit
Module¶
-
mapit.
get_args
()¶
-
mapit.
get_grid
(params)¶ Returns IMGrid object based on instrument and survey parameters
-
mapit.
get_halos
(params)¶ Returns HaloList object (with selection cuts applied, etc)
-
mapit.
get_lco
(halos, params, reuse_sfr=False)¶ Get Lco for all halos
-
mapit.
get_powercyl
(imgrid)¶ Return kprp, kpar, P(kprp, kpar) for cylindrically averaged power spectrum
-
mapit.
get_powersph
(imgrid)¶ Return k, P(k) for spherically averaged power spectrum
-
mapit.
get_powersph_errorbars
(k, power, params)¶ Calculate the error bars on spherically-averaged P(k) (1-sigma uncertainty) as a function of k.
This is a convenience method, which calls the internal method.
Parameters: k : 1D array
Values of k at which to calculate error bars on the power spectrum. [1/Mpc]
power : 1D array
Autopower spectrum at the corresponding values of k. Should be the same length as k. [uK^2 Mpc^3]
-
mapit.
get_tcube
(halos, imgrid, params)¶
-
mapit.
main
()¶
parameters
Module¶
-
parameters.
check_deprecated
(raw_params)¶
-
parameters.
get_cosmology_parameters
(raw_params)¶ Returns: cosmo : astropy.cosmology object
object containing cosmological parameters
-
parameters.
get_instrument_parameters
(raw_params)¶ Returns: instr : dict
instrument parameters
-
parameters.
get_params
(filepath)¶ Get parameter values and return them in the form of a dictionary.
Parameters: filepath : str
path to parameter file
Returns: params : dict
-
parameters.
get_survey_parameters
(raw_params)¶ Returns: survey : dict
survey parameters
-
parameters.
get_tsys
(raw_params)¶
-
parameters.
is_true
(raw_params, key)¶ Is raw_params[key] true? Returns boolean value.
-
parameters.
validate_params
(params)¶ Validate parameters and correct if necessary.
powerspectrum
Module¶
-
powerspectrum.
f3d_to_fcylavg
(func, x, y, z, bins=None, log=False)¶ Cylindrically average a function defined on a 3D grid
Parameters: func :
x :
y :
z :
bins :
Number of bins, in the form (kprp, kpar)
-
powerspectrum.
f3d_to_fsphavg
(func, x, y, z, bins=None, log=False)¶ Spherically average a function initially defined on a 3d grid
-
powerspectrum.
real_to_fourier
(func, x, y, z)¶
-
powerspectrum.
real_to_pow3d
(func, x, y, z)¶ Calculate a 3D power spectrum, given: – a function defined on a 3D grid of evenly-spaced (x,y,z) points – a 1D array of the sampled points in each dimension (x,y,z)
-
powerspectrum.
real_to_powcyl
(func, x, y, z)¶ Convert a real 3d function to cylindrically averaged power spectru, P(kpar, kprp).
Parameters: func :
x :
y :
z :
Returns: kprp :
perpendicular component of k (i.e. x and y)
kpar :
parallel component of k (i.e. z)
pcyl :
-
powerspectrum.
real_to_powsph
(func, x, y, z)¶ Convert real function to a spherically averaged power spectrum, P(k).
Parameters: func : float 3D array
values of function on 3D grid
x : float 1D array
y : float 1D array
z : float 1D array
Returns: k : float 1D array
radius in k-space
psph : float 1D array
spherically averaged power spectrum, P(k)
-
powerspectrum.
real_to_xpow3d
(f1, f2, x, y, z)¶ Calculate a 3D cross power spectrum, given: – two functions defined on a 3D grid of evenly-spaced (x,y,z) points – a 1D array of the sampled points in each dimension (x,y,z)
-
powerspectrum.
real_to_xpowcyl
(f1, f2, x, y, z)¶
-
powerspectrum.
real_to_xpowsph
(f1, f2, x, y, z)¶ Convert 2 intensity maps to a spherically averaged cross power spectrum, P(k)
-
powerspectrum.
xyz_to_rcylbins
(x, y, z, bins=None, log=False)¶ Transform Cartesian grid (x,y,z) to cylindrical bins (radial and z)
Parameters: x :
y :
z :
bins :
log :
Returns: rcylbins :
-
powerspectrum.
xyz_to_rsphbins
(x, y, z, bins=None, log=False)¶ Transform Cartesian grid (x,y,z) to spherically radial bins
Parameters: x, y, z : 1D arrays
cartesian grid arrays
bins : int or None
Number or radial bins. If None, defaults to bin count such that dr = max(dx, dy, dz)
Returns: rsphbins : 1D array
radial bin edges


Any two points, A and B, define a line, and a square can be constructed whose top edge is on that line.
Let C be the midpoint between A and B, and D be the corner of the square farthest from A.
The circle with center at C, through D, intersects the line AB in two places; let E be the
intersection furthest from A. Let F be the corner of the square furthest from B; the
rectangle with corners F, A, and E is a golden rectangle.
Please look at the source code of this page for more information.


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--- layout: post title: Recursive photography with @chhorno date: 2010-07-13 03:30:36.000000000 -07:00 type: post published: true status: publish categories: [] tags: [] meta: {} author: ---


It’s TIIIIIIIIMMMMMMMEEEEEE. Introducing first, the meme creator in the red trunks out, memeing out of Massachusetts, I present to you the Memer of the Masses, Memes over My Hammy, the Memeinator, the one, the only, AGGGGRRRROOOOOEEEEEEEEDDDDDD.
Hey, thanks me for that great introduction… I have a few Memes for you to enjoy today. Please find them below.
More Pedo justice
Looks like he(they) know this doesn’t look good
Here’s an alternative
Some thoughts on Voice of America and lack of NK coverage
Always awesome when government policy leads to some Nazi Germany comparisons…
 Trump’s team isn’t immune
So… what’s the point then? Why is this happening?
SPACE FORCE!
15 years prior… That’s pretty specific for the Simpsons to get right…
Media heating up
This is basically anything I’ve been saying since 2012
Yep
Some weird shit happening over at the FBI
Anons are pretty concerned about the ring… the blue image is from an FBI pamphlet
Let’s end this Meme the News on a miraculous journey
This page is synchronized from the post: ‘Meme the News - 6/21/18’


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Ariana Grande snubbed at MTV European Music Awards
Ariana Grande has been snubbed at the MTV Europe Music Awards after failing to win a single prize, despite being nominated in seven categories.
The Grammy award-winning US pop star, who did not attend the event, was among the big losers on the night, alongside Lil Nas X who was nominated in six categories but also went home empty handed.
Billie Eilish, however, took home two gongs, for best song and best newcomer, blowing her fans a kiss in a brief pre-recorded video message.
K-pop superstars BTS, who were not at the event, also scored a double win for best live and biggest fans.
The night was also marked by a performance from NCT 127.
The K-pop boy band became the first from the Korean genre to appear at the annual event, this year held at the FIBES Conference and Exhibition Centre in Seville, Spain.
Taylor Swift, hot from the release of her seventh album Lover, and Halsey were also handed two awards.
The star-studded event featured an impressive roster of performances from the likes of Halsey, Mabel and Spanish singer Rosalia.
The event is returning to Spain for a fourth time after visiting Barcelona in 2002, Madrid in 2010 and Bilbao in 2018.
Dua Lipa kicked off the night with a high-intensity performance of her new single Don’t Start Now.
The British star was joined by a troupe of dancers clad in white body-suits as she sung the disco-tinged track, from her forthcoming untitled album.
Lipa, 24, later sat next to her boyfriend Anwar Hadid, 20, the younger brother of models Bella and Gigi.
The pair have been together since Lipa’s reported split from her former partner, chef Isaac Carew, earlier this year.
Liam Gallagher also made an appearance to collect the inaugural rock icon award.
In his inimitable style, the former Oasis singer told the crowd: “I was here last year. I want to recognise MTV for recognising my brilliance.”
He then closed out the evening with a two-song set including the Oasis track Wonderwall.


