Provides Beautiful Animated Marker Clustering functionality for Leaflet, a JS library for interactive maps.
Requires Leaflet 1.0.0
For a Leaflet 0.7 compatible version, use the leaflet-0.7 branch
For a Leaflet 0.5 compatible version, Download b128e950
For a Leaflet 0.4 compatible version, Download the 0.2 release
Include the plugin CSS and JS files on your page after Leaflet files, using your method of choice:
v1.4.1
<EMAIL_ADDRESS>npm install leaflet.markercluster
In each case, use files in the dist
folder:
MarkerCluster.css
MarkerCluster.Default.css
(not needed if you use your own iconCreateFunction
instead of the default one)leaflet.markercluster.js
(or leaflet.markercluster-src.js
for the non-minified version)Install jake npm install -g jake
then run npm install
jake
.jake test
.See the included examples for usage.
The realworld example is a good place to start, it uses all of the defaults of the clusterer. Or check out the custom example for how to customise the behaviour and appearance of the clusterer
Create a new MarkerClusterGroup, add your markers to it, then add it to the map
var markers = L.markerClusterGroup();
markers.addLayer(L.marker(getRandomLatLng(map)));
... Add more layers ...
map.addLayer(markers);
By default the Clusterer enables some nice defaults for you:
disableClusteringAtZoom
option){ weight: 1.5, color: '#222', opacity: 0.5 }
.You can disable any of these as you want in the options when you create the MarkerClusterGroup:
var markers = L.markerClusterGroup({
spiderfyOnMaxZoom: false,
showCoverageOnHover: false,
zoomToBoundsOnClick: false
});
As an option to MarkerClusterGroup you can provide your own function for creating the Icon for the clustered markers.
The default implementation changes color at bounds of 10 and 100, but more advanced uses may require customising this.
You do not need to include the .Default css if you go this way.
You are passed a MarkerCluster object, you'll probably want to use getChildCount()
or getAllChildMarkers()
to work out the icon to show.
var markers = L.markerClusterGroup({
iconCreateFunction: function(cluster) {
return L.divIcon({ html: '<b>' + cluster.getChildCount() + '</b>' });
}
});
Check out the custom example for an example of this.
If you need to update the clusters icon (e.g. they are based on markers real-time data), use the method refreshClusters().
You can also provide a custom function as an option to MarkerClusterGroup to override the spiderfy shape positions. The example below implements linear spiderfy positions which overrides the default circular shape.
var markers = L.markerClusterGroup({
spiderfyShapePositions: function(count, centerPt) {
var distanceFromCenter = 35,
markerDistance = 45,
lineLength = markerDistance * (count - 1),
lineStart = centerPt.y - lineLength / 2,
res = [],
i;
res.length = count;
for (i = count - 1; i >= 0; i--) {
res[i] = new Point(centerPt.x + distanceFromCenter, lineStart + markerDistance * i);
}
return res;
}
});
disableClusteringAtZoom
option).L.DomUtil.TRANSITION
is false, this option has no effect (no animation is possible).animate
option is also true) then adding individual markers to the MarkerClusterGroup after it has been added to the map will add the marker and animate it into the cluster. Defaults to false as this gives better performance when bulk adding markers. addLayers does not support this, only addLayer with individual Markers.spiderfyOnMaxZoom
option when using disableClusteringAtZoom
.disableClusteringAtZoom
does not restore their previous icon (see #391).{ weight: 1.5, color: '#222', opacity: 0.5 }
.Options for the addLayers method. See #357 for explanation on how the chunking works.
Leaflet events like click
, mouseover
, etc. are just related to Markers in the cluster.
To receive events for clusters, listen to 'cluster' + '<eventName>'
, ex: clusterclick
, clustermouseover
, clustermouseout
.
Set your callback up as follows to handle both cases:
markers.on('click', function (a) {
console.log('marker ' + a.layer);
});
markers.on('clusterclick', function (a) {
// a.layer is actually a cluster
console.log('cluster ' + a.layer.getAllChildMarkers().length);
});
cluster
and markers
attributes)cluster
and markers
attributes)addLayer
, removeLayer
and clearLayers
are supported and they should work for most uses.
addLayers
and removeLayers
are bulk methods for adding and removing markers and should be favoured over the single versions when doing bulk addition/removal of markers. Each takes an array of markers. You can use dedicated options to fine-tune the behaviour of addLayers
.
These methods extract non-group layer children from Layer Group types, even deeply nested. However, be noted that:
chunkProgress
jumps backward when addLayers
finds a group (since appending its children to the input array makes the total increase).hasLayer
method will return true
for non-group child layers, but false
on any (possibly parent) Layer Group types.If you are removing a lot of markers it will almost definitely be better to call clearLayers
then call addLayers
to add the markers you don't want to remove back in. See #59 for details.
If you have a marker in your MarkerClusterGroup and you want to get the visible parent of it (Either itself or a cluster it is contained in that is currently visible on the map). This will return null if the marker and its parent clusters are not visible currently (they are not near the visible viewpoint)
var visibleOne = markerClusterGroup.getVisibleParent(myMarker);
console.log(visibleOne.getLatLng());
If you have customized the clusters icon to use some data from the contained markers, and later that data changes, use this method to force a refresh of the cluster icons. You can use the method:
markers.refreshClusters();
markers.refreshClusters([myMarker0, myMarker33]);
markers.refreshClusters({id_0: myMarker0, id_any: myMarker33});
markers.refreshClusters(myLayerGroup);
markers.refreshClusters(myMarker);
The plugin also adds a method on L.Marker to easily update the underlying icon options and refresh the icon.
If passing a second argument that evaluates to true
, the method will also trigger a refreshCluster
on the parent MarkerClusterGroup for that single marker.
// Use as many times as required to update markers,
// then call refreshClusters once finished.
for (i in markersSubArray) {
markersSubArray[i].refreshIconOptions(newOptionsMappingArray[i]);
}
markers.refreshClusters(markersSubArray);
// If updating only one marker, pass true to
// refresh this marker's parent clusters right away.
myMarker.refreshIconOptions(optionsMap, true);
The following methods can be used with clusters (not the group). They are typically used for event handling.
When you receive an event from a cluster you can query it for the bounds.
markers.on('clusterclick', function (a) {
var latLngBounds = a.layer.getBounds();
});
You can also query for the bounding convex polygon. See example/marker-clustering-convexhull.html for a working example.
markers.on('clusterclick', function (a) {
map.addLayer(L.polygon(a.layer.getConvexHull()));
});
When you receive an event from a cluster you can zoom to its bounds in one easy step.
If all of the markers will appear at a higher zoom level, that zoom level is zoomed to instead.
zoomToBounds
takes an optional argument to pass options to the resulting fitBounds
call.
See marker-clustering-zoomtobounds.html for a working example.
markers.on('clusterclick', function (a) {
a.layer.zoomToBounds({padding: [20, 20]});
});
The Clusterer can handle 10,000 or even 50,000 markers (in chrome). IE9 has some issues with 50,000.
Note: these two examples use the chunkedLoading
option set to true in order to avoid locking the browser for a long time.
Leaflet.markercluster is free software, and may be redistributed under the MIT-LICENSE.
Leaflet.markercluster plugin is very popular and as such it generates high and diverse expectations for increased functionalities.
If you are in that case, be sure to have a look first at the repository issues in case what you are looking for would already be discussed, and some workarounds would be proposed.
Check also the below sub-plugins:
| Plugin | Description | Maintainer |
|---|---|---|
| Leaflet.FeatureGroup.SubGroup | Creates a Feature Group that adds its child layers into a parent group when added to a map (e.g. through L.Control.Layers). Typical usage is to dynamically add/remove groups of markers from Marker Cluster. | ghybs |
| Leaflet.MarkerCluster.LayerSupport | Brings compatibility with L.Control.Layers and other Leaflet plugins. I.e. everything that uses direct calls to map.addLayer and map.removeLayer. | ghybs |
| Leaflet.MarkerCluster.Freezable | Adds the ability to freeze clusters at a specified zoom. E.g. freezing at maxZoom + 1 makes as if clustering was programmatically disabled. | ghybs |
| Leaflet.MarkerCluster.PlacementStrategies | Implements new strategies to position clustered markers (eg: clock, concentric circles, ...). Recommended to use with circleMarkers. Demo | adammertel / UNIVIE |
| Leaflet.MarkerCluster.List | Displays child elements in a list. Suitable for mobile devices. Demo | adammertel / UNIVIE |


Branched across Europe and the Americas, we offer expertise legal and support services in the practices of international transactions, businesses, tax and investments.
We provide planning advice, counsel, and legal support services to enterprises and individuals engaged in international transactions, business or investments. We focus on the jurisdictions of Europe and the Americas.
Our knowledge and experience in the dynamics of transnational legal and economic milieus assists clients to structure international businesses and investments. Firm members are fluent in various languages (primarily English, German, French, Spanish and Russian) and continuously update and improve their professional skills through seminars and conferences.
Various corporate clients have entrusted us as counsel for general legal matters arising from their corporate and commercial operations. Our approach - teamwork with highly qualified professionals and clients' trusted advisors - provides a wealth of skills enabling elaboration of comprehensive strategies.
Thus our clients benefit from wide-ranging experience in structuring, negotiating, and implementing business acquisitions and divestitures, mergers and reorganizations, debt and equity financing, capital market transactions (both public and private sectors), leveraged buy-outs, corporate restructuring, commercial compliance, as well as equipment leasing and U.C.C. matters.
We represent a spectrum of domestic and foreign business structures (corporations, partnerships, “pass through” entities). One of our fortés is implementing business start-ups, including:
Planning to attain long-term client goals
Selecting appropriate operational structure(s)
Establishing basic relationships (commercial, executive, banking)
Providing executive support (eg: executive participation, visas...)
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Due diligence research and reporting
Another forté involves effectuating changes in business or investment structures or entities with perspectives of updating and improving them, such as:
Legal reviews and analyses
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We may also constitute and coordinate the expert and professional teams needed to prepare and maintain effective operational, financial, business, or reorganization plans.
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Our taxation services include:
Analyzing and optimizing appropriate laws and jurisdictions
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Projects include acquisitions of shopping malls, purchases/sales of commercial buildings, mortgage financing, and resolving land development problems.
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Obtaining Apostilles
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International Notarization
International Wills, Trusts, Estates


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Diogo M. Costa
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Refracts light - bends it as it enters the eye
Controls how much light enters the pupil
Focuses light onto the retina
A bundle of sensory neurones at back of eye. It carries impulses from the eye to the brain.


