--- title: About Sitecore Commerce Cookbook linkTitle: About menu: main: weight: 10 --- {{< blocks/cover title="About Sitecore Commerce Cookbook" image_anchor="bottom" height="min" >}}
Recipes and menus for Sitecore Commerce.
{{< /blocks/cover >}} {{% blocks/lead %}} Sitecore Commerce Cookbook contains recipes and menus to use with Sitecore Commerce. Just like a real cookbook, there are basic recipes that teach you how to do simple things (like how to boil an egg) and more difficult recipes (how to make a souffle). Once you have mastered the recipes, you can start combining the recipes into menus to create more advanced features. {{% /blocks/lead %}}


| hook_plot_html {knitr} | R Documentation |
These hook functions define how to mark up graphics output in different output formats.
hook_plot_html(x, options) hook_plot_asciidoc(x, options) hook_plot_tex(x, options) hook_plot_md(x, options) hook_plot_rst(x, options) hook_plot_textile(x, options)
x |
Filename for the plot (a character string). |
options |
A list of the current chunk options. |
Depending on the options passed over, hook_plot_tex
may return the
normal \includegraphics{} command, or \input{} (for tikz
files), or \animategraphics{} (for animations); it also takes many
other options into consideration to align plots and set figure sizes, etc.
Similarly, hook_plot_html
, hook_plot_md
and
hook_plot_rst
return character strings which are HTML, Markdown, reST
code.
In most cases we do not need to call these hooks explicitly, and they were
designed to be used internally. Sometimes we may not be able to record R
plots using grDevices::recordPlot()
, and we can make use of
these hooks to insert graphics output in the output document; see
hook_plot_custom
for details.
A character string of code, with plot filenames wrapped.
https://yihui.org/knitr/hooks/
# this is what happens for a chunk like this # <<foo-bar-plot, dev='pdf', fig.align='right'>>= hook_plot_tex("foo-bar-plot.pdf", opts_chunk$merge(list(fig.align = "right"))) # <<bar, dev='tikz'>>= hook_plot_tex("bar.tikz", opts_chunk$merge(list(dev = "tikz"))) # <<foo, dev='pdf', fig.show='animate', interval=.1>>= # 5 plots are generated in this chunk hook_plot_tex("foo5.pdf", opts_chunk$merge(list(fig.show = "animate", interval = 0.1, fig.cur = 5, fig.num = 5)))


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Google Pixel 4 Display Brightness Artificially Limited to 450 Nits - Gizchina.com
by PierreGoogle Pixel 4 Display Brightness Artificially Limited to 450 Nits
5 (100%) 2 votes
It would appear as bad news aren’t over for the owners Google’s latest flagship – the Pixel 4. In addition to having a display that only works at the much touted 90Hz frequency in certain occasions, while dropping to 60Hz in others, the device has now been proven to have another limitation of some sort.
XDA’s editor Mishaal Rahman did indeed found out that the maximum brightness of Google Pixel 4 is only about 450 nits. Far lower than the brightness of other flagships in 2019; most phones in this category often sport a brightness of over 600-700 nits.
Pixel 4 ‘s Display Brightness Artificially Limited to 450 Nits
It was then pointed out that pointed out that Google’s flagship phone display isn’t bright enough for outdoor use, which obviously could make it hard to use for some buyers. So why did Google go with this low brightness display?
Well, the truth is that the screen on the Pixel 4 is as good as many others on different flagships. The problem does instead lay in the software.
Google is indeed limiting the brightness of the display in order to save battery. Why is that so important? Most likely because the fourth gen Pixel phone comes with a 2800mAh capacity battery. One of the smallest we’ve seen in the last years, while other manufacturers equip their devices with 4000mAh juice packs nowadays.
The software limitation applied by Google becomes obvious when HDR videos are played. The smartphone does indeed go full brightness to show the best possible dynamic range. When you quit the video you’re back to 450 nits maximum brightness though.
Now, it is possible to modify the kernel to let the smartphone set the display to the brightest setting. To do so you’ll have to get root privileges which void the warranty.
Fun fact, well not to fun for Pixel 4 owners but still, the Android device is capable of achieving a brightness of 610 nits. Do not expect to admire it for long with the tiny battery inside though.
What do you guys think about this new controversy? Do you own a Pixel 4? Let us know down below!


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{% load static %}
{% block style %}
{% endblock style %}
{% block content %}
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--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/user_attribute.2C.20mk_cache.html ---
@Simon Hudon, is there any chance you could quickly explain how user_attribute X Y
works?
I'm struggling to work out what's going on in attribute caching. In particular, in cache_cfg
, the mk_cache
field is meant to be a list name -> tactic X
. When is this function invoked? What is the list of names passed to it?
It seems that the type X
is some global cache object associated with the attribute, and the type Y
is a "decorator" on every name that has been tagged with the attribute, that you can recover using attr.get_param name
, which is a tactic Y
.
But how do you interact with the X
?
... Okay, I think I understand.
the function in mk_cache
is called some subset of the times that attr.get_cache
is called.
Certainly if attr.get_cache
hasn't been called before, mk_cache
runs. If any declarations have had the attribute added since the last call to attr.get_cache
, mk_cache
runs.