F
- The factory interfacepublic class FactoryProvider<F> extends java.lang.Object implements Provider<F>, HasDependencies
public interface PaymentFactory { Payment create(Date startDate, Money amount); }You can name your factory methods whatever you like, such as create, createPayment or newPayment.
constructedType
is a concrete class with an @Inject
-annotated
constructor. In addition to injector-supplied parameters, the constructor should have
parameters that match each of the factory method's parameters. Each factory-supplied parameter
requires an @Assisted
annotation. This serves to document that the parameter
is not bound by your application's modules.
public class RealPayment implements Payment { @Inject public RealPayment( CreditService creditService, AuthService authService, @Assisted Date startDate, @Assisted Money amount) { ... } }Any parameter that permits a null value should also be annotated
@Nullable
.
module
, bind the factory interface to the returned
factory:
bind(PaymentFactory.class).toProvider( FactoryProvider.newFactory(PaymentFactory.class, RealPayment.class));As a side-effect of this binding, Guice will inject the factory to initialize it for use. The factory cannot be used until the injector has been initialized.
public class PaymentAction { @Inject private PaymentFactory paymentFactory; public void doPayment(Money amount) { Payment payment = paymentFactory.create(new Date(), amount); payment.apply(); } }
Assisted
annotation to disambiguate the
parameters. The names must be applied to the factory method's parameters:
public interface PaymentFactory { Payment create( @Assisted("startDate") Date startDate, @Assisted("dueDate") Date dueDate, Money amount); }...and to the concrete type's constructor parameters:
public class RealPayment implements Payment { @Inject public RealPayment( CreditService creditService, AuthService authService, @Assisted("startDate") Date startDate, @Assisted("dueDate") Date dueDate, @Assisted Money amount) { ... } }
AssistedInject
. This triggers a limited backwards-compatibility mode.
Instead of matching factory method arguments to constructor parameters using their names, the parameters are matched by their order. The first factory method argument is used for the first @Assisted constructor parameter, etc.. Annotation names have no effect.
Returned values are not created by Guice. These types are not eligible for method interception. They do receive post-construction member injection.
| 限定符和类型 | 方法和说明 |
|---|---|
F |
get()
Provides an instance of
T . |
java.util.Set<Dependency<?>> |
getDependencies()
Returns the known dependencies for this type.
|
public java.util.Set<Dependency<?>> getDependencies()
HasDependencies
Injector
will be
included in the returned set.getDependencies
在接口中 HasDependencies


Tell me the size in case of a cloth
And the color if you prefer one
Well, where did you find it? It can be a place or a site
And finally how much he will have to pay for it?


Event Location:
Innovation Warehouse
1 East Poultry Avenue
London, , United Kingdom
Abstract:
Excel has been the main tool for presenting data in a digestible form almost forever. The wealth of facilities on top of the basic spreadsheet functions have helped to power Excel to this position, and to keep it there. As well as the bread and butter spreadsheet function, there are facilities for querying databases, filtering data, grouping, charting, pivoting, and many, many more. Even Microsoft have realised Excel's role, adding more data analysis/BI/BA functionality in the latest Excel releases, 2010, 2013 and Office 365. Even with all of this richness, it's still never enough is it? Sometimes it just doesn't do the thing(s) you need it to do now.You want to do something and it is not in the Excel tool-set?  It will be fast-paced and quite intensive, but all of the files will be made available afterwards.
Speaker(s): Bob Phillips,
Abstract:
Many people have been put off using Slicers as they think they consume too much of the screen “real estate”, and are plain ugly. This is very true when used straight “out of the box”, and Microsoft have not made it easy to expose the methods of formatting them into objects which can be very pleasing on the eye as well as effective in filtering data.This session will show users how they can format Slicers, and some of the pitfalls and workarounds when trying to group some data items – especially dates.The session will then continue showing how Slicers can be used in Excel 2010 and later to control multiple Pivot Tables with a single click, as opposed to having to write VBA as in previous Excel versions.It will then include information on how to use Slicers with The Table object, which has been made available since Excel 2013. Coupled with the use of the Aggregate function, this can provide a very useful method of summarising data without having to create a Pivot Table first.
Speaker(s): Roger Govier,
Abstract:
Microsoft Excel provides a huge variety of possible standard charts in the Chart Wizard(Insert | Charts | Recommended Charts). Only a few of them are really useful. Many of themshouldn’t be used at all. Even worse, many useful charts are missing, although they shouldbe provided by default. A closer and critical look at Excel’s standard charts: which ones are useful, whichones are less useful and which shouldn’t be uses at all (and why?)Presentation of a selection of useful non-default charts include: Description of the chart type (Tornado, Waterfall, etc.): what is it good for? Showcase: a real use case for this chart type combination charts / dual axes formulas and NV data series dummy data series invisible data series formatting tricks error barsPossible further use cases for this chart type in business and science.Although none of the presented charts are available in Excel by default, the necessarytweaks and hacks are all based on Exce
Speaker(s): Robert Mundigl,
Abstract:
Topics:• Excel Power pivot models: which paths are available?• Using Excel as prototyping tool and Visual Studio as application building tool.• The difference between applications, made by the SQL professionals and Excel users.• Recognize some of the pitfalls in the migration process from Excel to other platforms.• What will be the role of the Excel user during and after migration to VS.It is very easy to port your Excel Power pivot model to SQL server, Analytic Server and then return the results to Excel of a SharePoint server. Technical spoken no sweat at all, piece of cake. But looking closer at a practical point of view there are many hurdles to be taken in the process. So why should you, as SQL expert, accept Excel Power pivot models as a source of professional applications? What are there benefits? How can you support the Excel user?
Speaker(s): Henk Vlootman,
Abstract:
In this mobile-first, cloud-first era – data is at the intersection – with apps, devices and sensors creating tremendous volumes of data. To get value out of that data, we must be able to reason over it, tap into processing power to quickly analyze it and accelerate the insights, which ultimately lead to better decisions, actions and business results. Companies that put data at the heart of their business operations outperform those that don’t by a significant margin, which we call releasing the ‘Data Dividend’. We will take a walk through the key technologies from PowerBI to AzureML and IoT to show how to start driving your Data Culture.
Speaker(s): Jon Woodward,
Abstract:
This half day session is ticket only.
Speaker(s): Allan Mitchell,
Abstract:
How a Fortune 1000 Silicon Valley data networking equipment manufacturer used all-flash memory storage to consolidate both the number of Data Centers and transformed their business with faster than anticipated RoI and improved business agility.
Speaker(s): Jen Stirrup,
Abstract:
See how the characters from Lord of the Rings can be applied to Business Intelligence. Whether you are a Data Wizard, a Dwarf mining for insights, an Elf creating elegant visualisations or an ordinary Hobbit seeking business enlightenment before second breakfast, BI Office from Pyramid Analytics can help you achieve your quest for insights and timely business information. The Race of Presenting Men: Avi Perez (King Aragorn) Ian Macdonald (Boromir)
Speaker(s): Avi Perez,
Abstract:
You already know that you can accomplish a lot within the Power Query user interface. If you are a data steward, however, you may be asked to deliver complex data sets in Power Query that require some knowledge of advanced functionality, including the M language. This session will examine what these requirements might be, how to implement them, and how best to deploy them to end users. We will cover how to create common types of calculations in M, how to best use functions, calling to web services, and OData data sources, and more. We will also discuss the best way to use Power Query with the rest of the Power BI stack, especially PowerPivot.
Speaker(s): Chris Webb,
Abstract:
Introduction to Power BI
Speaker(s): Jen Stirrup,
Abstract:
This session you will see how SanDisk in a simple way can help you to accelerate your application, why wait for hours to get the response to your query when you can have it in minutes or seconds.
Speaker(s): Jonas Holmgren,