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American National Standards Institute
The Institute oversees the creation, promulgation and use of thousands of norms and guidelines that directly impact businesses in nearly every sector: from acoustical devices to construction equipment, from dairy and livestock production to energy distribution, and many more. ANSI is also actively engaged in accreditation - assessing the competence of organizations determining conformance to standards.
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American Society of Testing and Materials (ASTM)
Working across borders, disciplines and industries we harness the expertise of over 30,000 members to create consensus and improve performance in manufacturing and materials, products and processes, systems and services.
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American Water Works Association
The American Water Works Association is an international, nonprofit, scientific and educational society dedicated to providing total water solutions assuring the effective management of water. Founded in 1881, the Association is the largest organization of water supply professionals in the world. Our membership includes over 3,900 utilities that supply roughly 80 percent of the nation's drinking water and treat almost half of the nation’s wastewater. Our nearly 50,000 total memberships represent the full spectrum of the water community: public water and wastewater systems, environmental advocates, scientists, academicians, and others who hold a genuine interest in water, our most important resource. AWWA unites the diverse water community to advance public health, safety, the economy, and the environment.
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Bay Area Water Works Association
BAWWA’s purpose is to provide opportunities for its members to interact with each other and exchange information and ideas as well as broaden its collective member’s knowledge and experiences relative to water works issues and industry developments and opportunities.
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Central Coast Builders Association
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McElroy
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National Fire Protection Association
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National Sanitation Foundation International
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Axe = argmin, argmax of X
ArgMin(d,x,list)
and ArgMax(d,x,list)
are functions that seek the value of element a=list[i]
that minimizes/maximizes the expected value of
the function x(a)
above and below that element.
This process is then repeated recursviely d
times on each part of the data.
A large number of learners, clusterers, evaluation methods can be characeterised in this way.
Example1
For example, given the numbers
100,10,90,20,110,30,90,40,120
we might what to know how to best split the numbers so as to minimize standard deviation.
Step1: sort the numbers:
all= 10,20,30,40,90,100,110,120
i= 1 2 3 4 5 6 7 8
Step2: what is f
of the whole space?
all.n = 8
all.mu = 65
all.sd = sqrt( sum( (all[i] - all.mu)^2 ) / (n-1) ) = 44.4
Step3: find any split (say,i=2) and calculate the standard deviation above and below that slot
left = all[ i <= 2 ]
right = all[ i > 2 ]
left.sd = 7.07
right.sd = 37.64
Step 4: find the expected value of the standard deviation afer the split.
xpect(n, n1, v1, n2, v2) = n1/n*v1 + n2/n * v2
left.n = 2
right.n = 6
xpect(8, left.n, left.sd, right.n, right.sd) = 30.00
From this we can conclude that splitting at x=2 will reduce the uncertainty in this space from 44.4 to 30. Great!
Step5: now repeat the above, but for all values of i
.
- For sanity sake, we might demand that each left and right split
not be too small; e.g.
enough=2
items. - We'll also assume there exists some
Num
class that can incrementally update and reportn
andsd
.
Here's ArgMin(1,sd, list)
; i.e. only one level of split and we want to minimize standard deviation:
def sd(x, y):
return xpect(x.n + y.n, x.n, x.sd, y.n, y.sd)
def lt(x, y): return x < y
def gt(x, y): return x > y
def xSplit(lst,
lo = 1,
hi = length(lst),
enough= 2,
better= lt,
f = sd,
best = 10000000):
cut = nil
if hi-lo > 2*enough: # otherwise, why bother?
left = Num()
right = Num()
for i = lo, hi:
right + lst[i] # give eveything to right
for i = lo, hi:
a = lst[i]
left + a # add one to the right
right - a # remove one from the left
if left.n >= enough and right.n >= enough:
tmp = f(left,right)
if better( tmp , best ):
cut, best = i, tmp
return cut,best
Note that:
- This function returns
cut=nil
if no cut is found. - This function assumes the list is sorted before calling this function.
- For Python use
lo,hi = 0
tolength-1
; - If you want to generate more than one split, then call it recursively
with
lo=lo,hi=cut
andlo=cut+1,hi=hi
andbest
(in the recursive call) equal to thebest
return from the above). - To minimze on other things then use another
xpect
function. - This can actually serve as a
argmax
as well.- Change
better
togt
- Initialize
best
to a large negative number.
- Change
If we called this in the above data, then it would recommend we cut at 4, i.e. the list
all= 10,20,30,40,90,100,110,120
i= 1 2 3 4 5 6 7 8
should split into
left = 10,20,30,40
right= 90,100,110,120
So what we have right now is a very simple 1-dimensional clustering algorithm for a list of numeric numbers
For lists of more complex data types, we need to pass in a selector, which we will call x
that extracts the number we want to use from each
item in the list. E.g. if clustering on an Employee's age, we might use x=employee.age
.
Further, given tables of independent and dependent variables, sometimes we want to clsuter on the independent variable in order to have most impact on the dependent variable. e.g. age alive
sanity checks Sanit.g.y checks. sd cohen. fayyad iranni. is it valid to split (are the splits actually different?)
scott knott
FFTtrees
which would have an expected value of standard deviation of 12.9 (much less than the origianl 44.4)
def gotEnd(x, y) return xpect(x.n + y.n, x.n, x.ent, y.n, y.ent)


Interface to Frobby for fast computations on monomial ideals.#
The software package Frobby provides a number of computations on monomial ideals. The current main feature is the socle of a monomial ideal, which is largely equivalent to computing the maximal standard monomials, the Alexander dual or the irreducible decomposition.
Operations on monomial ideals are much faster than algorithms designed for ideals in general, which is what makes a specialized library for these operations on monomial ideals useful.
AUTHORS:
Bjarke Hammersholt Roune (2008-04-25): Wrote the Frobby C++ program and the initial version of the Python interface.
Note
The official source for Frobby is <https://www.broune.com/frobby>, which also has documentation and papers describing the algorithms used.
- class sage.interfaces.frobby.Frobby#
Bases:
object
- alexander_dual(monomial_ideal)#
This function computes the Alexander dual of the passed-in monomial ideal. This ideal is the one corresponding to the simplicial complex whose faces are the complements of the nonfaces of the simplicial complex corresponding to the input ideal.
INPUT:
monomial_ideal – The monomial ideal to decompose.
OUTPUT:
The monomial corresponding to the Alexander dual.
EXAMPLES:
This is a simple example of computing irreducible decomposition.
sage: (a, b, c, d) = QQ['a,b,c,d'].gens() # optional - frobby sage: id = ideal(a * b, b * c, c * d, d * a) # optional - frobby sage: alexander_dual = frobby.alexander_dual(id) # optional - frobby sage: true_alexander_dual = ideal(b * d, a * c) # optional - frobby sage: alexander_dual == true_alexander_dual # use sets to ignore order # optional - frobby True
We see how it is much faster to compute this with frobby than the built-in procedure for simplicial complexes:
sage: t=simplicial_complexes.PoincareHomologyThreeSphere() # optional - frobby sage: R=PolynomialRing(QQ,16,'x') # optional - frobby sage: I=R.ideal([prod([R.gen(i-1) for i in a]) for a in t.facets()]) # optional - frobby sage: len(frobby.alexander_dual(I).gens()) # optional - frobby 643
- associated_primes(monomial_ideal)#
This function computes the associated primes of the passed-in monomial ideal.
INPUT:
monomial_ideal – The monomial ideal to decompose.
OUTPUT:
A list of the associated primes of the monomial ideal. These ideals are constructed in the same ring as monomial_ideal is.
EXAMPLES:
sage: R.<d,b,c>=QQ[] # optional - frobby sage: I=[d*b*c,b^2*c,b^10,d^10]*R # optional - frobby sage: frobby.associated_primes(I) # optional - frobby [Ideal (d, b) of Multivariate Polynomial Ring in d, b, c over Rational Field, Ideal (d, b, c) of Multivariate Polynomial Ring in d, b, c over Rational Field]
- dimension(monomial_ideal)#
This function computes the dimension of the passed-in monomial ideal.
INPUT:
monomial_ideal – The monomial ideal to decompose.
OUTPUT:
The dimension of the zero set of the ideal.
EXAMPLES:
sage: R.<d,b,c>=QQ[] # optional - frobby sage: I=[d*b*c,b^2*c,b^10,d^10]*R # optional - frobby sage: frobby.dimension(I) # optional - frobby 1
- hilbert(monomial_ideal)#
Computes the multigraded Hilbert-Poincaré series of the input ideal. Use the -univariate option to get the univariate series.
The Hilbert-Poincaré series of a monomial ideal is the sum of all monomials not in the ideal. This sum can be written as a (finite) rational function with \((x_1-1)(x_2-1)...(x_n-1)\) in the denominator, assuming the variables of the ring are \(x_1,x2,...,x_n\). This action computes the polynomial in the numerator of this fraction.
INPUT:
monomial_ideal – A monomial ideal.
OUTPUT:
A polynomial in the same ring as the ideal.
EXAMPLES:
sage: R.<d,b,c>=QQ[] # optional - frobby sage: I=[d*b*c,b^2*c,b^10,d^10]*R # optional - frobby sage: frobby.hilbert(I) # optional - frobby d^10*b^10*c + d^10*b^10 + d^10*b*c + b^10*c + d^10 + b^10 + d*b^2*c + d*b*c + b^2*c + 1
- irreducible_decomposition(monomial_ideal)#
This function computes the irreducible decomposition of the passed-in monomial ideal. I.e. it computes the unique minimal list of irreducible monomial ideals whose intersection equals monomial_ideal.
INPUT:
monomial_ideal – The monomial ideal to decompose.
OUTPUT:
A list of the unique irredundant irreducible components of monomial_ideal. These ideals are constructed in the same ring as monomial_ideal is.
EXAMPLES:
This is a simple example of computing irreducible decomposition.
sage: (x, y, z) = QQ['x,y,z'].gens() # optional - frobby sage: id = ideal(x ** 2, y ** 2, x * z, y * z) # optional - frobby sage: decom = frobby.irreducible_decomposition(id) # optional - frobby sage: true_decom = [ideal(x, y), ideal(x ** 2, y ** 2, z)] # optional - frobby sage: set(decom) == set(true_decom) # use sets to ignore order # optional - frobby True
We now try the special case of the zero ideal in different rings.
We should also try PolynomialRing(QQ, names=[]), but it has a bug which makes that impossible (see github issue #3028).
sage: rings = [ZZ['x'], CC['x,y']] # optional - frobby sage: allOK = True # optional - frobby sage: for ring in rings: # optional - frobby ....: id0 = ring.ideal(0) ....: decom0 = frobby.irreducible_decomposition(id0) ....: allOK = allOK and decom0 == [id0] sage: allOK # optional - frobby True
Finally, we try the ideal that is all of the ring in different rings.
sage: rings = [ZZ['x'], CC['x,y']] # optional - frobby sage: allOK = True # optional - frobby sage: for ring in rings: # optional - frobby ....: id1 = ring.ideal(1) ....: decom1 = frobby.irreducible_decomposition(id1) ....: allOK = allOK and decom1 == [id1] sage: allOK # optional - frobby True