When nothing has changed since the last call to attr.get_cache
, mk_cache
may or may not run...! I'm guessing this nondeterministic behaviour might be a race condition.
This seems.... not very useful. :-) In particular, when you add the attribute to a new declaration, there's no way to update the old value of the cache, because mk_cache
... oh, can mk_cache
call get_cache
? But still, it seems there's no way to know which declarations have newly received the attribute since the last call to mk_cache
, as mk_cache
is just passed the entire list of names, so you're still having to look at all the names that carry the attribute.
and in any case, no, mk_cache
cannot call get_cache
(unless your goal is SIGBUS).
Interesting. I didn't know the last bit.
I haven't confirmed it but I believe this works on cache invalidation logic. Every time you add the attribute, you invalidate the cache. Then, when you call get_cache
, you rebuild the cache. The idea is that you can add the attribute on a few lemmas and if you don't query the cache in between, it should fairly fast. After that, you can use the cache many time. The first time is going to be the most expensive but after that, every invocation will be very fast.
And I suspect that not building the cache incrementally is done to make the cache more reliable: mk_cache
expresses a simple relation between the set of declaration that has the attribute and what the cache should be. If you make it incremental it's much harder to use
And very easy to get it wrong
The slowest thing you can do from that perspective (which I do not think is any slower than not having a cache) is have a long sequence where you set an attribute, then query the cache, then set an attribute and so on. If you want to make those faster, you can do as follows:
lemma foo1 ... lemma foo2 ... lemma foo3 ... lemma foo4 ... lemma foo5 ... attribute [my_attribute] foo1 foo2 foo3 foo4 foo5
I don't think it will be much of a gain unless you have a lot of lemmas that don't depend on each other through your tactic.
I would wager to guess that mk_cache
is run 1) as soon as the tagged declaration is parsed 2) when you call get_cache
and it can't find a cache 3) when you call get_cache
and more declarations have been marked with the user attribute since the last time the cache was computed.
I was more interested in the following scenario: If I have two declarations in two files which do not import each other, both marked with the user attribute, is there any way that running get_cache
in one file will also include the cached declaration in the other file?
Or do I have to have a master file which imports both files? And the cache has to be recomputed in that file?
Or do I have to have a master file which imports both files? And the cache has to be recomputed in that file?
I'm pretty certain you need a master file, and the cache will be recomputed there. Anything else would require global mutable state in the environment, and that seems unlikely.
The fact that there is a race condition is and the computation of the cache is nondeterministic it pretty easy to verify. Run the following in VSCode, and read the trace messages:
-- open native open tactic @[user_attribute] meta def example_attribute : user_attribute unit unit := { name := `example, descr := "An example attribute", cache_cfg := { mk_cache := λ ls, (do trace format!"names: {ls}"), dependencies := [] }, after_set := some $ λ name priority persistent, (do trace format!"set {name}"), before_unset := some $ λ name persistent, (do trace format!"unset {name}") } def f := 3 def g := 4 section local attribute [example] f local attribute [-example] f local attribute [example] f end -- Notice no "unset" at the end of the section? section run_cmd success_if_fail (example_attribute.get_param `f >>= trace) local attribute [example] f run_cmd example_attribute.get_param `f >>= trace end set_option trace.user_attributes_cache true attribute [example] f run_cmd example_attribute.get_cache >>= trace -- it seems non-deterministic whether this next line finds a cached value run_cmd example_attribute.get_cache >>= trace attribute [example] g run_cmd example_attribute.get_cache >>= trace run_cmd example_attribute.get_cache >>= trace attribute [example] g run_cmd example_attribute.get_cache >>= trace run_cmd example_attribute.get_cache >>= trace
In any case... The reason I'm currently interested in this is my library_search
tactic, which requires looking over ever declaration in the library. It actually seems to be (incredibly?) fast already, but I was hoping to see if I could use attribute caching to make it even faster. My idea had been to make an auxiliary attribute "has_been_indexed", or something, and to progressively update the map of "lemmas arranged by head symbols" I need every time someone runs library_search
. But for this is help, we'd need to be able to reuse previous map, and just add to it the all the lemmas which have been added to the environment since the last call to library_search
. That isn't possible, it seems. Given that I'd expect there to be a new declaration roughly every time library_search
is called, the cache wouldn't be hit often: only ever for multiple invocations of library_search
within the same proof block.
In any case, this isn't a roadblock. It looks like library_search
may be fast enough to be usable.
Hi @Scott Morrison, essentially just because get_options
and set_options
are tactic_state
local, I have a way to have the lemma cache be generated only the first time library_search
is used in particular a tactic block.
Here's a working demo: https://github.com/khoek/lean-local-cache
Does that require modifying core?
No, all above board
Ok, cool!
And in a second begin end block of the same file, it is regenerated again, right?
Yes
https://github.com/leanprover-community/mathlib/pull/837
I'm rocking some tests
Last updated: Apr 24 2020 at 19:02 UTC


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| CS 216 - Data Structures
Homework #7 |
NOTE: This work is to be done in groups of 2-3.