Abstract:
In this session you'll see a how a data literate business person can use predictive modelling to solve business problems using modern tools. Session outline:1. Gain an understanding of the CRISP-DM methodology that makes advanced analytics easier to comprehend.2. Learn how RapidMiner can be used with CRISP-DM to solve a typical business problem3. Take away best practices that maximise your chance of success4. Next steps
Speaker(s): Lee Hawthorn,
Abstract:
Many BI projects aim to tell us “what happened?” but sometimes the more interesting question is “what would happen if?”. To do this we have to generate some plausible scenarios and model our business under these scenarios and then communicate the results effectively. This talk will present one small example of this. We will generate the scenarios using R, an open source language for munging data and stats. We’ll organise the results in a SQL Server database and an Analysis Services cube so that we can compare the different outcomes of each scenario. Finally we’ll use Power View to explore and visualise the results.
Speaker(s): Mark Wilcock,
Abstract:
Today’s Business Intelligence (BI) systems are increasingly perceived as mission critical, but their value is only as good as the quality of data they contain. Learn how you can use Microsoft SQL Server Master Data Services and Profisee’s Master Data Maestro to ensure data quality and improve BI valueDave Lawrence Technical Support Consultant – Profisee Software (UK) Limited
Speaker(s): Dave Lawrence,
Abstract:
Microsoft Finance - Delivering Business Impact with Excel. Come along and find out how Microsoft Finance use Excel and Power BI.
Speaker(s): Jen Stirrup,
This is a list of speakers from the XML Guidebook records. The details and URLs were valid at the time of the event.
Contact: http://www.pyramidanalytics.com
Avi Perez, CTO Avi is CTO of Pyramid Analytics. Avi began his long career in BI, analytics, and enterprise reporting while working as a CPA in banking in Australia and then building a USA based, healthcare informatics and BI platform for the cloud. Avi holds a B.Com from UNSW, Australia, and an MBA from Yale, USA. Ian Macdonald, Principle Technologist Ian has over 25 years’ experience in the Business Intelligence software market, having held senior technical, product management and marketi
LinkedIn: https://www.linkedin.com/in/vlootman
Contact: http://www.vlootman.nl
Henk Vlootman is trainer in Excel and Power pivot to managers throughout the world in the Dutch or English language since 1992. I also do assignments from the industry, partly consultancy and partly direct modelling. I do seminars and congresses. With Michiel Rozema (Rubicon, The Netherlands, I wrote the quot;Practice Book PowerPivot in Excel.quot; At this moment, again with Michiel Rozema I’m finishing a new Power pivot book. I write a monthly blog on Power BI for two different Dutch (financial) e-magazine. I’m manager of the LinkedIn group Power BI Gebruikersgroep. Henk is board member of the Dutch Power BI gebruikersgroep.
Mark is an independent consultant specializing in the analysis, reporting and visualization of financial data. Over the last 20 years, he worked on many systems to measure and monitor financial performance and manage market risks that arise from banking and trading activities. He#39;s the organizer of the London Business Analytics Group, a popular community group that holds monthly talks on topics ranging from Predictive Analytics to Power Query to Personalized Medicine. He blogs at zomalex.co.uk
Contact: http://www.sandisk.com
Sandisk
LinkedIn: http://uk.linkedin.com/in/jenstirrup/
Contact: http://www.jenstirrup.com
Jen Stirrup, Microsoft Regional Director and MVP is a well-known Business Intelligence and Data Visualization expert, author, data strategist, and Master of Business Administration (MBA) student in London. Jen leads a boutique analytics consultancy, delivering strategic advice to companies large and small. Jen has presented in Africa, India, Europe and North America. Jen has presented at Ignite, Techorama, TechEd, PASS Summit, SQLBits, and SQLSaturday events in Europe and the US. She also delivers the MAPA Azure Architects course worldwide with Microsoft team members. Jen was also featured on the Best of PASS Summit 2015 DVD as one of the top 10 speakers. Jen also was awarded PASS prestigious PASSion Award in 2012
LinkedIn: http://www.linkedin.com/in/jonathanwoodward
Jonathan Woodward is the UK Business Lead at Microsoft focused on the Data Platform covering: - Business Intelligence - Analytics - Big Data - Data Science
Contact: http://leehbi.com
Lee Hawthorn is a data-literate Finance professional who is a business analyst at heart. He is often found working with Sales and Marketing to improve top line growth and hacking business data to gain new insights. Lee launched advanced analytics within his organisation and has contributed to many data based projects covering Planning, BI, CRM. His BI scars have since healed since Power Query arrived in his tray.
LinkedIn: http://uk.linkedin.com/in/jenstirrup/
Contact: http://www.jenstirrup.com
Jen Stirrup, Microsoft Regional Director and MVP is a well-known Business Intelligence and Data Visualization expert, author, data strategist, and Master of Business Administration (MBA) student in London. Jen leads a boutique analytics consultancy, delivering strategic advice to companies large and small. Jen has presented in Africa, India, Europe and North America. Jen has presented at Ignite, Techorama, TechEd, PASS Summit, SQLBits, and SQLSaturday events in Europe and the US. She also delivers the MAPA Azure Architects course worldwide with Microsoft team members. Jen was also featured on the Best of PASS Summit 2015 DVD as one of the top 10 speakers. Jen also was awarded PASS prestigious PASSion Award in 2012
Contact: http://www.clearlyandsimply.com
Dr. Robert Mundigl is based in Munich (Germany). He is a Management Consultant based in Europe.Robert has used Excel since 1989 (version 3) and has a deep knowledge of the application itself and VBA programming as well as techniques and best practices of data analysis and data visualization. He contributed a series of Excel dashboard articles on Excel MVP Chandoo’s website chandoo.org, and he blogs at www.clearlyandsimply.com
Contact: http://www.copper-blue.com
This half day session is ticket only.
LinkedIn: https://www.linkedin.com/in/chriswebb6/
Contact: https://blog.crossjoin.co.uk/
Chris Webb is a member of the Power BI CAT team. He is the author of "Power Query for Power BI and Excel" and a co-author of "SQL Server Analysis Services 2012: The BISM Tabular Model", "Expert Cube Development with SQL Server 2008 Analysis Services", and "MDX Solutions with Microsoft SQL Server Analysis Services 2005 and Hyperion Essbase".
LinkedIn: http://uk.linkedin.com/in/jenstirrup/
Contact: http://www.jenstirrup.com
Jen Stirrup, Microsoft Regional Director and MVP is a well-known Business Intelligence and Data Visualization expert, author, data strategist, and Master of Business Administration (MBA) student in London. Jen leads a boutique analytics consultancy, delivering strategic advice to companies large and small. Jen has presented in Africa, India, Europe and North America. Jen has presented at Ignite, Techorama, TechEd, PASS Summit, SQLBits, and SQLSaturday events in Europe and the US. She also delivers the MAPA Azure Architects course worldwide with Microsoft team members. Jen was also featured on the Best of PASS Summit 2015 DVD as one of the top 10 speakers. Jen also was awarded PASS prestigious PASSion Award in 2012
LinkedIn: http://www.linkedin.com/in/visibardd
Contact: https://wessexbi.wordpress.com/
I am an independent consultant based in the UK, specializing in all things Excel, especially delivering BI within Excel. I came to appreciate the power and versatility of Excel as an enterprise tool in the mid-90s when managing the delivery of a data warehouse project. Now a freelance consultant, I specialize in Excel automation and BI delivered via Excel. An 11 year veteran of Microsoft#39;s MVP program, my life mission is to persuade small and medium corporates that data analysis and BI is important to them too, and that Power BI can help then find that information, in a straight-forward and cost-effective manner.
Contact: http://tiny.cc/MVPRogerGovier
Roger Govier is a long-serving Excel MVP, who has been involved in computing since 1978 through MSDOS and Windows and spent a number of years as Commercial Director of a small software house specialising in the Agricultural sector.Since 1996, Roger has operated as an IT Consultant, and has specialised in Microsoft Excel and automating it through VBA for clients all over the world, and ranging from small sub 10 Employee clients, through to large multi-nationals with multi-billion $ turnover.
Contact: http://www.profisee.com
Dave has over 30 years’ experience in providing sales support for data management software vendors, at Profisee he works with customers to build help them unleash the power of Microsoft SQL Master Data Services using Profisee’s Maestro Software. Dave holds a BSc in Mechanical Engineering from the University of Surrey.
The following is a list of sponsors that helped fund the event.