|
Connected Home over IP
672cf7684
|
This namespace includes all interfaces within chip for shared logging support. More...
Namespaces | |
| Platform | |
Typedefs | |
| using | LogRedirectCallback_t = void(*)(const char *module, uint8_t category, const char *msg, va_list args) |
Functions | |
| void | GetModuleName (char *buf, uint8_t bufSize, uint8_t module) |
| void | SetLogRedirectCallback (LogRedirectCallback_t callback) |
| DLL_EXPORT void | Log (uint8_t module, uint8_t category, const char *msg,...) |
| Log, to the platform-specified mechanism, the specified log message, msg, for the specified module, module, in the provided category, category. More... | |
| void | LogV (uint8_t module, uint8_t category, const char *msg, va_list args) |
| DLL_EXPORT bool | IsCategoryEnabled (uint8_t category) |
| DLL_EXPORT uint8_t | GetLogFilter () |
| DLL_EXPORT void | SetLogFilter (uint8_t category) |
| void | GetMessageWithPrefix (char *buf, uint8_t bufSize, uint8_t module, const char *msg) |
Variables | |
| static const char | ModuleNames [] |
| uint8_t | gLogFilter = kLogCategory_Max |
| static constexpr uint16_t | kMaxModuleNameLen = 3 |
| CHIP logging length constants. More... | |
| static constexpr uint16_t | kMaxPrefixLen = 3 |
| static constexpr uint16_t | kMaxSeparatorLen = 2 |
| static constexpr uint16_t | kMaxTrailerLen = 2 |
| static constexpr uint16_t | kMaxMessagePadding |
This namespace includes all interfaces within chip for shared logging support.
The interfaces include macros, constants, and functions for a platform-independent logging interface for the chip SDK.
chip SDK clients may choose, at compile time, among Android, C Standard I/O, or external (platform- and integrator-defined) logging style implementations that will be invoked when any of the following preprocessor symbols are asserted:
| using chip::Logging::LogRedirectCallback_t = typedef void (*)(const char * module, uint8_t category, const char * msg, va_list args) |
Identifies a category to which an particular error message belongs.
| Enumerator | |
|---|---|
| kLogCategory_None | This log category indicates, when passed to SetLogFilter(), that no messages should be logged. Indicates a category of log message that describes an unexpected or severe failure. This log category indicates that a logged message describes an unexpected or severe failure in the code. It should be used for things such as out-of-resource errors, internal inconsistencies, API misuse, etc. In general, errors that are expected to occur as part of normal operation, or that are largely determined by external factors (e.g. network errors, user/operator induced errors, etc.) should be logged as kLogCategory_Progress messages, not as kLogCategory_Error messages. |
| kLogCategory_Error | Indicates a category of log message that describes an event that marks the start or end of a major activity, or a major change in the state of the overall system. It should be reserved for high-level events. Such messages should provide the log reader with a good sense of the overall activity of the system at any point in time, while being minimally verbose. Where necessary such messages should include identifiers or other values that can be used to correlate messages involving a common actor or subject (e.g. connection ids, request ids, etc.) and/or to identify types of actions being taken or handled (e.g. message types, requested resource types, error numbers, etc.). |
| kLogCategory_Progress | Indicates a category of log message that describes detailed information about an event or the state of the system. Such messages can be used to provide ancillary information not suitable for the kLogCategory_Error and kLogCategory_Progress categories. |
| kLogCategory_Detail | |
| kLogCategory_Max |
Identifies a logical section of code that is a source of log messages.
| uint8_t chip::Logging::GetLogFilter | ( | ) |
| void chip::Logging::GetMessageWithPrefix | ( | char * | buf, |
| uint8_t | bufSize, | ||
| uint8_t | module, | ||
| const char * | msg | ||
| ) |
| void chip::Logging::GetModuleName | ( | char * | buf, |
| uint8_t | bufSize, | ||
| uint8_t | module | ||
| ) |
| bool chip::Logging::IsCategoryEnabled | ( | uint8_t | category | ) |
| void chip::Logging::Log | ( | uint8_t | module, |
| uint8_t | category, | ||
| const char * | msg, | ||
| ... | |||
| ) |
Log, to the platform-specified mechanism, the specified log message, msg, for the specified module, module, in the provided category, category.
| [in] | module | A LogModule enumeration indicating the source of the chip package module that generated the log message. This must be translated within the function to a module name for inclusion in the log message. |
| [in] | category | A LogCategory enumeration indicating the category of the log message. The category may be filtered in or out if CHIP_LOG_FILTERING was asserted. |
| [in] | msg | A pointer to a NULL-terminated C string with C Standard Library-style format specifiers containing the log message to be formatted and logged. |
| [in] | ... | A variadic argument list whose elements should correspond to the format specifiers in msg. |
| void chip::Logging::LogV | ( | uint8_t | module, |
| uint8_t | category, | ||
| const char * | msg, | ||
| va_list | args | ||
| ) |
| void chip::Logging::SetLogFilter | ( | uint8_t | category | ) |
| void chip::Logging::SetLogRedirectCallback | ( | LogRedirectCallback_t | callback | ) |
| uint8_t chip::Logging::gLogFilter = kLogCategory_Max |
|
staticconstexpr |
|
staticconstexpr |
CHIP logging length constants.
|
staticconstexpr |
|
staticconstexpr |
|
staticconstexpr |
|
static |


{% extends "base.html" %} {% block sidebaritems %}
Unique identifier for your app.
Your app's fullname.


Releases
Version downloads and complete release notes
Sub-Projects
The FreeRADIUS project maintains a number of sub-projects to add RADIUS capabilities to popular web servers and authentication services.
If your favourite application isn't supported, creating glue code is simple! Linking against libfreeradius-radius provides a complete toolkit for developing RADIUS authenticated services.
This is the PAM to RADIUS authentication module. It allows any PAM-capable machine to become a RADIUS client for authentication and accounting requests. You will need a RADIUS server to perform the actual authentication.
Files included with the module
README
Introduction and documentation
INSTALL
Installation instructions
USAGE
Module configuration and usage documentation
Changelog
What's changed
pam_radius_auth.conf
Sample configuration file for telling the client the location of the RADIUS server.
This is the Apache RADIUS authentication module. It allows any Apache web-serve to become a RADIUS client for authentication and accounting requests.
Module building and configuration
Configure this module into Apache by going to the Apache root directory, and typing:
Lang
./configure --add-module=LOCATION/mod_auth_radius.c
where LOCATION is the directory where the module source file resides. Then, type:
Lang
make
Alternatively, if you've already built and installed Apache with dynamic modules, you should be able to install this module via:
Lang
apxs -i -a -c mod_auth_radius.c
You should add your additional site configuration options to the configure line, above. Please read the README file for further information.
Files included with the module
README
Introduction and documentation
httpd.conf
Sample HTTPD configuration file for RADIUS attributes, with additional comments and documentation.
htaccess
Sample .htaccess file
mod_auth_radius.c
C source file for Apache 2.4.x
Updates
The latest version of the module is 1.6.0.
For the latest source code, see the GitHub site:
https://github.com/FreeRADIUS/mod_auth_radius
Author contact
Alan DeKok<EMAIL_ADDRESS>Related pages
FreeRADIUS Client is a framework and library for writing RADIUS Clients which additionally includes radlogin, a flexible RADIUS aware login replacement, a command line program to send RADIUS accounting records and a utility to query the status of a RADIUS server. All of these programs are based on a library that lets you develop a RADIUS-aware application in less than 50 lines of C code. It is highly portable and runs on Linux, many BSD variants and Solaris.
See the Wiki for more information.
Version 1.1.7
Version 1.1.7 has a large number of fixes, but is still compatible with the code from 1.1.6. The ChangeLog is:
- Allow "configure --with-nettle" to use nettle MD5 implementation. Patch from Nikos Mavrogiannopoulos.
- Clean up generation of random numbers. Patch from Nikos Mavrogiannopoulos.
- Update BSD license as permitted by Christos Zoulas.
- Define PW_MAX_MSG_SIZE for maximum message sice. Patch from Nikos Mavrogiannopoulos.
- Allow the dictionary file parser to understand BEGIN-VENDOR / END-VENDOR as with FreeRADIUS server. Patch from Nikos Mavrogiannopoulos.
- Added support for IPv6. Patch from Nikos Mavrogiannopoulos.
- Don't crash if a config option is unset. Patch from Nikos Mavrogiannopoulos.
- Fix encoding of "date" attributes. Patch from Christian Schoch.
- Build fixes from Sven Neuhaus, Ghennadi Procopciuc, Daniel Pocock, and gureedo.
- Fix memory leaks. Patches from Alex Massover, William King, gureedo, and FreeSWITCH.
- Fixes to retry algorithm. Patch from Lewis Adam.
- Zero out secret fields. Patch from Scott Neugroschl.
- Update the dictionaries. Patches from Bogdan-Andrei Iancu and gureedo.
- Make the library thread-safe. Based on a patch from Alex Massover.
- Made rc_avpair_log thread-safe by using a buffer supplied by the caller. Patch from Alex Massover.
- Removed lock file for sequence number. It isn't needed.
- Use poll() where possible to avoid issues with FD_SETSIZE. Patch from Alfred E. Heggestad.
- Set Acct-Delay-Time in Accounting-Request packets. Patch from Alfred E. Heggestad.
License
Unlike the FreeRADIUS Server which is available under the GPL, or libfreeradius which is available under the LGPL, the FreeRADIUS Client library is distributed under the BSD license. This is to facilitate the maximum possible use of correct, up-to-date, maintained code in as many other RADIUS Client implementations as possible.
The FreeRADIUS team collectively has decades of RADIUS experience, and is active in defining new RADIUS standards. We have worked with many different RADIUS servers and clients, and know what it takes to make a client that is robust, feature-rich, and inter-operable. To that end, we are releasing this library under the BSD license, to lower your costs in developing a RADIUS client, and to increase the likelihood that your client will inter-operate with every other implementation.
We want you use this code in your application whether it is Open Source or not.
Please see the COPYRIGHT file in the radiusclient source code for more details.
History
Radiusclient used to live at http://www.cityline.net/~lf/radius/ but seems to be no longer maintained (Tarballs are still available from ftp://ftp.cityline.net/pub/radiusclient/). It does however still ship with some Linux distributions including SUSE Linux.
A fork of the original radiusclient called radiusclient-ng is used as the basis of the RADIUS support in SER and OpenSER.
In late 2006 it was decided that the FreeRADIUS Project should adopt the latest code from radiusclient-ng cvs as the basis of a new FreeRADIUS client package. The intention is to roll some of the client functionality of the FreeRADIUS server into this separate client package and to make the FreeRADIUS suite a one stop shop for all people wishing to use and develop RADIUS related applications.
The first version released by the FreeRADIUS project is 1.1.5. This version fixes an MD5 related endian issue and introduces a client configuration framework to the library which lends itself to allowing embedded radius client functionality. Development of the codebase is ongoing.