Define a class HeapSorter<E extends Comparable<E>> with a default constructor and a method public void sort(E[] a) that sorts a in place without making use of an additional array. You are encouraged to adapt the text pseudocode. (Warning: Pseudocode arrays use 1-based rather than 0-based indexing, so take extra care with off-by-one errors.) Here is some sample test code illustrating one possible use:
Scanner in = new Scanner(System.in); System.out.print("How many integers? "); int size = in.nextInt(); System.out.print("How many possible random values? "); int values = in.nextInt(); Integer[] array = new Integer[size]; Random random = new Random(); for (int i = 0; i < size; i++) array[i] = random.nextInt(values); new HeapSorter().sort(array); for (int i = 0; i < size - 1; i++) if (array[i] > array[i + 1]) { System.out.println("Array not sorted"); System.exit(1); } System.out.println("Array sorted");


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Figure 8: A Typical Thematic Map
In all fields, GIS research should focus on exploiting the ability to synthesize disparate data themes. The single variable thematic map is one of the most common GIS outputs, but decision makers rarely want to know how one variable varies across space. They want to know about the interaction of many different variables. This type of analysis lies at the heart of GIS, but the way software is currently configured, the user must be familiar with a plethora of software-specific commands to perform an analysis, which means that the help of a GIS specialist is usually required.
An environmental sensitivity analysis is one example of this kind of study. Data on vegetation, soil type, elevation, slope and aspect are synthesized to come up with some measure of environmental sensitivity for every point in the study area. Generally, scientists define the study parameters and then the GIS work is performed by a technician who applies those parameters to a data set and then generates a map.
The need for better GIS interfaces is currently being addressed by individual users who develop "modules" using the GIS package's scripting language (the fact that all major GIS packages have a scripting language is an acknowledgment of their weak user interface). Modules have been developed for forest management, political redistricting, bus routing, etc. This section can be thought of as an effort to build an urban design module.
There are five components to the construction of this system. First, it must be decided what are the important things to know about a city in order to understand it (Kevin Lynch proposed that a city's edges, nodes, paths, districts and landmarks must be known). Second, we must create computable algorithms for the identification of these "important things"--Rowe's descriptive model. Third, the user interface must strike a balance between simplicity and flexibility. Right now, GIS user interfaces err on the flexible side, allowing a multitude of operations if the user can figure out how to perform them. A GIS for urban design should be easily employed by an urban designer, so beyond the creation of functions with specific application to the urban design field, an interface should be created which maximizes the ability of the designer to explore the study area.
Fourth, an urban design module must be flexible in terms of the definition of algorithms. Urban design is different from most disciplines that use GIS in that there are few generally accepted procedures that are implemented the same way in every situation. Defining the "important things" that must be known about a place is an issue that many people have an opinion about, but no official body, like the American Planning Association, has set down any rules or even guidelines on this question. For example, we may think that an algorithm to find the shortest path from one place to another is an important tool, but a designer may think that the time or distance between two places is relatively unimportant to the design of an urban area when compared to issues such as safety, a feeling of home, etc. "Although attempts have been made to reduce design to completely explicit systems of search or synthesis, it remains an art, a peculiar mix of rationality and irrationality. Design deals with qualities, with complex connections, and also with ambiguities" (Lynch, 1981). So an urban design module must allow the user to create their own analysis tools, but in an easier way than simply providing a scripting language that is closer to programming than using an existing program. This last aspect will not be developed in the context of this work because of the extensive programming required. Instead, this work develops the system the way Lynch might have, and leaves the creation of a flexible interface to further research.
Fifth and finally, an urban design or planning GIS must incorporate some method of receiving input from the general public and organizing and synthesizing this information graphically. The importance of including the public in the planning process has been well documented,[9] but decision makers often exclude the public from the process by arguing that it is too expensive and time-consuming to hold numerous public meetings and try to come to some sort of group consensus. Information networking technology offers a forum for the public which could overcome these arguments. A general framework for this part of the system would include the provision of information to the public, a way for people to make comments with text and pictures (possibly also video and audio), a way for people to browse the comments of others and a way of synthesizing the input to get an idea of the collective view on the issue.
The scope of this work is to lay out all of the issues concerned with GIS and urban design, but to only go into depth on a small number of them. This section presents a prototype of the descriptive component of an urban design GIS. More specifically, it looks at how patterns in the landscape could be explored, it takes a detailed look at how to model Kevin Lynch-type nodes and discusses in broader terms how the other elements of Lynch's legible city might be modeled.
A short description of the key data layers is presented here while detailed source information can be found in Appendix B: Data Dictionary. The data layer used to represent street areas here actually consists of the area comprised of streets and sidewalks. No more detailed data set covering the entire city could be found for these features. The building footprints data layer represents the outlines of buildings as they would appear from an aerial view. No height information was included and in many cases, multiple buildings are represented as a single sha`e because of their proximity to one another. Parcels were obtained from the City of Boston, who created this data set for tax assessment purposes. Parcel-based data included land use, building value and land value. Aerial photography came from MassGIS, the Massachusetts agency responsible for compiling and disseminating state digital data. The photographs have a half-meter resolution and are geographically referenced and orthorectified, meaning that the picture has been adjusted to compensate for elevation and the angle of the photograph. This is done so that the viewer seems to be looking straight down on the scene and to maintain accurate sizes and shapes. Census data was simply downloaded from the Internet using the U.S. Census Bureau's service. All 1990 Census data is available in this way.