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| UnicodeMessage.java |
1 package com.nexmo.messaging.sdk.messages; 2 /* 3 * Copyright (c) 2011-2013 Nexmo Inc 4 * 5 * Permission is hereby granted, free of charge, to any person obtaining a copy 6 * of this software and associated documentation files (the "Software"), to deal 7 * in the Software without restriction, including without limitation the rights 8 * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 * copies of the Software, and to permit persons to whom the Software is 10 * furnished to do so, subject to the following conditions: 11 * 12 * The above copyright notice and this permission notice shall be included in 13 * all copies or substantial portions of the Software. 14 * 15 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN 21 * THE SOFTWARE. 22 */ 23 24import com.nexmo.messaging.sdk.messages.parameters.MessageClass; 25 26/** 27 * UnicodeMessage.java

 28 * 29 * Represents the details of a unicode text message that is to be submitted via the Nexmo REST api 30 * Unicode messages are required when sending messages to the handset that contain characters that are not 31 * within the GSM alphabet.
 32 * For example, sending messages in Arabic or Chinese

 33 * 34 * Created on 5 January 2011, 17:34 35 * 36 * @author Paul Cook 37 * @version 1.0 38 */ 39public class UnicodeMessage extends Message { 40 41 static final long serialVersionUID =<PHONE_NUMBER>926552344L; 42 43 /** 44 * Instanciate a new unicode text-message request
 45 * This message will be submitted as a unicode 16 bit text message 46 * 47 * @param from the 'from' address that will be seen on the handset when this message arrives, 48 * typically either a valid short-code / long code that can be replied to, or a short text description of the application sending the message (Max 11 chars) 49 * @param to the phone number of the handset that you wish to send the message to 50 * @param messageBody The text of the message to be sent to the handset 51 */ 52 public UnicodeMessage(final String from, 53 final String to, 54 final String messageBody) { 55 super(MESSAGE_TYPE_UNICODE, 56 from, 57 to, 58 messageBody, 59 null, 60 null, 61 null, 62 true, 63 false, 64 null, 65 null, 66 0, 67 null, 68 null); 69 } 70 71 /** 72 * Instanciate a new unicode text-message request, exposing all of the available parameters, and optionally requesting a delivery notification
 73 * This message will be submitted as a unicode 16 bit text message 74 * 75 * @param from the 'from' address that will be seen on the handset when this message arrives, 76 * typically either a valid short-code / long code that can be replied to, or a short text description of the application sending the message (Max 11 chars) 77 * @param to the phone number of the handset that you wish to send the message to 78 * @param messageBody The text of the message to be sent to the handset 79 * @param clientReference This is a user definable reference that will be stored in the Nexmo messaging records. It will be available in detailed reporting / analytics 80 * In order to help with reconcilliation of messages 81 * @param statusReportRequired If set to true, then a delivery notification will be requested for this message delivery attempt. 82 * Upon receiving notification of delivery or failure from the network, the Nexmo platform will submit a notification to the url configured in your 83 * Nexmo REST account that represents the outcome of this message. 84 * @param messageClass (Optional) The message class that is to be applied to this message. 85 * @param protocolId The value of the GSM Protocol ID field to be submitted with this message. Ordinarily this should be left as the default value of 0 86 */ 87 public UnicodeMessage(final String from, 88 final String to, 89 final String messageBody, 90 final String clientReference, 91 final boolean statusReportRequired, 92 final MessageClass messageClass, 93 final Integer protocolId) { 94 super(MESSAGE_TYPE_TEXT, 95 from, 96 to, 97 messageBody, 98 null, 99 null, 00 clientReference, 01 true, 02 statusReportRequired, 03 null, 04 null, 05 0, 06 messageClass, 07 protocolId); 08 } 09 10} 11