Affordance
The Good
Imgur's UploaderImgur got their uploader just right. It is straightforward and obvious what the user needs to do to upload an image, and gives users 4 easy ways to do so.
The Bad
As we are all to familiar with, Angel is pretty horrible. It definitely has some affordance issues. For example, the buttons on the left of the home page once you've logged in.  In literally every other use of the "power" symbol I've seen, it has something to do with the power state of the device you're using. This is an affordance issue because the button's appearance does not correspond to its function.
Mapping
The Good
This registration form is quick, easy, and well-mapped. The submit button is right at the bottom, which is where your cursor will be when you finish the form. Additionally, the form easily fits on one screen so you won't have to scroll to find the submit button.
The Bad
Seriously, if you've ever been here you'll know what I'm talking about. There are around 6 download buttons that either download something other than what you're trying to download, or just take you to a different website entirely. This is very confusing and is poor mapping as the download control is obfuscated by fake download controls.
Rule of Thirds
The Good
Excepting the top navigation, Apple's home page is a perfect example of the rule of thirds. The main featured product takes up the top two thirds, while other hot items are displayed along the bottom third of the page.
The Bad
RockAuto is an online auto parts store, however their website leaves a lot to be desired. The info/language/contact navigation is squished into the left sixth of the page, with car makes taking up the remaining 5/6 of the page. To make it even worse, in the list of car makes, there is more whitespace than there is content.
Ockham's Razor
The Good
Microsoft did a great job designing this page to get its point across cleanly and concisely. There is no irrelevant information, and the design is smooth and clean.
The Bad
Fox News' home page is anything but simple. There are stories in different formats all over the page, some with pictures, links to others in bulleted lists that appear as though they are part of a major story but aren't, and many ads that pretend to be links to news stories. Yuck.
Signal-to-Noise Ratio
The Good
Ford's page for its 2015 Mustang sports car is very quick and to the point. Except for the top navigation, the page contains only information related to the new car.
The Bad
This site is an abomination.  It hurts my eyes to even look at the thing.


--- layout: post title: Maybelline Color Sensational Moisture Extreme Lipstick Brick Rose tags: - Maybelline status: publish type: post published: true meta: _aioseop_title: Maybelline Color Sensational Moisture Extreme Lipstick Brick Rose _aioseop_keywords: Maybelline Color Sensational Moisture Extreme Lipstick Brick Rose _edit_last: '2' wp_plus_one_redirect: '' _graphene_slider_img: global _graphene_slider_imgurl: '' _graphene_show_addthis: global _graphene_post_date_display: global _sg_subscribe-to-comments<EMAIL_ADDRESS>_yoast_wpseo_linkdex: '0' _thumbnail_id: '2593' ---
Once you get the knack of lip shades, its hard to stop yourself from exploring the different shades out there. I am quite new to the world of Lip Color and still in experimental phase. As might have happened with almost each one of you, I started with natural, neutral and nude shades.
Price: Rs 220 My experience: I picked this up since I did not want to plunge in with killer hot red shade instantly. Although I quite appreciate this lip stick for the prices it demands, it has smooth texture, great pigmentation and non drying. What I did not like the much is the slight tinge of golden shimmer in the color, but its not that much. Lasting power is kind of OK. On me this colors lasts around 3 hours and does not settle on fine lines. What I like:What I did not like:
Its a great budget pick, and specially for those who are afraid to flaunt red lip, can definitely give this a try :)
Which red lippie do you have?


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Get Weight Lifting Logos Pictures. ✓ free for commercial use ✓ high quality images. Designevo's weightlifting logo maker enables even a newbie to make logos with a professional appearance easily.
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{{/*A pipeline is a possibly chained sequence of "commands". A command is */}}
{{/*a simple value (argument) or a function or method call, possibly with multiple arguments: */}}
{{/*If the value of the pipeline is empty, no output is generated;*/}}
{{/*The empty values are false, 0, any nil pointer or interface value, */}}
{{/*and any array, slice, map, or string of length zero.*/}}
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| Generated by Epydoc 3.0beta1 on Fri Jul 31 02:00:36 2009 | http://epydoc.sourceforge.net |


--- layout: page title: "System for Cross-domain Identity Management: Protocol" description: "The System for Cross-domain Identity Management (SCIM) specification is an HTTP-based protocol that makes managing identities in multi-domain scenarios easier to support via a standardized service. Examples include, but are not limited to, enterprise-to-cloud service providers and inter-cloud scenarios. The specification suite seeks to build upon experience with existing schemas and deployments, placing specific emphasis on simplicity of development and integration, while applying existing authentication, authorization, and privacy models. SCIM's intent is to reduce the cost and complexity of user management operations by providing a common user schema, an extension model, and a service protocol defined by this document." ---
| Document Name: | RFC 7644 |
|---|---|
| Document URI: |
urn:ietf:rfc:7644
|
| Online Version: |
https://datatracker.ietf.org/doc/html/rfc7644
|
| Organization: | Internet Engineering Task Force (IETF) |
| Series: | Request for Comments (RFC) |
| Abstract: | The System for Cross-domain Identity Management (SCIM) specification is an HTTP-based protocol that makes managing identities in multi-domain scenarios easier to support via a standardized service. Examples include, but are not limited to, enterprise-to-cloud service providers and inter-cloud scenarios. The specification suite seeks to build upon experience with existing schemas and deployments, placing specific emphasis on simplicity of development and integration, while applying existing authentication, authorization, and privacy models. SCIM's intent is to reduce the cost and complexity of user management operations by providing a common user schema, an extension model, and a service protocol defined by this document. |
application/scim+json
Return to ( Series | Organization | all Specifications )


talks
Research Talks
May 2022: Invited Talk at Meta Research.
The Platform Design Problem.
May 2022: Invited Talk at Google Brain AutoML.
Nonlinear Initialization Methods for Low-Rank Neural Networks.
May 2022: Invited Talk at Berkeley Center for Human-Compatible Artificial Intelligence (CHAI) Seminar.
Controllable and Interpretable Agents: The Platform Design Problem and Beyond.
April 2022: Invited Talk at Google Research NYC.
Sparse and Low-Rank: Resource-Efficient Methods in Machine Learning.
February 2022: Invited Talk at Google Brain Neural Modeling Group Invited Talk.
Nonlinear Initialization Methods for Low-Rank Neural Networks.
February 2022: Invited Talk at Simons Flatiron Center for Computational Neuroscience.
Sparse and Low-Rank: Resource-Efficient Methods in Machine Learning.
February 2022: Invited Talk at Amazon AWS.
Nonlinear Initialization Methods for Low-Rank Neural Networks.
February 2022: Invited Talk at Simons Theory of Computing, Learning in Games Program, Equilibrium Computation and Machine Learning Reading Group.
The Platform Design Problem.
February 2022: Graduating Bits at ITCS.
Graduating Bits Talk.
[slides-ppt] [slides-pdf]
[YouTube video]
January 2022: Invited Talk at Simons Flatiron Center for Computational Mathematics.
Sparse and Low-Rank: Resource-Efficient Methods in Machine Learning.
[slides-ppt] [slides-pdf]
December 2021: NeurIPS 2021 StratML Workshop Spotlight Oral Presentation.
The Platform Design Problem.
[slides-ppt] [slides-pdf] [video]
December 2021: WINE 2021 Oral Presentation.
The Platform Design Problem.
[slides-ppt] [slides-pdf]
November 2021: Google Algorithms Group Invited Talk.
The Platform Design Problem.
[slides-ppt] [slides-pdf] [YouTube video]
October 2021: Google Learning Theory Group Invited Talk.
The Platform Design Problem.
[slides-ppt] [slides-pdf]
July 2021: EC 2021 NetEcon Workshop Oral Presentation.
The Platform Design Problem.
[workshop] [slides-ppt] [slides-pdf]
July 2021: ICML 2021 Long Oral Presentation (presented by Brandon Araki).
The Logical Options Framework.
[icml]
[slides-pdf]
March 2020: NYAS 14th Annual Machine Learning Symposium Spotlight Presentation.
Learning the Optimal Step Size for Gradient Descent on Convex Quadratics.
[symposium] [slides-ppt] [slides-pdf]
October 2019: SOSP 2019 Oral Presentation (presented by Mathias Lécuyer).
Privacy Accounting and Quality Control in the Sage Differentially Private ML Platform.
[slides]
August 2019: Yahoo Research Invited Talk.
Attribute-Efficient Learning of Monomials over Highly-Correlated Variables.
[slides-ppt] [slides-pdf]
June 2019: RSS 2019 Oral Presentation (presented by Brandon Araki).
Learning to Plan with Logical Automata.
[slides] [slide-notes]
March 2019: ALT 2019 Oral Presentation.
Attribute-Efficient Learning of Monomials over Highly-Correlated Variables.
[slides-ppt] [slides-pdf]
March 2019: NYAS 13th Annual Machine Learning Symposium Spotlight Presentation.
Attribute-Efficient Learning of Monomials over Highly-Correlated Variables.
[symposium] [slides]
December 2018: NeurIPS 2018 Workshop on Infer2Control Oral Presentation (presented by Brandon Araki).
Learning to Plan with Logical Automata.
[slides]
July 2018: ICML 2018 Theory of Deep Learning Workshop Oral Presentation (presented by Mikhail Khodak).
A Compressed Sensing View of Unsupervised Text Embeddings, Bag-of-n-Grams, and LSTMs.
May 2018: Master’s Thesis presentation by Mikhail Khodak and Nikunj Saunshi.
A Compressed Sensing View of Unsupervised Text Embeddings, Bag-of-n-Grams, and LSTMs.
[slides]
April 2018: Seminar on Theoretical Machine Learning at the Institute for Advanced Study (presented by Mikhail Khodak).
A Compressed Sensing View of Unsupervised Text Embeddings, Bag-of-n-Grams, and LSTMs.
[slides]
September 2017: Invited talk at Princeton Neuroscience Institute.
Mapping between fMRI responses to movies and their natural language annotations.
[slides]
May 2017: Princeton COS Master’s Thesis Presentation.
Temporally Dependent Mappings Between fMRI Responses and Natural Language Descriptions of Natural Stimuli.
[slides]
December 2016: NeurIPS 2016 MLINI Workshop.
Mapping between Natural Movie fMRI Responses and Word-Sequence Representations.
[slides]
July 2016: Invited Talk at Intel-Princeton Neuroscience Collaboration Meeting.
Decoding fMRI to Text with Context.
[slides]
June 2016: ICML 2016 MVRL Workshop.
A Semantic Shared Response Model.
[slides]
Slides for Expository Presentations
There are several talks I’ve given in seminars and other settings which do not have slides — either they can be found on the notes page or I have not transcribed my handwritten notes into LaTeX yet. The following are the non-research presentations I’ve given with slides.
-
Describing Value Iteration Networks [slides] [course website]
-
Learning Sparse Polynomials over Product Measures [slides] [course website]
-
Optimization Landscape for Tensor Decompositions [slides] [course website]
-
A Survey on Image Captioning with Deep Learning [slides] [course website]
-
A Survey on Deep Learning for Natural Language Processing [slides] [course website]