These five databases--streets, parcels, building footprints, aerial photographs and Census data--will be used in conjunction with local knowledge to generate an "understanding" of the urban environment. This understanding will be different depending on the needs and personal characteristics of each individual planner. In this work I use Kevin Lynch's model of understanding the urban environment as described in ]Image of the City. Although I use this model as an example, the real strength of this application will be its ability to be customized to process any designer's model of the city.
Landscape abstraction should transcend traditional human understanding of the physical world, and most importantly extend the limit of our perception of reality.Perron and Miller, 1991
I consider pattern finding to be a key aspect of any sketch planning GIS. Every designer will want a slightly different set of tools, but the ability to recognize and explore spatial patterns will be included in some way. This function, in its simplest form, takes thematic data sets and allows the user to combine them in various ways. For example, the user can quickly calculate and view all places that are predominantly residential, urban, run down, with a high rate of unemployment and comprised largely of non-native English speakers. This is accomplished by combining demographic, land use and city assessor's data. The utility of finding patterns is not the main focus here, but rather the ability to quickly process pattern finding requests that bring together multiple data sources. Kp>
So then the goal here is to create a tool which offers the designer more depth. The obvious way to accomplish this is to add multimedia elements to the GIS such as pictures, video, etc., but the amount of time and effort required to put develop that type of audio/visual database is too great. Instead, I try to create a greater depth of knowledge by allowing the user to quickly find areas that meet any number of conditions from any number of data layers.
This is a task to which GIS is well suited because of its ability to overlay spatially referenced data sets and contrast and compare their attributes. The way this is often done in GIS analyses is to choose a number of data sets, perform the overlay, and then classify the resulting data set's values into a thematic map. I did not want to use this method because it seems to presuppose a knowledge of which data sets to overlay and what value will be important in the end. Instead, I start with a place of interest. The user can find out everything about the place (limited only by what data sets are available). Then the user can find other similar places throughout the city. All of the intricate overlay commands are transparent to the user, so that they can concentrate on the exploration process.
In order to combine these ideas into a prototype pattern finding application, it was necessary to predict certain modes of operation for the hypothetical user--two are presented here. The first assumes that the planner has in-depth knowledge about one place--usually an street corner or a parcel, and wants to find out the underlying characteristics about this place as well as other places that have similar characteristics. The second is not based upon any one place. The user is allowed to enter any characteristics of interest and see how they compare.
The place-based method is modeled by having the user select a building in the area of interest. The program then allows the user to select any of the themes present in the database that is of interest to the analyst. In Figure 9a the user has selected population density. The next step is to decide what range of population density is important. The value at the location of the building (109.98) is given as a starting point, but the user decides that 100 is a better minimum value. The maximum value is chosen in the same manner, and then additional themes may also be added to the pattern. After all of the parameters are entered, the program finds all areas in Boston that meet all of the criteria.
In this way, information about one place can be used to help the user find other places that are likely to be similar without having to study every acre of the city in detail. This proves to be a very stimulating method of analysis, especially when places with similar characteristics turn out to look quite different "on the ground."
The non place-based method is similar to the place-based method, but the conceptual goal is quite different in that the user's interest is not focused on one specific place, but on a specific set of characteristics. The GIS aids the user in choosing a range of values for each characteristic by reporting certain statistics such as mean, maximum, minimum, standard deviation and quantiles.
These explorations become iterative when the designer takes the results of an analysis (which the program allows to become another data layer) and refines or expands that exploration path by further restricting the limits of a query or adding another query element or intersecting two separate analysis paths. As all the query results can be saved as spatial layers, they are all available for use as inputs into subsequent analyses. For example, the result of an analysis that finds areas that are sensitive to real-estate speculation might be important in studies of economic development zones, road and utilities upgrades, rent control, etc.
Blind pattern finding can be a powerful exploratory tool, but the designer often wants to start with a certain geographic boundary and understand what makes the area within the boundary different from the area without. This is not really pattern finding but pattern understanding, because what you want to know is why the pattern that has been observed exists. The amount of programming necessary to prototype this concept is beyond the scope of this work, but it is important to keep in mind because it represents the beginnings of a predictive, or planning model which would go beyond simply describing a place.
Figure 9: Place-based pattern finding
(a) the user interface
(b) Places similar to a building in the Mission Main public
housing development
Figure 10: Blind Patterns
Horizontal hatching: Areas vulnerable to commercial real-estate
speculation
Cross-hatching (look in lower right corner): The same areas with over 50% Black
population
Kevin Lynch, in The Image of the City, looks at the city as a place where many aspects of physical form and land use are controlled by individuals and not by centralized government, resulting in an environment which is constantly changing over time. Within this framework, however, there is a function for the city planner, and that function is to create an environment where residents can take emotional ownership over a large part of the city. Outside of this area that they think of as "theirs," there should be no consternation associated with navigating around the rest of the urban landscape. This vision of the city contains familiar, private home neighborhoods, lively commercial and civic centers, and navigable and easily identified paths between all of these districts. These building blocks of the urban environment are called nodes, paths, districts, edges and landmarks.