I’m Mariana Nascimento, a Brazilian product designer that works on the intersection of .
During the last 8 years, I have shifted from graphic to user experience design, which reflects my passion for talking to real people and understanding their needs.
Currently, I am simplifying financial services at Nubank, the largest independent digital bank in the world[1] with over 20 million users.[2]
In practice, my team and I apply qualitative research methods to uncover common pain points. Then, I try to solve these problems by designing interfaces that are clean and easy-to-implement.
Before we launch a new product or improvement, we validate if our design actually works. To do so, I conduct face-to-face interviews with real customers. Now, of course, we are doing them remotely.
Most of this work is confidential, but here are a few selected .
Education
In Rio de Janeiro, I studied graphic design at Senac, which offers a course focused on the professional design practice.
Also, I took a two-year specialization course on digital design, offered by ESPM, in addition to a few short courses on UX and UI design.
More recently, in São Paulo, I have earned a Design Sprint certificate after an intense course at Mergo.
Currently, I am learning more about qualitative research through a certified online course, offered by MIT and edX, focused on how conversational interviews can be used to produce rich insights.


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Projects
Physically Based Simulations
BRDF Explorer
A tool to experiment and test different models of brdfs for PBR rendering. Here you can choose between different implementations for the normal distribution function, joint masking-shadowing function and Fresnel reflectance components. Some parameters can be controlled as well.
Comming up
- Disney diffuse model
- Anisotropic models
GLSL Editor
A simple shader editor tool that provides a convenient and quick way to test shader ideas. Here you can edit shader files and see the results in real time.Everything can be done inside the application screen, from code editing to uniform value setting. Code uniforms are parsed and the GUI is updated automatically. Here is the list of current features:
- Continuous compilation (error listing)
- Save/Load shader files (including a configuration file containing values of light/material)
- Visual cues for debugging (point light, directional light)
- Custom uniforms support (you can create uniforms (uniform arrays are supported as well))
Comming up
- Add other useful uniforms: time, mouse position, camera position
- Pass other mesh information to the shader as well.
- Incorporate ImGuizmo.
- Skybox/sphere allowing environment mapping.
- Shadows (add a floor to the scene).
- Save custom uniform values in config file.
- Load obj files.
Rust Experiments
Small projects to help me get involved with the rust language. Right now I only have one :)
In order to get into rust I started implementing a ray tracer following Peter Shirley’s ray tracing book series.
I’ve also been packing everything I do into a set of libraries that eventually serve me as frameworks to new projects (and hopefully help anyone who might use them).
hermes
Hermes is a C++ utility lib containing a wide range of classes and algorithms. It serves as a swiss-knife for several types of projects.
Most of hermes features are also implemented in CUDA
, which can be optionally enabled.
Currently hermes comprises the following pieces:
-
Geometry: points, vectors, matrices, transformations, intersection tests, quaternions, etc;
-
Storage: memory blocks, multi-dimensional arrays, array of structures, texture memory regions;
// Example of an Array of Structures usage
hermes::AoS aos;
auto vec3_field_id = aos.pushField<vec3>("v");
auto f32_field_id = aos.pushField<f32>("f");
aos.resize(4);
auto acc = aos.accessor();
for (int i = 0; i < aos.size(); ++i) {
acc.valueAt<vec3>(vec3_field_id, i) = {1.f + i, 2.f + i, 3.f + i};
acc.valueAt<f32>(f32_field_id, i) = 1.f * i;
}
- Numeric: interpolation, differential operators, staggered grids, finite difference matrices;
- BLAS: Linear Algebra stuff, PCG, RBF;
- Structures: octree, BVH, half-edge meshes, morton code ordering;
- Common: file system (bash-like) methods, string utils, reduce methods, marching cubes;
and other utilities such as thread pools, colored console output, memory dumper, fast sweep algorithms, etc.
Comming up
- color struct fields in a memory dump inside the console.
circe
Circe is a graphics engine written on top of OpenGL (and Vulkan). Initially, the goal was just to produce some lib to help me on building visualizations of my research data, but now there is a lot more I can do with it than I previously expected :)Vulkan
Shadows
GPU picking
instance picking
Deferred Rendering
That is what Circe can provide for now:
- UI: imgui integration, gizmos, trackball, reference grids;
- Graphics: shader management, compute shaders, uniform buffers, post effects, shadow map;
- IO: texture, viewport displays, text, buffers, render buffers, framebuffer access;
and other useful utilities such as color palettes, mesh loading, primitive intersection, mouse picking, BVH, etc.
Comming up
- improve the scene graph.
- add procedural methods for terrain generation
odysseus
Odysseus is an ongoing project, on its early steps, of a data driven game engine.Comming up
- Pool Allocator
- Stack and Double Stack Allocators
- mem singleton
- add memory contexts


Represents
Is the client still connected?
Send a server-sent-event to the client as part of a "text/event-stream" response
Generated using TypeDoc
Represents


Notes For mpily
About
This is a sort of rough notebook where I keep rough notes and short cuts for stuff I usually forget. Feel free to go through them. Though they are highly tailored for my use and thus might not suit you as well.
- Version: 1.0
- Author: Harnish Design
- Created: 8 April, 2020
- Update: 12 May, 2020
If you have any questions that are beyond the scope of this help file, Please feel free to email via Item Support Page.
Some basic Git and GitHub Commands
Below are some of the common Git Commands:
-
git init
-
git add 'file or directory name'
-
$ git commit -m "comit message in quotes"
-
$ $ git push "remote_URL/remote_name" "branch"
-
$ $ git pull "branch_name" "remote_URL/remote_name"
-
$ $ git merge "branch_name"
-
$ $ git checkout -b "new_branch"
$ $ git checkout "branch_name"
While in the directory you wish to make a git repository the above command will initialize a git repository in that directory.
Adds files in the to the staging area for Git. Before a file is available to commit to a repository, the file needs to be added to the Git index (staging area). There are a few different ways to use git add, by adding entire directories, specific files, or all unstaged files.
Record the changes made to the files to a local repository. For easy reference, each commit has a unique ID.
Sends local commits to the remote repository. git push requires two parameters: the remote repository and the branch that the push is for.
Is used to get the latest version of a repository.
integrates branches together.
Used to start working on a different branch. The -b option creates a new branch.
MultiFactor Authentication
What is MultiFactor Authentication
It is an electronic authentication method in which a user is granted access to a website or application only after successfully presenting two or more pieces of evidence (or factors) to an authentication mechanism: knowledge (something only the user knows), possession (something only the user has), and inherence (something only the user is). MFA protects the user from an unknown person trying to access their data such as personal ID details or financial assets.
Why Use MultiFactor Authentication
Simple one step verification is just not enough. Not even for Google. Google admitted that hackes steal about 250000 web logins each weed In MFA we aren't doing away with passwords and logins, we instead are layering another layer of information. For example someone could link a cell phone to the account and then during login they are asked to provide evidence that they are the owner through receiving a message from the cell phone.
Who is Using MultiFactor Authentication
- At the top of the list is definitely Google. In fact Google has been using it since 2011
- Git Hub is also moving to 2FA. In fact you can configure 2FA on your Git Hub account by following these steps
- Microsoft Azure. Obviously given how valuable their data isYou can read more about it here
Types of MultiFactor Authentication
- Time Based One Time Password: Automatically generates an authentication code that changes after a certain period of time. You can use apps such as :
- Two Factor authentication using text message:
- Using a Security Key: Can use finger Print or Window Hello.
IOT Communication Protocols
We know that at the foundation of IoT is the communication aspect. The sending and receiving of information. The question at hand is how to do this. The following Internet Protocols can be used to accomplish this task:
-
HTTP
This is one of the simplest means. In this case the controller sends information to a webpage. In HTTP we use the POST and GET routines in order to achieve the communication. Taking an example of a NODE MCU that is used to keep a record of the weather in a particular location, the MCU will 'POST' the data to a web server/API and receive an OK HTTP response from the server. An Outline of this process may look like: The output may end up looking like this: Unfortunately HTTP is not very secure and thus for crucial applications such as in hospitals is not appropriate.
-
UDP
User Datagram Protocol is one of the core members of the internet protocol suite. It allows computers to send messages (datagrams) to other computers in an IP network. UDP uses a simple connectionless communication model with a minimum of protocol mechanisms. It has no handshaking dialogues, and thus exposes the user's program to any unreliability of the underlying network; there is no guarantee of delivery, ordering, or duplicate protection. UDP is suitable for purposes where error checking and correction are either not necessary or are performed in the application; UDP avoids the overhead of such processing in the protocol stack. Time sensitive applications often use UDP because dropping packets is preferable to waiting for packets delayed due to retransmission, which may not be an option in a real-time system. UDP is also advantageous in that it allows clients to communicate to each other without the need of a web server.
-
TCP
The main characteristic of TCP is that a connection between client and server is established before data is sent. The figure below shows the 3-way handshake between 2 hosts P and Q. A 3 way handshake is carried out in which connection between the 2 hosts is established. Because of this there is less data loss. Also, this 3 way handshake can be used to improve security over the network.
>
MICROPORCESSORS AND MICROCONTROLLERS
A microcontroller is essentially a small computer on a chip. And as such it has memory, a processor and I/O. Below is the architecture of the Atmega32.A microprocessor on the other handis a computer processor wherein the data processing logic and control is included on a single integrated circuit, or a small number of integrated circuits. The microprocessor contains the arithmetic, logic, and control circuitry required to perform the functions of a computer’s central processing unit. Below we have the block diagram of the Z80microprocessor.
| Microcontroller | Microprocessor it Uses |
|---|---|
| Atmega328 | 8-bit AVR |
| ESP8266 | Tensilica Diamond Standard 106Micro (aka. L106) @ 80 MHz (default) or 160 MHz |
Companies in Kenya that apply Microprocessors and microcontrollers
- Africa's Talking
- Gear-Box
- Numeral-IoT
- Twiga Foods
- Coco Networks
- EABL
- Apollo Agriculture