Reply-to address configured in e-mails sent by this plugin.
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{{< layout}}
{{$pageTitle}}What is your date of birth?{{/pageTitle}}
{{$header}}
Are you 16 or older?
{{/header}}
{{$content}}
{{< hmpo-partials-form}}
{{$form}}
{{#radio-group}}16-or-older{{/radio-group}}
{{#input-submit}}{{/input-submit}}
{{/form}}
{{/ hmpo-partials-form}}
I'll be 16 in the next 3 weeks
It should take around 3 weeks to get your new passport. You need to apply for a 10 year adult passport by answering 'yes' to this question.


phia: Post-Hoc Interaction Analysis
Analysis of terms in linear, generalized and mixed linear models,
on the basis of multiple comparisons of factor contrasts. Specially suited
for the analysis of interaction terms.
| Version: |
0.2-1 |
| Depends: |
car, graphics, stats |
| Imports: |
Matrix, grDevices, methods, utils |
| Suggests: |
nlme, lme4 |
| Published: |
2015-11-07 |
| Author: |
Helios De Rosario-Martinez [aut, cre],
John Fox [ctb],
R Core Team [ctb] |
| Maintainer: |
Helios De Rosario-Martinez <helios.derosario at gmail.com> |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/heliosdrm/phia |
| NeedsCompilation: |
no |
| Materials: |
ChangeLog |
| CRAN checks: |
phia results |
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=phia
to link to this page.


| Hinxton Single Cell Interactive Analysis Environment version 1.1.0 Galaxy version 19.05-dev | |
QuickstartWhat is this?An environment where you can do downstreaming analysis for Single Cell transcriptomics. We provide decomposed analysis steps from Seurat, Scanpy, Scater and SC3 to do clustering analysis, starting from 10x formatted data, EMBL-EBI Single Cell Expression Atlas studies or Loom files (Scanpy only currently). You can visualise results using the integrated UCSC CellBrowser. Check out our example workflows. New to Galaxy, start here! If you are new to Galaxy you might benefit from learning how to use tools, workflows and datasets in this this environment by visiting the Learn Galaxy resources and then coming back. This will help you make the most of this environment and of other Galaxy setups. |


Philosophical conversations
Randomly generated using famous quotes.
Pick two to chat.
Person A
Person B
Converse!


Research and analysis
How national leaders of education and teaching school alliances can work with other schools to close gaps in attainment.
PDF , 643KB , 54 pages
If you use assistive technology (such as a screen reader) and need a version of this document in a more accessible format, please email<EMAIL_ADDRESS>. Please tell us what format you need. It will help us if you say what assistive technology you use.
A high priority for schools is to close gaps in attainment between pupils from disadvantaged backgrounds and their peers.
This report summarises the outcomes and learning for system leaders from a research project in 2012. National leaders of education and teaching school alliances worked together to support:
Examples from case studies explain the work that was undertaken.
The full case studies are available on The National Archives website:


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State
Mode then State
Size by:
None
Trade
Exports
Imports
Color by:
None
Trade
Exports
Imports
Label threshold
NaN
1
2
Mean/Average neutral value


Wordle Clone
This is a simple wordle clone demonstrating DOM manipulations and AJAX calls.
Enter your guess here. The word changes every 2 minutes so hurry up:
seconds to go!
Game Over
Close


box = page['Footer']
box.append(doc.footerHtml)
page = doc.newPage(title='How', name='how.html', template='home')
box = page['Introduction']
box = page['Main']['Content']
Design students meet online with each other and the coaches in regular intervals.
For interaction and exchanging documents a range of techniques are available, e.g. Skype, Google Hangout, Google Docs, offline video, Dropbox, Github, FaceTime and Second Life, to name a few. Selection and usage can be the topic of one of the assignments.
Students get assignments for imaginary design projects, with time frames ranging from several hours to several months. The assignments are challenges, where the specific topics can be filled by the individual students.
Questions how to approach these challenges, research on what skills need to be developed, what knowledge needs to be acquired, what techniques and materials need to be developed and how the project planning should be designed, are all part of assignments.
With regular intervals – ranging from hours to days to once per week – the various levels of intermediate results are presented to the group of students and coaches. The aim of the coaches is to create a safe environment, in which anything can be said about any aspect of the work and the process.
The process of creating such a safe environment – and the finding of methods for feedback – are part of the assignments, and therefor subject to sketching and modification too.
During the presentations feedback is given on the presented work, but also on the presentation itself and on the process and proceedings between the presentations.
Various models are offered to students, showing what their design process could be like. And they are encouraged to created their own, and apply them to their designs.
In the past a magnitude of design methods have been developed, but unfortunately most of them focus on production techniques and deadlines. You may recognize that in your current design practice.
What most design methods don’t do is create space for designers to develop themselves. To allow unintended mistakes. Cuddle solutions that don’t seem to be profitable right away. To spend time on acquiring skills without predefined purpose.
Yet, for the development of skills, such an approach is essential.
DesignDesign.Space offers that environment. To study a specific topic for a defined period of time. Formulating challenges, feed back techniques and design methods that are customized for your development.
Tuition needs to be payed before the training starts. No refund is possible, but participants have the right to build in breaks for some period of time, if that is discussed before hand.
box = page['Main']['Side']
Many of the assignments need collaborating with other online students, who – throughout the process – can have different roles, ranging from colleague to client to user.
Design Game on location at OTIS College of Art and Design. Besides the development of sketching techniques, the design of feedback methods is an important and integral part of every DesignDesign.Space study.
box = page['Section']['Title']
box = page['Section']['0']
Imagine to ask a client which of the visule design parameters will be used for coherency or diversity. E.g. color cannot be the main recognition (“red”) and differentiate at the same time.
box = page['Section']['1']
Nine out of ten clients will confirm that their ideal identity is best defined by a single logo, with consistent use of color, name and typeface.
box = page['Section']['2']
This means that all other parameters don’t have to be defined. Layout, texture, typography and language are not supposed to contribute to recognition of a brand.
box = page['Section']['3']
Or going one step further: if most of the other parameters are consistently used, they may allow a variation of different logo’s.
box = page['OtherMain']['Content']
In general the aim is to bring graduate students as well as experienced designers forward to a space of “WOW!”.
Focus is on design students and their individual goals. Not on predefined course content.
As designer, doing the DesignDesign.Space study, you are open minded and willing to get valuable feedback on your work.
You are interested to improve and change and to participate in the work of colleague students.
You are disciplined to work hard between online sessions, and more interested in the development of skills and challenging assignments than in assessed diploma’s.
box = page['OtherMain']['Side']
Developing sketching techniques should be an important part of any design study.
Arranging a collections of objects in arbitrary order, the layout is hard to remember and to reproduce.
If objects are ordered by height, it needs some time to recognize the rule. But after that, it can be applied to any set of objects.
Ordered by color, the rule is instantly clear, without the to mention to the viewer. This can easily be reproduced.


Internet
`Prev `__
I
`Next `__
--------------
**Internet**: n.
The mother of all networks. First incarnated beginning in 1969 as the
ARPANET, a U.S. Department of Defense research testbed. Though it has
been widely believed that the goal was to develop a network architecture
for military command-and-control that could survive disruptions up to
and including nuclear war, this is a myth; in fact, ARPANET was
conceived from the start as a way to get most economical use out of
then-scarce large-computer resources. Robert Herzfeld, who was director
of ARPA at the time, has been at some pains to debunk the
“survive-a-nuclear-war” myth, but it seems unkillable.
As originally imagined, ARPANET's major use would have been to support
what is now called remote login and more sophisticated forms of
distributed computing, but the infant technology of electronic mail
quickly grew to dominate actual usage. Universities, research labs and
defense contractors early discovered the Internet's potential as a
medium of communication between *humans* and linked up in steadily
increasing numbers, connecting together a quirky mix of academics,
techies, hippies, SF fans, hackers, and anarchists. The roots of this
lexicon lie in those early years.
Over the next quarter-century the Internet evolved in many ways. The
typical machine/OS combination moved from `*DEC* <../D/DEC.html>`__
`*PDP-10* <../P/PDP-10.html>`__\ s and
`*PDP-20* <../P/PDP-20.html>`__\ s, running
`*TOPS-10* <../T/TOPS-10.html>`__ and `*TOPS-20* <../T/TOPS-20.html>`__,
to PDP-11s and `*VAX* <../V/VAX.html>`__\ en and Suns running
`*Unix* <../U/Unix.html>`__, and in the 1990s to Unix on Intel
microcomputers. The Internet's protocols grew more capable, most notably
in the move from NCP/IP to `*TCP/IP* <../T/TCP-IP.html>`__ in 1982 and
the implementation of Domain Name Service in 1983. It was around this
time that people began referring to the collection of interconnected
networks with ARPANET at its core as “the Internet”.
The ARPANET had a fairly strict set of participation guidelines --
connected institutions had to be involved with a DOD-related research
project. By the mid-80s, many of the organizations clamoring to join
didn't fit this profile. In 1986, the National Science Foundation built
NSFnet to open up access to its five regional supercomputing centers;
NSFnet became the backbone of the Internet, replacing the original
ARPANET pipes (which were formally shut down in 1990). Between 1990 and
late 1994 the pieces of NSFnet were sold to major telecommunications
companies until the Internet backbone had gone completely commercial.
That year, 1994, was also the year the mainstream culture discovered the
Internet. Once again, the `*killer app* <../K/killer-app.html>`__ was
not the anticipated one — rather, what caught the public imagination was
the hypertext and multimedia features of the World Wide Web.
Subsequently the Internet has seen off its only serious challenger (the
OSI protocol stack favored by European telecoms monopolies) and is in
the process of absorbing into itself many of the proprietary networks
built during the second wave of wide-area networking after 1980. By 1996
it had become a commonplace even in mainstream media to predict that a
globally-extended Internet would become the key unifying communications
technology of the next century. See also `*the
network* <../T/the-network.html>`__.
--------------
+--------------------------------+----------------------------+-------------------------------------------+
| `Prev `__ | `Up <../I.html>`__ | `Next `__ |
+--------------------------------+----------------------------+-------------------------------------------+
| interesting | `Home <../index.html>`__ | Internet Death Penalty |
+--------------------------------+----------------------------+-------------------------------------------+