Lynch argues that understanding the city in this way will help planners be able to plan cities that work better for their inhabitants, but in his 1985 reflection on the book's impact, he is disappointed with the way his work was used. With his work in hand, planners felt that they could find these patterns on their own, with no resident input, when Lynch's theory was that the location of these nodes and boundaries of these districts must be ultimately defined by the public. This is why a system of sharing experience (discussed at the end of this section) is critical to the success of this model. While the physical environment will offer clues to the image of the city, the computer can not know how safe people feel on their street, or how many neighbors and shopkeepers they can identify by face. This information must come from individuals having input into the system, and this issue will continue to be discussed throughout the paper.
Nodes are points, the strategic spots in a city into which an observer can enter, and which are the intensive foci to an from which he is traveling. They may be primarily junctions, places of a break in transportation, a crossing or convergence of paths, moments of shift from one structure to another. Or the nodes may be simply concentrations, which gain their importance from being the condensation of some use or physical character, as a street-corner hangout or an enclosed square. Some of these concentration nodes are the focus and epitome of a district, over which their influence radiates and of which they stand as a symbol.The Image of the City, pp. 47-48
So nodes are either notable intersections of paths or concentrations of activity. In fact, these two definitions are self-reinforcing, as centers of activity often develop at important intersections, and paths are often created to service major nodes.
In Boston's South End, the Boston Center for the Arts (BCA) intersection (Figure 21B) is a neighborhood node. The BCA is a multi-purpose facility where art classes and exhibitions are held and artists lofts and studios are located. The block containing the BCA is on the north side of Tremont Street, with a small theater next door and a music school and a parking lot behind. Across from the BCA and along Tremont heading southwest are a number of small businesses including coffee shops, restaurants and antique stores. The Tremont/Berkeley Street intersection is a heavily traveled automotive path, with commuters on their way to and from the Massachusetts Turnpike and Interstate 93. Pedestrians from the surrounding residential areas use Tremont Street as a destination (for its cultural and commercial offerings) and as a path to downtown Boston, located north and east of the node. Many children are also seen in the area, as a number of schools are within a three block radius.
It is easy to picture a typical day in this node, with people hurrying to work and school in the morning, adults grabbing coffee and breakfast along the way and everyone avoiding the cars speeding along the streets towards the downtown office buildings. Mid-day is quieter. Those who are fortunate enough not to have to work visit the art exhibitions and stop in for a long lunch at a local café and maybe browse the antique stores, hoping for a great find. The afternoon brings a flurry of street activity as school lets out, and before you know it dinner is being served at the restaurants. The area may remain lively well into the evening if there is an art opening or a play that night.
This knowledge is a result of many visits to the area over the course of a three-month investigation of the neighborhood. The task here, however, is to identify this node solely through the use of our database (local resident input will be added to the system later). Earlier, nodes were defined as intersecting paths and/or centers of activity.  Each may be a node in a micro reading of a site, but here we are concerned with neighborhood/city scale. Therefore, the following conditions will lead to a more accurate attribution of the term node for urban planning.
A place may be a node if it is situated along a major street. Major may be defined in an urban setting as a street of at least four car widths. This translates at the minimum into one lane of traffic in each direction, with parking on both sides. Sidewalk width is also important, as it influences people's ability to interact with each other in this public setting (sidewalk data is unfortunately often neglected in the construction of an urban database). [14] Wetlands are so important because they are the transition area between forests, fields and water. Being rich in food sources they also attract animals from the land, air and water. The same theory can be applied to the human species. Because of the varied needs of people, the greatest level of activity will be found in areas that service the greatest number of needs. The BCA is coded as commercial land use with institutional uses found to the west and east. Residential areas surround these public uses, which is crucial because public areas without nearby residential districts become ghost towns at night and on weekends.
One important characteristic of the area which is not reflected in the data is that the buildings on Tremont Street generally have commercial uses on the ground floor and apartments above (Figure 21A). The 1:25,000 land use database, however, codes these buildings simply as residential. A mixed use classification or a data structure which supported more than one classification for a given location would be more appropriate here, as is supported by the parcel-based land use data set. Agencies have resisted mixed use classifications because if you have 20 classes and you allow for each to be crossed with every other, there are 400 possible combinations. With 400 classes, the land use map is no longer significantly less complex than the real world, so once again you may need a GIS specialist in order to make sense of it. Agencies that create the database should be able to build in multiple levels of detail into a database either with a different data model than currently exists15 or with a different interface to the data than currently exists. The end user then has the freedom to choose the level of detail they need to complete the task at hand. The parcel-based land use data set offers a rich classification scheme (see Appendix B: Data Dictionary), but any aggregation must be performed by the user.