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WITNESS LIST Nominations Committee February 5, 1997-9:00A University of Tx. Board of Regents For: A.R. Sanchez (himself), Laredo A.W. Riter Jr. (himself), Tyler Patrick C. Oxford (himself), Houston Rita C. Clements (herself), Dallas


There is almost no attempt to actually visualise anything. Even the pie charts are ridiculous, slices of the same conceptual pie are shown in their own individual pies! You’d digest this information more quickly and gain more insight by reading these numbers from a spreadsheet.


Arrest made in Māngere assault case
by New Zealand PolicePolice have arrested a man in connection with an alleged serious assault on a man in Māngere Town Centre on 20 October.
A 23-year-old man has been arrested and will face a charge of wounding.
He is due to appear in the Manukau District Court today.
Detective Senior Sergeant Warrick Adkin, Investigations Manager for Counties Manukau West, says the arrest follows a thorough enquiry by investigators.
“Police would also like to thank those members of the public who came forward with information after the case featured on the Police Ten 7 programme last night,” says Detective Senior Sergeant Adkin.
ENDS


The following article was written for and published by the annual newsletter of Dept. of Physics, IIT Bombay in collaboration with Insight, the student media body of IITB, in the Autumn semester of my freshmen year (2015). It is aimed at providing a brief info to the latest advancements in the field of quantum computing and what lies ahead.
A New Hope
Our story begins with a team of researchers at The University of New South Wales(UNSW), Australia, led by Andrew Dzurak who have successfully accomplished the making of a two qubit logic gate in silicon, which is a crucial hurdle overcome in making quantum computers a reality. “What we have is a game changer,” says team leader Prof. Dzurak.
“We’ve demonstrated a two qubit logic gate the central building block of a quantum computer and, significantly, done it in silicon. Because we use essentially the same device technology as existing computer chips, we believe it will be much easier to manufacture a fullscale processor chip than for any of the leading designs, which rely on more exotic technologies.” The key idea behind the working of the UNSW team has been the morphing of normal transistors, into defining quantum bits or ‘qubits’, by ensuring that each transistor has a single electron associated with it, and representing the binary equivalent of numbers 0 and 1 by spin of the electron.
The sentence makes sense quite ephemerally, so let’s deconstruct the concept in lyman’s language and restore freedom to our bound curiosity…
The Very Begining
Essentially the concept of quantum computing involves use of quantum bits or ‘qubits’ instead of conventional bits in boolean algebra, that can be coupled in a scalable manner to make up one and two qubit logic gates. The numerous physical realisations of qubits, single photons, trapped ions, silicon and semiconductor quantum dots, single defects or atoms in diamond etc. have to be sufficiently fault tolerant and conserved under time evolution, with discrete and spaced eigenvalues that can be mapped onto an effective spin 1/2 system.
The ideation for representing qubits as the spin of an electron was primarily proposed in 1968, and sparked up with eminent physicist Richard Feynman proposing the possibility of a quantum computer in 1982.
That which makes all the difference
The edge that a quantum system has over the conventional is the property of entanglement and superposition of states, i.e. a qubit’s existence is governed by superposition of the two basis states that denote conventional bits 0 and 1, mathematically, a linear combination.
The bloch sphere shown in the article, is a representation of a qubit with associated probability amplitudes, with the two basis states represented in standard Dirac notation (The braket notation). Thus considering two interacting qubits, four possible combinations yield, each weighed by a coefficient that denotes the probability of existence of the system in that state. To specify a combination of two conventional bits, two information are coded, the value of both the bits, while for the quantum system four information, the four coefficients. Thus the information represented by an ‘n’ qubit system is exponentially large in comparison with its classical counterpart, the former is essentially two raised to the latter.
But the world is not all cupcakes and rainbows
The state of superposition cascades down to one of its basis states on observation, termed as the collapse of the governing Schrodinger wave function, essentially leading to us losing our data that boasted of exponentially large capacities to normal bit sized information. Thus, here lies the spinner, specific algorithms have to be applied to extract specific information out of a quantum system. Many such brilliant minds have risen to the occasion, among them, notably and famed are Peter Shor (Shor’s Algorithm, 1994), Daniel Simon (Simon’s Algorithm, 1994) and Lov K. Grover (Grover’s Algorithm, 1996).
Let’s take a look at what specific information can be extracted out -
Shor’s algorithm is a quantum algorithm that addresses the problem of discrete logarithms and integer factorisation, a problem so intricate that our public key cryptography schemes like the RSA rely on the computational intractability in factoring large numbers for the most advanced classical computers.
Simon’s algorithm deals with the computational analysis of decision tree complexity and solves the problem exponentially faster than any known classical algorithm.
Grover’s algorithm addresses database search, i.e. given a unique output produced by a black box function (A function with unknown formulation but known mapping) it figures out the input with high probability, addressing the problem in quadratically fewer queries than classical.
Many more such algorithms exist, attacking with brute force, the issues that lie beyond the scope of classical computers. Another problem is that many of the quantum algorithms give probabilistic solutions, solutions with probability very close to one, and which can be improved upon by repeated iterations but nevertheless its probabilistic. Many others however, are fully deterministic and hence efficacious.
The quantum computers can only respond to specific algorithms and tasks exponentially efficiently than classical, thus, they are not the substitute for them, but an aid, for more technological and advanced sector. Not every task that a normal personal computer does can be effectively performed with them. So wish the genie to show you a movie, and quantum computer would be useless trash. Wish to crack security codes for all online credit transfers, ye ol’ quantum computer would watch the world burn as it decrypts transactions.
Further, not-so-farther difficulties ahead
A big hurdle now is to remove decoherence from the system, isolating the system from the surroundings, cutting down its interactions that make the system decohere, and to do so economically and feasibly. Decoherence is irreversible and nonunitary and thus must be controlled if not eradicated. Currently superconducting qubits can be configured to remove setting in of significant decoherence in physically avoidable time lag, which typically ranges between the order of nanoseconds to seconds at low temperatures, by cooling the qubit to 20milli kelvin or lower temperatures.
Another problem that is now faced is to scale this system up to vast numbers of stable qubit registers or “q-registers”, quantum mechanical analogues of classical processor registers.
Unless a very efficient way is developed, optimum working is an impossibility. In this direction, Prof. Dzurak notes that the team has “recently patented a design for full scale quantum computer chip that would allow for millions of our qubits, all doing the same kind of calculations we’ve just experimentally demonstrated.”
The UNSW team’s research breakthrough has attacked three of the major requirements -
1) qubits that can be initialised to arbitrary values,
2) qubits with successful readout fidelities,
3) a universal CNOT quantum gate, faster than the decoherence time of the system,
with the fabrication process compatible with standard Complementary Metal Oxide Semiconductor (CMOS) technology that already exists
for manufacturing classical Si based semiconductor chips.
Future experiments by this team will include improvements to facilitate full two qubit tomography.
Improvement by lowering the sensitivity to electrical noise is also targeted.
Though the two qubit system represents the smallest scalable system so far, it is consistent with current transistor sizes, offering the prospect of realizing a largescale
quantum processor using the same silicon manufacturing technologies that have enabled the current information age.
And lastly, on a more tender note, “Computers are physical objects, and computations are physical processes. What computers can or cannot compute is determined by the laws of physics alone.” – David Deutsch
So we mustn’t lose faith. More breakthroughs are yet to arrive!
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--- layout: post authors: ["Bill Mills"] title: "Reflections on Claremont" date: 2014-06-19 time: "21:00:00" tags: ["Bootcamps", "Claremont Colleges"] ---
The Claremont Colleges bootcamp just wrapped a couple of hours ago, and judging from my pile of happy sticky note responses, I think we nailed it pretty good. Things were a bit fast on the first day of intro shell and Python, but I think we hit something pitch perfect for day two on intermediate Python and Git. As this Python-heavy workshop progressed, some questions started coming into focus from student responses, discussions with instructors and organizers, and examinations of just how to teach this ascendent skill in scientific computing. To be clear: I have never taught our Python material, and I consider myself a fairly casual Pythonista. This is a debate that the masters need to consider, but I'm hoping here to use my agnostic outsider's perspective to help set the conversation up.
Two major axes span the space of teaching Python, and actually they're just the same two big questions found in teaching anything: what to teach, and how to teach it. But these old pedagogical chestnuts really resonate with the practice of teaching Python, because the place that Python's ecology has evolved to has made them pressing and polarized matters.
First up: what to teach. I've had the privilege of watching two awesome deliveries of the Python material at the two bootcamps I have taught, but excellent as they were, they could not have been more different. The Claremont Python lecture began from a place of absolute fundamentals—what is a variable type, what is assignment, what is an operator—those omni-linguistic channels of thought that shape programmatic logic and structure everywhere. Approaching the problem not just as basic Python but basic programming laid down a bulletproof foundation that moved gradually enough and depended on little enough chuft that almost everyone could keep up, even with a huge and varied group like we had at Claremont.
Python in Victoria earlier this year was a different animal altogether. That workshop was heavily tools oriented—lots and varied plotting, calculating some simple statistics from datasets using things like numpy and matplotlib (as I recall), and heavy use of the IPython Notebook. Actually, I'll never forget one quasi-magical thing that happened during the Victoria Python lecture; it was time to introduce for loops, and I expected the instructor would get bogged down picking apart syntax and trying to hash out in exact detail the guts of this pattern that students wrestle with the first time they see it; but instead, they just sailed right through it, talking about it like it was second nature—and the students got it! Somehow they assimilated this new idea with barely a speedbump, and just rolled right along playing with plotting tools. Waltzing through the chuft and getting students to get their hands dirty with useful tools right away seems so compelling and engaging, especially when they walk out of the room agog with possibility, but one person made a point I can't shake: how demoralizing is it for students when the next day they can't use any of the tools they were so excited by, because they don't have enough fundamentals to proficiently wield them?
Anyway, the proof is in the sticky notes, and much to my surprise, there wasn't really much of a criticism of pace or level of the Python material at Claremont on day one—the comment that got repeated a bunch of times, was "I wish there had been more hands on examples and puzzle problems to work on". So where is that shining kernel of value here—in the self-actualization and engagement of hands-on activity, or in the exciting promise of all the cool things the world of Python has to offer? Is it even possible to make engaging examples out of the tiniest nuts and bolts of programming, and can we float the nifty packages while imparting enough fluency that students can drive them on their own? The "what to teach" axis of this problem space can be reskinned as a slider from 'foundations' to 'tools'; finding the happiest home therein is to my mind an open question.
The second axis was of course, "...and how to teach it". The choice of vehicle for how to introduce Python seems to me like a pretty crowded room. You've got your standard vanilla.py to run at the bash prompt; you've got your command-line IPython shell; you've got your IPython Notebook; and you've got your web-based Python environments—and each one has its own virtues and pathologies. Where we really ran afoul of this embarrassment of riches at Claremont, was when we tried to use scripting and the interactive shell all at the same time. For many of these students, this was their first exercise in anything REPL, and their first dive into raw text document creation; all these boxes with nothing but text looked kind of the same to them after a while, and it showed in the questions and comments. Many of the helper questions during the day boiled down to students getting confused between text editor, IPython prompt, and bash prompt, and that same confusion was explicitly called out in the sticky note feedback at the end. It was glaring clear that we needed to clear the air, and give the students something solid to focus on, instead of asking them to rapidly switch their thinking from scripting to bashing to interactively issuing Python commands—all things they had encountered for the first time in the last couple of hours.
After this experience, the IPython Notebook's star seemed to be rising. Here is a one hundred percent contained environment where code is entered inline and results are delivered immediately afterwards both spatially and temporally (an instant and context-heavy feedback that is so key for learning). But problems lurk here too. As I was helping for the second Python lesson at Claremont (which used the notebook exclusively), at least half the strategies I gave boiled down to "hit run all and it'll probably be okay". Students were getting lost in the nonlinear state machine that the notebook implicitly creates, without getting a chance to get a solid grasp of what that meant or even that that was the case. We were able to keep on rolling just by re-running every cell, but there wasn't time for the students to really reflect on what that was all about. All this was, of course, after scrambling to get everyone's notebooks working in the first place; in terms of overhead, the notebook is an aircraft carrier compared to the log raft of a script to run at the command line—immensely powerful but sometimes tricky to bring together.
It wouldn't be a post from me if I didn't consider an idea probably no one will like: what if we cut way down on the big guns, and stuck to a script-and-execute model? This would not only eliminate the tragedies of getting all the IPython and Notebook stuff working for everyone, but would start building the muscle memory of writing programs and running them at the command line, which is much more reflective of the day-to-day trade of building software. Getting some of these extra platforms out of the way might make room for fundamentals as well as exciting and powerful package and tool demonstrations, and keep the whole process much more focused, which is one thing we absolutely need to do.
And yet, there is absolutely no pedagogical equal for immediate feedback, which is something the script-and-run model is slow to yield, while IPython nails it cold. So as a middle ground, what about an IPython Notebook where we encourage students to run the whole book each time they added to it, and maybe take some time to point out how stuff gets weird if you execute cells out of order. This isn't too far a cry from building a complete and consistent script, it keeps the student's attention all in one place, and it provides compelling immediate feedback; set it up so there's a 20 minute example at the start that is non-fatal to miss for those still struggling to get the notebook up, and we might have a way through the crowded room. That's one untested strategy—but all told, we've got another slider to adjust in our approach to teaching Python: rock-solid programs, or dynamic interactive environments?
Where you make contact with the dartboard of content vs. style will largely boil down to your priorities and personal flare; since the full range of these options is valuable, our goal should not be to pick winners and losers, but to pull in the best of all of what's out there. What the data seems to be showing after this latest round, is keep your platform focused, and keep it very hands-on.


Project file views
Projects files and elements are displayed in the C/C++ Projects view and in the ProjectExplorer view.
C/C++ Projects view
Displays, in a tree structure, only elements relevant to C and C++ projects. In this view you can do the following:
- Browse the elements of C/C++ source files
- Build Targets
- Create new projects, classes, files, or folders
- Import or Export files and projects
- Manage existing files (cut, paste, delete, move or rename)
- Open files in the editor view
- Open projects in a new window
- Refactor
- Restore deleted files from local history
- Search
Project Explorer view
The Project Explorer view provides a hierarchical view of all the resources in the workbench, not just your C/C++ resources. From this view, you can open files for editing or select resources for operations such as exporting.
Right-click any resource in the Project Explorer view to open a pop-up menu from which you can perform operations such as copy, move, create new resources, compare resources, or perform team operations. For a description of what each menu item does, select an item and press F1.
The Project Explorer view is provided by the Eclipse Platform. See the Workbench User Guide for more information.
CDT Projects
Working with existing code
Creating a project
Creating a project via a project template
Working with C/C++ project files


Welcome to Trash Talk
An Open Oakland Initiative
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### shell 'shell.html' '{{siteName}} - Try It Out'
{{siteName}} will work with most web pages. To try it out, simply enter a URL in the form below and hit Go. {{siteName}} will add links to the page at that URL and then display it.


Modern Space, a Professional Architectural firm and Exterior & Interior Designing Company was started in the year 2004 to present innovative ideas in the field of Exterior and Interior Design at Tirunelveli. Over the years we have designed and executed several prestigious and challenging projects at Tirunelveli, Thoothukudi,Nagercoil,Tenkasi. We have the one of the best Architects in Tamilnadu.
Read MoreA team that works with unwavering focus and dedication to accomplish each task
To maintain the highest levels of professionalism, integrity, honesty
We strive for professional excellence to the highest standards possible consistent with the goals of the project.
We dealing all types of building construction works. Also providing free consulting for clients.
We Offering a Quality Services to our Customers of all Landscape Garden Maintenance.
We are a team of passionate interior designers and one among the top home interior designers in thirunelveli.