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Hello, ! Based on your preference for and development, coupled with your -level experience and interest in , we have narrowed your results down to one of the following 3 languages:
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'We’ll see' - Sammy Ameobi talks about his Nottingham Forest future
The summer arrival from Bolton has proved an astute signing by Forest, and a hit on the terraces
by Barry CooperSammy Ameobi has set his sights on a new contract at Nottingham Forest, having impressed since arriving in the summer.
The winger has proved a popular figure this season under Sabri Lamouchi, clocking up 17 appearances and popping up with a couple of vital goals.
After leaving Bolton Wanderers in June, Ameobi penned a one-year deal at the City Ground, though he hopes his performances thus far are doing him no harm and hopes to secure a longer-term deal on Trentside.
“Yes, absolutely,” said the 27-year-old when asked if he’d like to stay at the club.

“We’ll see."
Ameobi’s first goal in the Garibaldi red came at Stoke City, a towering header to put his side 2-1 up after being a goal down, and he revealed just how that goal made him feel.
“Relieved.
“To go 1-0 down is never good, to come back and get the goal we were relieved and we wanted to keep the result going.”
Having been rested for Forest’s 3-0 win over Derby County in August, Ameobi was pivotal in ensuring the Reds were 1-0 winners in the Championship last weekend, an experience he quite enjoyed, coming on the back of bagging the winner at Luton.
“It was wonderful,” beamed the former Newcastle United youngster.
“A wonderful experience.
“It’s the first one I’ve played in here so, it was great and an unbelievable atmosphere.
“I loved it.”


 Also do you have a new computer?  Do you know inverse log-in stuff?
my mom
Nvrmnd. I figured out what it was.
my mom
Be sure to check your box.  I thought the dark-faced guy was a guy in a ski mask.


Download Code
The aim of this note is to explain how one can solve an optimal control problem with the moment method. While the theory is collected in [1], we will explain how one is able to use the Globtipoly toolbox, which is a powerful toolbox able to solve many other problems. This toolbox is available in http://homepages.laas.fr/henrion/software/gloptipoly3/. A more detailed documentation is provided in this link, if you are insterested in other applications than the optimal control problem.
The use of this toolbox needs a proper installation either of Sedumi or the Mosek solvers, which are toolboxes instrumental to solve numerically SDP (Semidefinite Program) problems, i.e. optimization problems expressed with LMI (Linear Matrix Inequalities) constraints.
This note does not aim at explaining all the details of the toolbox Globtipoly, since there exists already the paper [2] which introduces really well the problem. It does not aim neither at introducing in details the moment framework developed by Jean Bernard Lasserre and Didier Henrion, which is much more general than the optimal control problem framework. In this note, we just give a simple example to explain how this method can be used in the context of optimal control (especially for ODEs). Thanks to the recent paper [3], we also think that this framework might also work for optimal control of PDEs.
FRAMEWORK
We focus on the following ordinary differential equations:
where $x$ belongs to a subset $X$ of $\mathbb{R}^n$ and $u$ to a subset $U$ of $\mathbb{R}^m$. We assume that $f$ is a polynomial of $x$ and $u$. Moreover, we assume that $X$ and $U$ can be written with finitely many polynomial inequalities. The Gloptipoly toolbox allows to solve the following kind of optimal control problem:
where $X_T$ is also a subset of $\mathbb{R}^n$ defined with finitely many polynomial inequalities and $l$ is also a polynomial in the variables $x$ and $u$.
A SIMPLER EXAMPLE AS A MOTIVATION
We focus on a specific example to make the reading of thenote easier. We have
$u\in\mathbb{R}$ and:
It is a simple chain of integrators, really well-known in automatic control theory. As described in [1], the related system can be equivalently rewritten as follows:
where $g$ is any test function in $C^1(X)$, $\mu_1(x)$ is a measure supported on a compact set $K_1$ representing the constraints on $x$ and $u$, $\mu_2(x)=$ is supported on a given compact set $K_2$ corresponding to performance requirements. For example $K_2 = 0$ indicates that state $x$ must reach the origin.
The approximation provided by Gloptipoly consists in reducing the class of test function $g$ to be polynomials, with maximal degree $d$. This maximal degree $d$ is the parameter of approximation of the program. As proved in [1], the higher the degree $d$ is, the better is the result of the approximation.
Our aim is to find the minimal time so that the trajectories of the system go to $0$. Obviously, this result is already known, but we provide this simple example to make clear the use of the Globtipoly toolbox
IMPLEMENTATION
Before going to the optimal control problem, some (easy) technical lines of command are necessary for Gloptipoly to work.
First, you have to add to the path the toolbox Globtipoly
untar('http://homepages.laas.fr/henrion/software/gloptipoly3/gloptipoly3.tar.gz')
addpath(genpath('gloptipoly3'))
Second, you have also to add to the path the toolbox Sedumi.
unzip('https://github.com/sqlp/sedumi/archive/master.zip')
addpath(genpath('sedumi-master'))
Then, you are ready to define the optimization problem.
x0 = [1; 1]; u0 = 0; %% initial conditions
d = 6; %% maximum degree of test function.
We compute the analytic minimum time. We want to know whether we are able to compute the good one with the toolbox Gloptipoly.
if x0(1) >= -(x0(2)^2-2)/2
tmin = 1+x0(1)+x0(2)+x0(2)^2/2;
elseif x0(1) >= -x0(2)^2/2*sign(x0(2))
tmin = 2*sqrt(x0(1)+x0(2)^2/2)+x0(2);
else
tmin = 2*sqrt(-x0(1)+x0(2)^2/2)-x0(2);
end
We define measures for constraints. In other words, we also define the vector field under consideration.
The command mpol in Globtipoly allows to define the variables under consideration. One can then define polynomials with respect to these variables.
The command meas allows to define a measure depending on several variables. Hence, when writing meas([x_1;u_1]), one is defining a measure depending on the variables x_1 and u_1.
mpol x1 2
mpol u1
m1 = meas([x1;u1]);
We now define a measure associated to $x_2$, which will be related to some performance requirement. Indeed, we will impose that this variable is dissipative.
We then define the vector field.
We now define the test functions as polynomials, with maximal degree $d$. The command mmon in Globtipoly allows to define monomials up to an order $d$.
g1 = mmon(x1,d);
g2 = mmon(x2,d);
It is also necessary to assign the initial conditions, for the states as well for the control.
assign([x1;u1],[x0;u0]);
g0 = double(g1);
We define $K_1$ and $K_2$. The set $K_1$ is defined as: $K_1= \lbrace x_1,u_1 \in \mathbb{R}^2\mid x_1(2)\geq -1,: u_1^2\leq 1\rbrace$ and $K_2$ is defined as: $K_2 =\lbrace x_2\in\mathbb{R}\mid x_2^2\leq 0\rbrace$.
We have also to define the cost function of the problem under consideration. The one we are considering is quite simple and just reduces to being
In terms of functions, this means that you are minizing $x_1(t)$. This implies in particular that you are looking for the minimal time such that the trajectory $(x_1(t),x_2(t))$ will converge to $(0,0)$.
In other words, we are asking that the mass the measure $\mu_1$ is minimal.
Finally, we define also the differential equation with the polynomials truncated up to the order $d$. The command mom corresponds to the integral of polynomials against the suitable measure. For instance, for mom(g_2), one integrates the the polynomial g_2 against the measure $\mu_2$.
P = msdp(min(mass(m1)),... %%Definition of the cost function
u1^2 <= 1,... %% Definition of $K_1$
x1(2) >= -1,... %% Definition of $K_&$
x2'*x2 <= 0,... %% Definition of $K_2
mom(g2) - g0 == mom(diff(g1,x1)*f)); %% Definition of the dynamics.
GloptiPoly 3.8 of 15 December 2014
Define moment SDP problem
Valid objective function
Number of support constraints = 3
Number of moment constraints = 28
Measure 1
Degree = 6
Variables = 3
Moments = 84
Measure 2
Degree = 6
Variables = 2
Moments = 28
Relaxation order = 3
Total number of moments = 112
Generate moment and support constraints
Generate moment SDP problem
The command msdp allows to define the problem and all the constraints. As written in [1], this means that you are transforming the problem on functions into a SDP (Semi-definite programming) problem.
Once you do that, one has to solve this SDP problem. The command msol allows to do that.
GloptiPoly 3.8 of 15 December 2014
Solve moment SDP problem
*****************************************************
Calling SeDuMi
SeDuMi 1.32 by AdvOL, 2005-2008 and Jos F. Sturm, 1998-2003.
Alg = 2: xz-corrector, Adaptive Step-Differentiation, theta = 0.250, beta = 0.500
Put 28 free variables in a quadratic cone
eqs m = 112, order n = 59, dim = 766, blocks = 7
nnz(A) = 597 + 0, nnz(ADA) = 10192, nnz(L) = 5152
it : b*y gap delta rate t/tP* t/tD* feas cg cg prec
0 : 6.97E-01 0.000
1 : -4.85E+00 2.61E-01 0.000 0.3749 0.9000 0.9000 -0.46 1 1 7.9E+00
2 : -1.58E+01 1.08E-01 0.000 0.4124 0.9000 0.9000 -0.63 1 1 5.7E+00
3 : -1.60E+01 4.52E-02 0.000 0.4189 0.9000 0.9000 0.74 1 1 2.0E+00
4 : -7.27E+00 1.65E-02 0.000 0.3663 0.9000 0.9000 1.88 1 1 4.7E-01
5 : -4.16E+00 5.56E-03 0.000 0.3361 0.9000 0.9000 1.60 1 1 1.3E-01
6 : -3.52E+00 2.17E-03 0.000 0.3912 0.9000 0.9000 1.07 1 1 5.0E-02
7 : -3.37E+00 1.06E-03 0.000 0.4892 0.9000 0.9000 0.88 1 1 2.6E-02
8 : -3.24E+00 4.94E-04 0.000 0.4642 0.9000 0.9000 0.70 1 1 1.5E-02
9 : -3.17E+00 2.14E-04 0.000 0.4334 0.9000 0.9000 0.58 1 1 7.8E-03
10 : -3.12E+00 9.06E-05 0.000 0.4235 0.9000 0.9000 0.46 1 1 4.3E-03
11 : -3.08E+00 4.45E-05 0.000 0.4907 0.9000 0.9000 0.48 1 1 2.6E-03
12 : -3.05E+00 2.39E-05 0.000 0.5378 0.9000 0.9000 0.34 1 1 1.9E-03
13 : -3.02E+00 1.07E-05 0.000 0.4486 0.9000 0.9000 0.46 1 1 1.1E-03
14 : -2.98E+00 5.94E-06 0.000 0.5540 0.9000 0.9000 0.23 1 1 8.3E-04
15 : -2.95E+00 2.34E-06 0.000 0.3932 0.9000 0.9000 0.35 2 1 4.4E-04
16 : -2.91E+00 1.06E-06 0.000 0.4528 0.9000 0.9000 0.22 2 2 3.1E-04
17 : -2.88E+00 2.15E-07 0.000 0.2032 0.9000 0.7324 0.34 2 2 1.8E-04
18 : -2.84E+00 9.48E-08 0.000 0.4410 0.7706 0.9000 0.22 2 2 1.2E-04
19 : -2.82E+00 4.23E-08 0.000 0.4464 0.9000 0.9000 0.34 3 2 7.3E-05
20 : -2.78E+00 1.96E-08 0.000 0.4627 0.9000 0.9000 0.20 5 5 5.2E-05
21 : -2.76E+00 8.49E-09 0.000 0.4334 0.9000 0.9000 0.34 7 7 3.0E-05
22 : -2.73E+00 3.76E-09 0.000 0.4427 0.9000 0.9000 0.19 8 8 2.1E-05
23 : -2.70E+00 1.56E-09 0.000 0.4156 0.9000 0.9000 0.33 12 12 1.2E-05
24 : -2.67E+00 6.45E-10 0.000 0.4129 0.9000 0.9000 0.20 14 14 7.9E-06
25 : -2.66E+00 2.71E-10 0.000 0.4202 0.9000 0.9000 0.35 41 41 4.5E-06
Run into numerical problems.
iter seconds digits c*x b*y
25 0.4 Inf -2.6569125651e+00 -2.6557155494e+00
\vertAx-b\vert = 9.3e-06, [Ay-c]_+ = 1.9E-06, \vertx\vert= 5.2e+03, \verty\vert= 4.9e+04
Detailed timing (sec)
Pre IPM Post
6.598E-03 2.390E-01 7.343E-04
Max-norms: \vert\vertb\vert\vert=1, \vert\vertc\vert\vert = 1,
Cholesky \vertadd\vert=1, \vertskip\vert = 7, \vert\vertL.L\vert\vert = 3155.
*****************************************************
Check feasibility (eps = 1.0000e-03):
Marginally feasible SDP: residual = -5.0513e-07
Check Euclidean norm of solution (max = 1.0000e+06):
Norm = 4.9305e+04
Check ranks of moments matrices (rel gap svd = 1.0000e-03):
Measure 1
Rank shift = 1
Moment matrix of order 1 has size 4 and rank 4
Moment matrix of order 2 has size 10 and rank 10
Moment matrix of order 3 has size 20 and rank 20
Measure 2
Rank shift = 1
Moment matrix of order 1 has size 3 and rank 1
Rank conditions cannot ensure global optimality
Try to extract solutions (rel tol basis detection = 1.0000e-06):
Measure 1
Incomplete basis - no solution extracted
Global optimality cannot be ensured
Measure 2
Maximum relative error = 0.0000e+00
1 solution extracted
Inconsistent number of solutions amongst respective measures
No globally optimal solution could be extracted
Global optimality cannot be ensured
You display the minimal time and the lower bound of the cost functional.
disp(['Minimum time = ' num2str(tmin)]);
disp(['LMI ' int2str(d) ' lower bound = ' num2str(obj)])
Minimum time = 3.5
LMI 6 lower bound = 2.6557
For the initial condition x0 = [1 1] the exact minimum time is equal to 3.5. In table 1 of [2], a table is provided where you can see that when increasing $d$ the minimum time becomes closer and closer to the analytic one. We copy it in the note.
Conclusion
As noticed before, this note aimed at providing a quick course on how using the toolbox Gloptipoly toolbox to solve optimal control problem. The document [2] provides more examples, even for other kinds of optimization problem. Hence, we refer the interested reader to this document if he is interested in using this toolbox for other problems. Let us note moreover that this toolbox has been used to solve nonlinear hyperbolic PDEs, in the paper [3].
References
[1] J. B. Lasserre, D. Henrion, C. Prieur, and E. Trélat, Nonlinear optimal control via occupation measures and LMI-relaxations, SIAM J. Control Opt., vol. 47, 4, pp. 1643-1666, 2008.
[2] D. Henrion, J.B. Lasserre and J. Löfberg. GloptiPoly 3: moments, optimization and semidefinite programming. Optimization Methods & Software, 24(4-5), 761-779, 2009.
[3] S. Marx, T. Weisser, D. Henrion and J.B. Lasserre. A moment approach for entropy solutions to nonlinear hyperbolic PDEs arXiv preprint arXiv:1807.02306