So this node can be generally defined as follows:
Starting from the assumption that the area around urban nodes must include commercial, residential and institutional uses, I use an algorithm (Figure 11) that searches the land use data set (Figure 12) in a 500-foot radius around every cell for different land uses. If the aforementioned three land uses are not present, then the point can not be a node. If they are present, the point is ranked in comparison to other nodes based upon how many different types of land use are present in the area. Next, since I am in the experimental stage (i.e. not yet at the point where I have decided upon only one way to find nodes), I perform the same analysis again using a 260 foot search radius (Figure 16), and then once again using a 1,000 foot search radius. I see that the 1,000 foot radius is to be to large because it searching an almost half-mile diameter area, which is too large to be considered a single place in this urban context, but the other two searches seem to hold promise.
During the course of this research (as often happens in real life) a more detailed source of land use data became available, so I am able to run the same 500-foot and 260-foot search radius analyses using parcel-based land use with an intermediate classification (Figures 17 and 18) and with a highly detailed classification scheme (Figures 19 and 20). The difference between the intermediate and detailed classification schemes is not only the number of categories, but also the purpose for which the categories were created. The intermediate scheme was one that came with the database (Figure 13)--it could have been geared towards tax assessment, utility maintenance, or something else. The detailed scheme was developed specifically for this study (Figure 14). This can be seen in the category labels to the left of the maps.
Figure 11: The Node finding algorithm
The process I used to evaluate the success rate of finding nodes at this initial stage was to simply see if the found nodes coincided with Lynch's study (Figure 4) and my knowledge of downtown Boston.[16] The area of the city most Bostonians are familiar with consists of the Fenway/Kenmore, Back Bay/Beacon Hill, South End, and Central neighborhoods (Figure 23: City-defined Districts). There were three nodes here that I used as benchmarks, Kenmore Square, The BCA corner and Newbury Street.
Kenmore Square is a major city-wide node (Figure 21C). The roads coming together here are eight lanes wide in some sections. The effect of this is mitigated by a strip of useable area separating the two directions of traffic. Most of this strip is used as a park, but near the actual intersection there is a bus and subway station in this zone. The many diverse businesses include restaurants, music stores, a funeral parlor, the Boston University Bookstore, nightclubs, convenience stores, clothing stores and coffee shops. These are supported by Boston University, apartments and hotels, the baseball park, and a nearby street that serves as "nightclub row."
The BCA corner is a more subtle, neighborhood node. Only people who live or work in the South End are likely to frequent this area. Exceptions are those who are coming to the BCA for an event or in their car cutting through the South End on their way to the highway. The nature of the stores reflect this. They are mostly convenience stores, small restaurants and dry cleaners. Newbury Street is another major node, but it is different in that it is linear. The street is lined with shops that appeal to tourists and the wealthy, as well as eating places for locals.
The areas found with the 1:25,000-scale land use and a 500-foot search radius included the three test nodes mentioned above, but many other areas were also found. These did appear to be more active than the areas that were not found, but there was not enough of a distinction between places for the operation to be useful. Also, although the test areas were found, they were ranked lower than areas that are actually less active. Searching a 260-foot radius reduced the amount of area selected, but did not help in better identifying actual nodes. Similar problems resulted from the analysis using parcel-based land use and the intermediate classification scheme. Too much of the city was identified as "node-like" and the ranking of areas did not correspond well to the actual distribution of activity. This is a result of the classification scheme having little relation to urban design issues (Figure 13). The only category that was not residential, commercial or institutional is industrial, and what this categorization scheme emphasizes is the differing densities of residential areas. Although it may seem obvious that this description of land use would not be useful, I wanted to run the analysis with it to show how important the base data and categorization is to obtaining useful information.
The detailed classification scheme includes a number of important disaggregated land use categories. Institutional use is separated into schools, hospitals, library/museum/galleries, religious and other. Industrial use is separated into light industry, manufacturing and utilities. Commercial use is separated into retail, hotels, restaurants/bars and offices. These important differences in land use allow the node finding function to create highly descriptive and useful nodes (Figures 19 and 20), although this data set did not identify the BCA node. The major difference between the 500-foot and 260-foot detailed land use nodes is the size of the area identified. It seems that concentration of activity is better represented by the 260-foot search radius, but the data is not accurate enough (or the node finding function is not fine-tuned enough) for this search to work as well as the 500-foot radius search. In other words, the 260-foot radius is closer to the actual size of a node, but we must find larger, more general areas because even the parcel-based land use data set has drawbacks. For example, the BCA node was not found in large part because the land use data does not classify the buildings along Tremont Street. For some reason these areas were left out of the data set.
Once the algorithm was fine-tuned and studied in the lab as described above, I was ready to investigate the nodes that had been found in other parts of the city. This two-step process of building theory and associated algorithms in the office and then field-checking the theory reflects the general idea that the GIS should allow the designer to apply their knowledge about a small area to the entire city. I used my knowledge of downtown Boston to formulate an algorithm that would identify areas I consider nodes and then the algorithm applied that concept to the rest of the study area. In fact, the algorithm was extremely successful in performing this task, although this success is difficult to prove because design methods are inherently difficult to quantify. A photographic presentation (Figure 21) of the nodes is the best way to describe them without labor-intensive pedestrian and traffic counts or video. All photographs were taken between 9:00AM and 5:00PM on weekdays.