DataBOOM: the canon for data science
1
Welcome
2
How to make the most of this course
I Core theory
3
Principles of data science
4
Visualizing data
5
Writing about data
6
Data ethics
II Getting started
7
Setting up
RStudio
8
Running R code
9
Using
RStudio
and
R
scripts
10
Variables in
R
11
Structures for data in
R
12
Calling functions
13
Base plots
14
Packages
15
Basics of ggplot
III Working with data in R
16
Importing data
17
Dataframes
18
Data wrangling
IV Exploring & analyzing data
19
Exploratory Data Analysis
20
Significance statistics
21
Displaying data
V Creating your own dataset
22
Managing project files
23
Formatting your own data
24
Reading Excel files
25
Reading GoogleSheets
26
Reading online data
VI Your R tool bag
27
Joining datasets
28
for
loops
29
Writing functions
30
Working with text
31
Working with dates & times
32
Working with factors
33
Cleaning messy data
34
Matrices & lists
35
Pipes
36
Exporting data & plots
VII Interactive dashboards
37
Intro to Shiny apps
38
Shiny dashboards
39
Data entry apps
VIII Databases
40
Introduction
41
Platforms
42
Alternatives
43
Practices
IX Documenting your work
44
R Markdown
45
Reproducible research
46
Automated reporting
47
Formatting standards
X Version control and teamwork
48
What is version control?
49
What is Git?
50
Standard git operations
51
A git workflow
52
Other git platforms
XI Writing about data
53
Types of writing
54
Elements of style
55
Sections of a report
XII Creating websites
XIII Advanced skills
56
Mapping
57
Geographic computing & GIS
58
Statistical modeling
59
Apply family
60
Iterative statistics
61
Iterative simulations
62
Image analysis
63
Machine learning
64
Template
References
Databrew LLC
DataBOOM: the canon for data science
Module 2
How to make the most of this course
(Make sure you involve pizza.)


OfficePages
My Profile
My Tasks
Settings
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My Profile
My Tasks
Settings
Log out
My Profile
My Tasks
Settings
Log out
Dashboard
Folder
Upload Folder
Files
Upload File
Recycle Bin
Log out
Folder Name
Create


To prevent users accidentally becoming lost, the navigable area can be limited with the Viewport:limitTo method.
Viewport:limitTo


| Interface | Description |
|---|---|
| IndexedProducer<A extends Indexed> |
A factory interface for
Indexed objects. |
| ReferenceProvider |
| Class | Description |
|---|---|
| IndexedComparator<I extends Indexed> |
Comparator for Indexed objects
compares length of code in preference to value of string.
|
| IndexedDataCache<K,D extends Indexed> |
DataCache for Indexed types.
|
| IndexedReference<I extends Indexed> |
A lightweight class that holds the id of an Indexed type
and enough information to create the target object.
|
| IndexedReferenceDataCache<I extends Indexed> |
A DataCache keyed by IndexedReference objects.
|
| IndexedReferenceFormat |
Table format form converting reference fields into
object identifier strings.
|
| IndexedTypeProducer<T extends Indexed,F extends IndexedProducer<T>> |
TypeProducer to make
Indexed objects from an Integer field. |
| LazyIndexProducer<A extends Indexed,F extends IndexedProducer<A>> | |
| ReferenceComparator |
A Comparator that sorts
IndexedReference objects by numerical order. |


{{action}} Student Exam Result
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Total
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DeepDrummer Experiment
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Code Ninjas
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Man must explore, and this is exploration at its greatest
Problems look mighty small from 150 miles up
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{% extends "base.html" %} {% block content %}
| M.S. | Johns Hopkins University | May 2013 |
| Engineering Management | ||
| GPA: 3.88 | ||
| B.S. | University of California, Los Angeles | Jun 2012 |
| Bioengineering | ||
| GPA: 3.38 | ||
Accenture Federal Services
Jun 2013 - Present
Business & Technology Consultant
San Francisco, CA
Department of Bioengineering, UCLA
Jun 2011 - Jun 2012
Undergraduate Research Associate | P.I.: Dr. James Dunn
Los Angeles, CA
Eastdil Secured
Jun 2010 - Jun 2011
Information Technology Intern
Santa Monica, CA
| Computer Programming | ||
| Advanced | SQL, Oracle 12c Performance Tuning | |
| Proficient | PL/SQL, HTML | |
| Novice | Java, Python, Unix, Amazon Web Services | |
| Systems Integration | ||
| Proficient | Agile, Scrum, Requirements Analysis/Development, Use Case/User Story Development | |
| Novice | Process Analysis and Modeling/Design, Functional Design, Database Design | |
| Business Implementation | ||
| Novice | Business Process Design, Change Enablement, Customer Relationship Development, Project Management, Proposal Development |
Johns Hopkins University Recruitment | Accenture
Sep 2013 - Jan 2015
Center for Leadership Education Recruitment Lead
DC Analyst Action Team | Accenture
Sep 2013 - Jan 2015
Community Service Co-Lead
Hopkins Biotech Network | Johns Hopkins University
Nov 2012 - May 2013
Director of Events and Marketing
Bay to Breakers Volunteer Lead | Accenture
Mar 2016 - May 2016
Led 50 Accenture volunteers over three days at the 2016 Bay to Breakers 12k
Ronald Reagan Medical Center Volunteer | UCLA
Sep 2011 - Jun 2012
Patient escort volunteer: 100+ hours transporting patients and observing procedures
New Salvation Ministries Volunteer | Skid Row, Los Angeles, CA
Sep 2010 - Jun 2012
Organized and distributed food monthly to homeless at the Union Rescue Mission
Campus Crusade for Christ | UCLA
Sep 2010 - Jun 2012
Participated weekly in Real Life Meetings, Bible study, and helped lead Safe Rides
Biomedical Engineering Society | UCLA
Sep 2008 - Jun 2012
Participated in networking, informational, and social events
Sigma Chi Fraternity, Delta Eta Chapter | UCLA
Sep 2008 - Jun 2012
Participated in brotherhood events, including philanthropic and recruitment events
Eagle Scout | Troop 543, Orange, CA
Aug 2003 - Jun 2008
Project: Refurbished a section of Santiago Oaks Regional Park that burned in a wildfire
W.S.E. Deans Tuition Fellowship | Johns Hopkins University
$25,000 given to applicants demonstrating a strong penchant for engineering
Undergraduate Research Fellows Program | University of California, Los Angeles
$2,000 given to support students excelling in undergraduate research


Copies the text of a
String
concatenation to the system clipboard. This can be useful, for example, when you have a multi-line SQL query in your code split into concatenated lines that you need to copy to an external application.


Topics:
addChild
, and
contains
value
property and a
children
array.
addChild(value)
should accept a value and add it to that
node’s children
array.
contains(value)
should return true
if the tree
or its children the given value.
children
array use
new Tree(value)
to create the node.
Tree
class inside of itself.insert
, contains
,
depthFirstForEach
, and breadthFirstForEach
.
insert(value)
inserts the new value at the correct location
in the tree.
contains(value)
searches the tree and returns
true
if the the tree contains the specified value.
depthFirstForEach(cb)
should iterate over the tree using
DFS and passes each node of the tree to the given callback function.
breadthFirstForEach(cb)
should iterate over the tree using
BFS and passes each node of the tree to the given callback function
(hint: you’ll need to either re-implement or import a queue data
structure for this).
addNode
, contains
,
removeNode
, addEdge
, getEdge
, and
removeEdge
addNode(newNode, toNode)
should add a new item to the
graph. If toNode
is given then the new node should share an
edge with an existing node toNode
.
contains(value)
should return true if the graph contains
the given value.
removeNode(value)
should remove the specified value from
the graph.
addEdge(fromNode, toNode)
should add an edge between the
two specified nodes.
getEdge(fromNode, toNode)
should return
true
if an edge exists between the two specified graph
nodes.
removeEdge(fromNode, toNode)
should remove the edge between
the two specified nodes.
Graph
class that searches through the
graph using edges. Make this search first as a depth first search and
then refactor to a breadth first search.


Loading...
Computed Observables
< Back To DOCS
Purpose
Sample: computedObservables
HTML
Result
{{myValue}} {{$fizzbuzz$}}
reset
plus one
minus one
times two
half
Firebase emulator
myValue:
< Back To DOCS


Tinder is an API for interfacing with Campfire, the 37Signals chat application.
Example
campfire = Tinder::Campfire.new 'mysubdomain'
campfire.login<EMAIL_ADDRESS>'mypassword'
Create, find and destroy rooms
room = campfire.create_room 'New Room', 'My new campfire room to test tinder'
room = campfire.find_room_by_name 'Other Room'
room.destroy
Speak and Paste
room.speak 'Hello world!'
room.paste File.read("path/to/your/file.txt")
Listening
room.listen
#=> [{:person=>"Brandon", :message=>"I'm getting very sleepy", :user_id=>"148583", :id=>"16434003"}]
# or in block form
room.listen do |m|
room.speak 'Welcome!' if m[:message] == /hello/
end
Guest Access
room.toggle_guest_access
room.guest_url #=> http://mysubdomain.campfirenow.com/11111
room.guest_invite_code #=> 11111
Change the name and topic
room.name = 'Tinder Demo'
room.topic = 'Showing how to change the room name and topic with tinder…'
Users
room.users
campfire.users # users in all rooms
Transcripts
transcript = room.transcript(room.available_transcripts.first)
#=> [{:message=>"foobar!", :user_id=>"99999", :person=>"Brandon", :id=>"18659245", :timestamp=>Tue May 05 07:15:00 -0700 2009}]
See the API documentation for more details.
Installation
Tinder can be installed as a gem or a Rails plugin. Install the gem by executing:
gem install tinder
Or, download it from RubyForge.
Source
Contributions are welcome and appreciated! The source is available from:
http://github.com/collectiveidea/tinder