--- layout: post status: publish published: true title: VMworld 2010 - General Session - Live Blogging author: display_name: iguy login: iguy email<EMAIL_ADDRESS>url: '' author_login: iguy author_email<EMAIL_ADDRESS>wordpress_id: 499 wordpress_url: http://itsjustanotherlayer.com/?p=499 date: !binary |- MjAxMC0wOC0zMSAxMTowMTo1NCAtMDUwMA== date_gmt: !binary |- MjAxMC0wOC0zMSAxNjowMTo1NCAtMDUwMA== categories: - VMware tags: - vmworld comments: - id: 131 author: Eric Feistel author_email<EMAIL_ADDRESS>author_url: '' date: !binary |- MjAxMC0wOS0wMyAxMTo0NTozMSAtMDUwMA== date_gmt: !binary |- MjAxMC0wOS0wMyAxNjo0NTozMSAtMDUwMA== content: The company that VMware acquired was Integrien (www.integrien.com), not Integreon (www.integreon.com). Similar names, but totally different companies. - id: 132 author: iguy author_email<EMAIL_ADDRESS>author_url: http://www.itsjustanotherlayer.com date: !binary |- MjAxMC0wOS0wMyAxNjoxNjozMyAtMDUwMA== date_gmt: !binary |- MjAxMC0wOS0wMyAyMToxNjozMyAtMDUwMA== content: Thanks. I've updated the post with the correct company name. ---
Hello one and all. Its a Live Blog going down today. Enjoy the live blogging and check out @iankoenig on twitter for even more live information.
Update 9:04am:
Hanging out with Virtualization-spotlight.com owner chatting about the cloud. Waiting for the session to start. What coolness do we have this year?
Update: 9:10am:
The opening presentation video asks the great question of "What is the cloud?". A cute Matrix like fun here.. A great quote:
Update: 9:27am
Virtual Roads. Actual Clouds. The theme this year.
Starting down this road and it is a journey:
Most customers start with cost efficiency. They find that money savings are huge. As they use it they find out that VMs are easier to manage and use.
The next step is Quality of Service. Businesses find out that can get more reliability without the high cost of delivery. Many applications run better as virtual machines. Sharepoint/Exchange are mentioned all the time to VMware that it is better.
The latest step this year is IT as a Service (ITaaS). Phase 3 is all about agility. How can IT offer computer resources for giving the business the ability to quickly consume these resources to get to value faster is the question?
IT as a Service == Optimizing IT production for business consumption.
Some of the great innovations is that by having OS instances that aren't owning the hardware means you have options. Large change in how IT addresses computing.
Can start talking about the computer food groups of compute, storage, network, security and work on decreasing OpEx and enhancing security. One item that has been missing out of this has been security and is now a serious focus by VMware.
Now because we can separate from hardware and have defined what a datacenter is we can start abstracting away from the datacenter itself and virtualize that.
Realistically Hybrid Cloud is the right approach by Paul Martiz. We need management. We need standards.
Update 9:39am:
The current solutions really address the old applications and approaches. The next true step is how can we make new applications more scalable and cloud friendly. So a new application platform needs to be defined and delivered. What are the common services they need?
Common Management, Common Services and Open frameworks. These frameworks have to be able to handle whatever programming languages are coming. Every time you tie to a language someone will come along with a new language that solves some problem. Need to stay away form that wherever we can.
These Frameworks also need to connect to different clouds. Google App Engine, vmForce, vCloud.
Update 9:47am:
Different devices are coming into the business environment. IT has no choice on this. It will come one way or another and IT will need to figure out how to deliver secure, manageable approaches. iPads are coming in over night.
The third layer of innovation needed called "New End User Access". This is the stack that is now the new IT one for the cloud era.
Update 9:51am:
Steve Herrod's turn to show the details of the theory from Paul Maritz.
Again vSphere is the basis of this all. Can really deliver and is getting better and faster on every release. Policy driven SLAs with Network IO control and Storage IO control. If you know about vSphere 4.1 already this part is a good review.
Integrien, the acquisition of the day. VMware is buying them for their proactive heatmap style management and allocation. This is a new style of management to show the tons of information in easier to process displays. Very graphical.
Update 10:02am:
Herrod: For IT as a Service is key about moving to offering an "App Store" for clients at the business. They want services, not VMs. They want a database server, web server. Not a Windows/Linux/Unix box generally.
Virtual Datacenters are a key way to discuss this. To provide the services you define the SLAs an function of that datacenter. So you can setup just what you need and what levels are necessary.
vCloud Director is live. This is the key management tool for this entire environment.
Update 10:12am:
vShield platform is a critical to making the Cloud work. Need a common set of services that will offer some basic security available everywhere. This is both on the private and the public cloud. vCloud Director is on both sides of the fence and offers the same functionality everywhere and can span the private to the public in a secure way.
Update 10:26am:
Now we are on the Application platform layer and is what vFabric is all about. It is a common set of services available to make new application cloud friendly. The great thing about this is it will work with Ruby, Python, Java etc.
Update 10:27am:
The final area is the End User Computing experience. View 4.5 is the part of modernizing the desktop direction. Released today. View 4.5 has the ability to lower the cost of acquistion below $500 a system which is below the physical desktop costs.
The now is to call User-centric IT. We need to get away from PC Centric. Most consumers are use to using any device. Why not move to User focused?
Project Horizon demo going on. This is focused around User-Centric IT. This allows you to have whatever applications you are licensed are immediately provisioned to your virtual workstation. Single sign on and user focused. Not device. Some applications may not work well on a given devices.
A good demo of View iPad client with Project Horizon. This is the future of IT.
Update: 3 Sept 2010 - Fixed the company name (Integrien) that VMware bought