The difficulty in creating the node finding algorithm had more to do with data and computing resources than with conceptual issues. Without the parcel-based land use data set, this study would not have been successful. This is significant because very few cities have developed digital data sets at this level of detail, but detail is crucial to studies of the urban environment. Computing power is also an issue. This analysis would not have been possible with the kind of computing power currently available in personal computers. UNIX workstations were used, and even then it was only feasible to analyze a portion of the city, which itself is only a portion of the metropolitan area. Progress in the detail of data sets and computational power will make experimentation in this area much more practical in the future.
Figure 12: The BCA node as described by the 1:25,000 land use data
set
click for full-scale image
Figure 13: The BCA node as described by the parcel-based land use data
set
with an intermediate classification scheme
click for full-scale image
Figure 14: The BCA node `s described by the parcel-based land use data
set
with a detailed classification scheme
click for full-scale image
Figure 15: Nodes derived from 1:25,000 scale land use
and a 500-foot search
radius
click for full-scale image
Figure 16: Nodes derived from 1:25,000 scale land use
and a
260-foot search radius
click for full-scale image
Figure 17: Nodes derived from parcel-based land use
with an
intermediate classification scheme and a 500-foot search radius
click for full-scale image
Figure 18: Nodes derived from parcel-based land use
with an
intermediate classification scheme and a 260-foot search radius
click for full-scale image
Figure 19: Nodes derived from parcel-based land use
with a detailed
classification scheme and a 500-foot search radius
click for full-scale image
Figure 20: Nodes derived from parcel-based land use
with a detailed
classification scheme and a 260-foot search radius
click for full-scale image
Figure 21: Photographs of nodes around the city
(A) Dudley & Warren
(B) The BCA (Tremont &Union)
(C) Kenmore Square (Commonwealth Avenue)
(D) Downtown Crossing
(E) Centre and Buckford
r>
(F) Uphams Corner
Figure 22: Key to the Nodes Photographs
Districts are medium-to-large sections of the city, conceived of as having two-dimensional extent, which the observer mentally enters "inside of," and which are recognizable as having some common, identifying character. Always identifiable from the inside, they are also used for exterior reference if visible from the outside. Most people structure their city to some extent in this way, with individual differences as to whether paths or districts are the dominant elements. It seems to depend not only upon the individual, but also upon the given city.The Image of the City, p. 47
The easiest way to explain the concept of district is by example. In Boston, the South End, the North End, Back Bay and the Financial District are obvious districts. New York has Greenwich Village, Soho, Wall Street, Harlem and countless others. Although specific boundaries may be hard to agree upon, the general existence and location of most districts are easy for residents to acknowledge.
A useful distinction can be made here between a neighborhood district and a physical district. Defining neighborhood districts using digital data is difficult because the boundaries may be based on historical events, informal gang (south-central Los Angeles) or politician-controlled areas, elevation (Beacon Hill, Boston), etc. Some of these factors have some physical form and can therefore be captured in a GIS, but some will not. Furthermore, physical form may lead the designer into misclassifying a neighborhood. For example, Boston's South End crosses over Massachusetts Avenue, a street so wide that planner unfamiliar with the area would assume that no neighborhood could cross that barrier.
The issue of defining districts for Boston was aided by the fact that one of the data sets available specifically addresses this issue by outlining and naming the eighteen neighborhoods of the city (Figure 23: City-defined districts). An interesting use of the inverse pattern finding application described at the end of this paper would be to take one of these neighborhoods and ask what is different about it as compared to the rest of the city, or adjacent neighborhoods. In this way the accuracy and usefulness of the neighborhood data set could be evaluated. Districts are an important macro-level concept of neighborhood, but micro-districts are also crucial to a sense of comfort in the city. These districts would be a number of blocks, rather than a section of the city. This is the area in which many of the faces should be familiar. Christopher Alexander describes this as Pattern 14: Identifiable Neighborhood, which says, "People need an identifiable spatial unit to belong to." 17 The district as Lynch defines it would be a closer match to Pattern 12: Community of 7000, which states, "Individuals have no effective voice in any community of more than 5000=10,000 persons."[18]
Alexander's definition of community is reflected in the dividing up of Boston into wards, the smallest political unit in the city. Neighborhood boundaries can be explored using traditional thematic mapping techniques. The three districts generated in Figure 23 are shaded by taking the minimum and maximum values for the attribute in question (median family income, percent Asian and percent Black) and dividing that range into four equal ranges. The Back Bay/Beacon Hill area is home to the only city residents whose average income is more than the city's average of $35,532 (Figure 23: A high income district). Boston's Chinatown district appears clearly by classifying the city by percentage Asian population. Only the small Chinatown area has a greater than 50% Asian population in each block group (Figure 23: An Asian district). Similarly, Blacks seem to be concentrated in Roxbury and Mattapan.