Preventable, self-inflicted injuries from the constant repetition of using the wrong muscles in the wrong place at the wrong time.
Developing great ATHLETES is all about developing great PEOPLE. Where as traditional training is hyperfocused on sport specific, physical training, at MAXIMUS, we view all developmental components as equally important.
| Physical | Movement is the foundation of any athletic feat. Inefficient, ineffective movements limit performance and increase injury risk. |
| Mental | A strong mind enables a strong performance. |
| Nutrition Education | The athlete’s fuel determines how their body performs in the long run. |
| Personal | Character is critical to the long term success of the athlete. Our athletes are held to exceptional standards regarding beliefs and attitudes both in and out of sport. |
Monthly workshops only go so far - our Training System strategically and intentionally integrate all components of athlete development into each training session, developing habits that enable continuous, consistent improvements.
Reliable, explosive acceleration and blazing top end speeds will LITERALLY separate your child from the pack. Developing these skills will give your child the confidence they need to execute when it matters most, creating opportunities on the court, diamond, ice, and field!
Though it may seem straightforward, sprinting is a series of extremely complex movements subjecting the body to high levels of force. Learning to sprint efficiently and effectively will develop coordination, rhythm, strength, power, and durability that transfer immediately to their sport of choice.
Mondays, Wednesdays, and Fridays from 6-7:30PM.
| Rate Option | Price per month* (HST included) |
|---|---|
| 1 per week | 140 |
| 2 per week | 200 |
| 3 per week | 240 |
*Based on a 4 week month. Monthly rates may vary when prorated for cancelled practices/holidays and/or 5 week months.


Bayern eye Man Utd loan star as long-term replacement in key area
Bayern Munich are keeping tabs on Manchester United goalkeeper Dean Henderson as they think about a potential swoop for the Englishman, according to reports.
The 22-year-0ld, who is on loan at Sheffield United this term, has impressed for Chris Wilder’s side having only let in nine goals in 12 Premier League games, with the Blades sitting 5th in the table.
Henderson signed a new long-term deal at Old Trafford in June that will keep him at the club until 2023 at the latest, but according to the Daily Mail, Bayern could be preparing to make a move for the goalkeeper.
The report says that the German champions eye Henderson as the long-term successor to Manuel Neuer, 33, whose current contract expires in 2021.
Neuer has made 354 appearances for Bayern since joining the club from Schalke, but he will be 35 when his deal reaches its conclusion and could look to move on to pastures new.
Henderson, meanwhile, will not be available for the Blades this weekend for the clash with his parent club, who sit 10th in the table.
Wilder’s men have impressed at home this season, taking runaway leaders Liverpool close to a draw while beating Arsenal 1-0.
Read more: Man Utd weighing up shock move for ex-Man City proven goalscorer


I did this with 4 objects using this simulator. It appears to be stable enough.
| Mass | X Pos | Y Pos | X Velocity | Y Velocity |
|---|---|---|---|---|
| 200 | -57 | 0 | 0 | 0 |
| 2 | 126 | 0 | 0 | 116 |
| 1 | 166 | 0 | 0 | 82 |
| 0.001 | 172 | 0 | 0 | 42 |
Not by the look of it. Charon is on the right.
http://en.wikipedia.org/wiki/File:Pluto_and_charon.jpg
Figures:
Pluto: Mean radius 1153 ± 10 km
Charon: Mean radius 603.5 ± 1.5 km


DREAMLIFE OF ANGELS, THE (LA VIE REVEE DES ANGES) (director/writer: Erick Zonca; screenwriters: Roger Bohbot/Virginie Wagon; cinematographer: Agnes Godard; cast:Elodie Bouchez (Isa), Natacha Regnier (Marie), Gregoire Colin (Chriss), Jo Prestia (Fredo), Patrick Mercado (Charly), 1998-France)
Reviewed by Dennis Schwartz
Who finds in life what they dream of? This emotionally moving film will look into that and will also examine the heart aches of two working class girls, doing it in a way only the French can do it justice.
The petite 21-year old Isa (for Isabelle), who is loaded down with a full backpack, wanders into the cold and grey industrial city of Lille. She hopes to stay with a male friend, but finds out he's in Belgium, and ends up remaining in Lille for the night. She hopes to pick up some cash by selling touristy postcards on the street, which leads to an encounter with a Yugoslavian who tells her about a sewing job in a clothing factory. Isa, being unskilled, gets fired after working there only one day, but not before meeting a fellow seamstress, Marie (Regnier), who is the same age.
 There are many things about Isa that are unexplained and delightfully mysterious that we accept from her because she is so genuinely likable.
Marie reluctantly puts her up in a beautiful apartment, one that she is minding for a mother and a daughter lying comatose in the hospital after a car crash.The mother will die, leaving the teenage girl with no visitors except for Isa who takes it upon herself to make contact with the girl in the hospital. These encounters brilliantly show what Isa is all-about, as she wants to will the girl back to life. For Isa, life holds so much promise and light and love in it, that misery alone cannot stop her thoroughly from the angelic path she is on. The journey becomes for her only a question if her dreamlife can become her real life, as she will seek the ideal and not be deterred by what roadblocks stand in her way, which is something the young can do more readily than the elderly. By the end of the film, we wonder what will become of her, as the camera pans the sad faces of the women who work all their lives in a factory, where Isa might have no choice but to end up working in and be exploited by the bosses, as it seems that is the pattern of life for a working girl here.
Her relationship with Marie is not a very warm one, instead it is a workable one. Marie is not a trusting or caring person; in fact, she is most of the time a downer who expects the worst in life and when that happens she can't properly handle it without becoming crazy.
The tall and slender Marie is very attractive but she is also very mixed-up emotionally.  Her relationship with the more spiritually minded Isa is based more on convenience than on mutual admiration or anything else, since they are both impoverished and seem to be stuck because of their lack of education and inability to fit into society and their inability to meet a guy who they love or who can love them in return. They are working-class girls, seemingly trapped by their birth, unable to get what they want from life. Each one dreams of a way out; but Isa, as hard as it is to believe from her appearance, is the one more grounded in reality, the one better prepared to make a go of it in life, and she is the one who grows up right in front of us.
Their encounter with the opposite sex comes on their first night together, as they try to crash a rock concert without having a ticket, but two rough-looking bouncers keep them out while flirting with them. The girls are not attracted to the guys and tell them so in a nasty way, but the relationship changes to one of friendship after much banter back and forth.  The guys feel sorry for the penniless girls; also, they want to keep up a relationship with them, so they give them some money to help them out.
The supposed meal ticket and way out of the trap Marie is in comes about unexpectedly, as she gets caught shoplifting a leather jacket and meets again Chriss (Colin), she once randomly approached him in the street in a hostile manner when she was in a playful mood. He pays for the jacket, which she accepts with hostility. She is someone who is terribly concerned about appearances and being humiliated, constantly unhappy about her station in life. He will turn out to be a womanizer, and she will be one more girl in his series of conquests, but is too blinded by her own dreams to see this, though all the signs are there. His nightclub (his father bought it for him) happens to be the place where the girls' bouncer friends work.
Isa, in need of money, tucks in her pride and takes on the temp job of dressing like a fool, putting on roller-skates and advertising sandwich-boards. Marie, however, will not. She can't handle the demeaning nature of the job.
A steady rift grows between the women, as Marie thinks she's got what she wants with her relationship with Chriss and doesn't need Isa anymore, and acts hostile toward her. All Isa is trying to do is clue her friend into not falling for Chriss, telling her that he will only drop her when he wants to, these remarks only make Marie more insulting towards her. There is a classic look of disgust on the face of Isa, that seems to be saying, you are really sick, when she finally realizes that she has to move on from here.
The performances of the two actresses was bewitching, as the two women deservedly shared Best Actress honors last year at Cannes.
The poignancy and merits of the film, are in depicting accurately the reality of the girls' lives. It is a film without one false note of sympathy or sentimentality in it. This is not the type of a girl-buddy movie as seen in some Hollywood films of late, filled with glibness and glitter and canned experiences. Here, what happens has the ring of truth to it and is powerful in the sense that its simple telling of the tale, without trying to be cute or pedantic, turns out to be profound. It caught a certain inexpressible joy there is to life, the kind of joy where one can connect with someone else and feel satisfied in doing that because what you are doing is true, just like Isa did when she befriended the girl in the coma.
This debut film for the 42-year-old director, done with the austerity of a master, reminiscent of someone like a Robert Bresson, is a work of considerable merit. It is a film that not only depicted the shattering of a friendship and a realistic look at life for the working class, but it probed into the deep seated loneliness found within each of the girls, looking at it in a poetic way.
REVIEWED ON 9/3/99 GRADE: A
Dennis Schwartz: "Ozus' World Movie Reviews"
http://www.sover.net/~ozus
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