val SHA512_256: DLSequence
DLSequence (ASN1Sequence) for SHA512 truncated to 256 bits, used in SPHINCS-256 signature scheme.


New Features for Gamma
SymPy Gamma is essentially SymPy’s clone of Wolfram|Alpha, at least in terms of math features. We just rolled out some new features:
Improved plotting, still based on D3.js
Multiple graphs on one plot:
Polar and parametric equations:
Diophantine equation solving:
diophantine(3*x**2 + 4*y**2 - 5*z**2 + 4*x*y - 7*y*z + 7*z*x)
Recurrence relation solving:
rsolve(y(n+2)-y(n+1)-y(n), y(n), {y(0): 0, y(1): 1})
- Boolean logic results:
An updated version of SymPy, and various other improvements
Gamma's (and by extension, SymPy's) parsing still needs work, though, when it comes to the implicit style. Consider, for instance, the input y(x)
. Is this
- The function \(\mathrm{y}(x)\), or
- The product \(yx\)?
This makes inputs ambiguous, at least to the parser. For instance, it makes sense that expand(a(x + 1) + b(x + 2))
should be \(ax + bx + a + b\) and not \(\mathrm{a}(x+1) + \mathrm{b}(x+2)\). Meanwhile, rsolve(y(n+2) - y(n+1) - y(n), y(n))
wouldn't make any sense as \(\mathrm{rsolve}(ny + 2y - ny - y - ny, ny)\).
How do we solve this problem? I see three, non-mutually-exclusive ways:
- Provide an "interpret as" functionality, like Wolfram|Alpha. For functions, you can also explicitly specify a function symbol with
Function("f")(x)
, though this is rather tedious to type. - Give the parser a whitelist/blacklist of functions to use implicit function or implicit multiplication syntax.
- Try it both ways and take the one that doesn't raise an exception.
So in the future, I'd like to improve SymPy's parser more -- and hopefully, someday add natural language parsing to Gamma. Dealing with these ambiguities is a first step towards that.
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Methods defined here:
- __init__(self, file)
- Initialize with a file object
- bin(self, s)
- Return a value as a binary string
- calc_max_bits(self, signed, values)
- Calculates the maximim needed bits to represent a value
- close(self)
- Closes the stream
- read(self, count=0)
- Read
- readACTIONRECORD(self)
- Read a SWFActionRecord
- readCLIPACTIONRECORD(self, version)
- Read a SWFClipActionRecord
- readCLIPACTIONS(self, version)
- Read a SWFClipActions
- readCLIPEVENTFLAGS(self, version)
- Read a SWFClipEventFlags
- readCURVEDEDGERECORD(self, num_bits)
- Read a SWFShapeRecordCurvedEdge
- readCXFORM(self)
- Read a SWFColorTransform
- readCXFORMWITHALPHA(self)
- Read a SWFColorTransformWithAlpha
- readEncodedU32(self)
- Read a encoded unsigned int
- readFB(self, bits)
- Read a float using the specified number of bits
- readFILLSTYLE(self, level=1)
- Read a SWFFillStyle
- readFILTER(self)
- Read a SWFFilter
- readFIXED(self)
- Read a 16.16 fixed value
- readFIXED8(self)
- Read a 8.8 fixed value
- readFLOAT(self)
- Read a float
- readFLOAT16(self)
- Read a 2 byte float
- readFOCALGRADIENT(self, level=1)
- Read a SWFFocalGradient
- readGLYPHENTRY(self, glyphBits, advanceBits)
- Read a SWFGlyphEntry
- readGRADIENT(self, level=1)
- Read a SWFGradient
- readGRADIENTRECORD(self, level=1)
- Read a SWFColorTransformWithAlpha
- readKERNINGRECORD(self, wideCodes)
- Read a SWFKerningRecord
- readLANGCODE(self)
- Read a language code
- readLINESTYLE(self, level=1)
- Read a SWFLineStyle
- readLINESTYLE2(self, level=1)
- Read a SWFLineStyle2
- readMATRIX(self)
- Read a SWFMatrix
- readMORPHFILLSTYLE(self, level=1)
- Read a SWFMorphFillStyle
- readMORPHGRADIENT(self, level=1)
- Read a SWFTextRecord
- readMORPHGRADIENTRECORD(self)
- Read a SWFTextRecord
- readMORPHLINESTYLE(self, level=1)
- Read a SWFMorphLineStyle
- readRECT(self)
- Read a SWFMatrix
- readRGB(self)
- Read a RGB color
- readRGBA(self)
- Read a RGBA color
- readSB(self, bits)
- Read a signed int using the specified number of bits
- readSHAPE(self, unit_divisor=20)
- Read a SWFShape
- readSHAPEWITHSTYLE(self, level=1, unit_divisor=20)
- Read a SWFShapeWithStyle
- readSI16(self)
- Read a signed short
- readSI32(self)
- Read a signed int
- readSI8(self)
- Read a signed byte
- readSTRAIGHTEDGERECORD(self, num_bits)
- Read a SWFShapeRecordStraightEdge
- readSTYLECHANGERECORD(self, states, fill_bits, line_bits, level=1)
- Read a SWFShapeRecordStyleChange
- readSYMBOL(self)
- Read a SWFSymbol
- readString(self)
- Read a string
- readTEXTRECORD(self, glyphBits, advanceBits, previousRecord=None, level=1)
- Read a SWFTextRecord
- readUB(self, bits)
- Read a unsigned int using the specified number of bits
- readUI16(self)
- Read a unsigned short
- readUI32(self)
- Read a unsigned int
- readUI8(self)
- Read a unsigned byte
- readZONEDATA(self)
- Read a SWFZoneData
- readZONERECORD(self)
- Read a SWFZoneRecord
- readbits(self, bits, bit_buffer=0)
- Read the specified number of bits from the stream
- readraw_tag(self)
- Read a SWFRawTag
- readtag_header(self)
- Read a tag header
- reset_bits_pending(self)
- Reset the bit array
- seek(self, pos, whence=0)
- Seek
- skip_bytes(self, length)
- Skip over the specified number of bytes
- tell(self)
- Tell
Data descriptors defined here:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
Data and other attributes defined here:
- FLOAT16_EXPONENT_BASE = 15
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Books are among the best things because there are books for anyone and everyone. Sometimes it is hard to find a book to read..Luckily, there are many websites available now to help you pick the very best one.
Some great websites to checkout:
Goodreads -great site that lets you connect with friends!
Whichbook -great site to pick a book based on your interests


Picture the scene. Your big corporate meeting, people flying down from Europe for a day. Let’s all meet they said. We insist we have everyone. Schedule for late Thursday afternoon? Super.
I coordinate with a local contact to attend. Oh, I can’t make it, I have to pick up my kids Thursday afternoon. Right. How about a different time? Yea, that’s fine.
My battery proceeded to die in the evening. So he called me, and I missed it. Around 10 p.m., when I got around to checking e-mail, I see a “I was expecting a call from you.” There was another e-mail regarding a project our companies were partnering on. I had an issue with it, and it was urgent, so I replied questioning his e-mail.
His response five minutes later: “I did not hear back from you regarding the meeting.” I replied I did not get a confirmation so I will get back to him on that in morning. And well, you didn’t answer my question.
I message him after the meeting was confirmed in the morning. He proceeds to call me and say “This is why I was trying to call you yesterday. I can’t make the new time” Eh, what now?!
Fine, you can’t make it. But what am I supposed to figure out when you say I didn’t hear back from you on the meeting. Instead of typing that, why didn’t you type that you couldn’t make the time. Instead of typing “waiting for your call”, couldn’t you have bloody told me what the problem was so when I did check it, I could react?
Let me add that 15 minutes after the scheduled time, he called me. When I returned the call, he told me he wanted to know how the meeting had gone. Er. Did you not propose the time that you then cancelled? You *knew* I’d be in the meeting because it was on your damned calendar as well.
And we wonder why we don’t get a lot of stuff done here. Even though I’m on topic, I will not discuss our favorite telco provider today. But seriously, what is it with simple professionalism around these parts. Why is it so painfully lacking. Inform people what to do, what you want. Communicate! Telling me I’m being transparent with you doesn’t make you that, by the way.
If I wasn’t leaving out the country for two weeks, I’m fairly certain another post on customer service would be on its way. Until then, make do with this happy excerpt I received the other day:
Japanese attitude for work:
If someone can do it, you can do it too :)
If no one can do it, you must do it!
Arabic version:
If someone can do it, let him do it!
If no one can do it, why should I do it?
And yes, this was forwarded quite graciously by an Arab.


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Body
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// Test single trace
from pymc.examples import arbitrary_stochastic
forestplot(arbitrary_stochastic.trace)
autocorrplot(arbitrary_stochastic.trace)
with asmod.model as model:
start = model.test_point
h = find_hessian(start)
step = Metropolis(model.vars, h)
trace = sample(3000, step, start)
forestplot(trace)
autocorrplot(trace)