Figure 23: Identifying Districts
City-defined districts
A high income district
click for full-scale image
An Asian district (Chinatown)
click for full-scale image
A Black district
click for full-scale image
Paths are the channels along which the observer customarily, occasionally, or potentially moves. They may be streets, walkways, transit lines, canals, railroads. For many people, these are the predominant elements in their image. People observe the city while moving through it, and along these paths the other environmental elements are arranged and related.The Image of the City, p. 47
Roads and transit lines are easily included in a GIS, the difficulty comes in classifying them according to use. Road width is one way to obtain a rough idea of how heavily used a street is for vehicular traffic, but this is only one type of path. Jacobs suggests that the number of intersections one street has with others is a good indicator of how busy and interesting a street will be because more intersections implies a greater potential to be part of the route to more destinations.[19] For example, one would only find people who are going somewhere on that street on a long street with no intersections.
Since paths are channels along which people customarily move and nodes are places at which people customarily meet, it is logical that people will customarily move from node to node. This suggests a different method of defining paths. Instead of going back to the original data sources to model the path concept, it can be constructed from the nodes model. This theory works particularly well for Newbury Street (along the northeastern portion of Figure 20). This street is used by many go from the western part of downtown Boston to the financial district in the northeast. It is more frequently used than the completely residential streets to its north because it offers the opportunity to see more people, have a snack or window shop.
Apart from being a connection of nodes, the classification of paths proved to be the most difficult concept of Lynch's to model. Transportation data is rarely very detailed, due to the time and expense associated with pedestrian and traffic counts and classifying a street as a single unit when its name may change along its route. Because of this lack of helpful data sources, this is one area in which I do not foresee GIS being immediately helpful to urban design.
Edges are the linear elements not used or considered as paths by the observer. They are the boundaries between two phases, linear breaks in continuity: shores, railroads cuts, edges of development, walls.The Image of the City, p. 47
The identification of hard edges may clearly be aided by GIS. Many times a district will be constructed using one type of data (demographics) and the edge will be formed by another (streets, rail lines, water features). The overlay and intersection capabilities of GIS allow this type of analysis to be performed in a straightforward manner. That addresses the question of hard edges, but Lynch also identifies soft edges, which he calls seams. Soft edges separate distinct regions but have no easily observable edge element.
Soft edges can be roughly identified with GIS because edges must be defined in the creation of any vector-based data set. For instance, the Census data used was based on block groups. These are usually two to four city block areas that U.S. Census Bureau researchers have decided are similar enough to aggregate into a block group. The 1:25,000 land use data set also required a trained professional to decide where one area ended and the next began. This was not a problem with the parcel-based data because lot lines served as the edges.
Landmarks are another type of point-reference [like nodes], but in this case the observer does not enter within them, they are external. They are usually a rather simply defined physical object: building, sign, store, or mountain...They may be within the city or at such a distance that for all practical purposes they symbolize a constant direction... They are frequently used clues of identity and even of structure, and seem to be increasingly relied upon as a journey becomes more and more familiar.The Image of the City, p. 48
Finding landmarks would be one of the most difficult tasks for a traditional GIS. As directional guides, they are often taller than other landscape features, which makes them difficult to distinguish with data sets that rarely include object heights. Many objects become landmarks because they stand out from their surroundings in other ways, like appearance, and this characteristic is also rarely captured in a database.
The best way to identify landmarks is through resident input. In fact, one of Lynch's main points is that all of the preceding elements of the city should be identified using the experience of the people that define them through their daily activities.
Lynch put forth the effort to interview individuals, but each interview took at least two hours, so his technique could not be considered an implementable model in the context of a city government working within a limited budget. Advances in networking technologies and electronic communication should make the collection and analysis of public opinion on local issues more common, but research on integrating GIS and public input is still in its infancy.
Lynch asks four questions of his interviewees. Draw a sketch map of the area showing interesting and important features, sketch the route and events along an imaginary trip, list parts of the city felt to be most distinctive, and describe where a few objects are located. Instead of sitting down with a person and asking these questions, they can now be asked and answered with a computer. As we may soon reach the point in America where a large and diverse portion of the citizenry could be reached through electronic networks, Lynch's technique should be revisited with these new tools in mind.


Guest lineups for the Sunday news shows
WASHINGTON (AP) - Guest lineups for the Sunday TV news shows:
ABC’s “This Week” - Reps. Eliot Engel, D-N.Y., and Steve Scalise, R-La.; Democratic presidential candidate Pete Buttigieg.
NBC’s “Meet the Press” - Reps. Terri Sewell, D-Ala., and Tom Cole, R-Okla.; Democratic presidential candidate Andrew Yang.
CBS’ “Face the Nation” - Reps. Steny Hoyer, D-Md., Kevin McCarthy, R-Calif., and Jackie Speier, D-Calif.
CNN’s “State of the Union” - White House counselor Kellyanne Conway; Rep. James Clyburn, D-S.C.
“Fox News Sunday” - Conway; Rep. Jim Himes, D-Conn.
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| 12 Feb 1885 |
Julius Streicher born, Fleinhausen Germany. |
| 1913 |
Marries Kunigunde Roth. |
| 1914 |
Joins the German Army. |
| 1915 |
Son, Lothair, born. |
| 1918 |
Son, Elmar, born. |
| 14 Apr 1923 |
Launches Der Stürmer newspaper, with Anti-Semitic viewpoint. |
| 6 Apr 1924 |
Elected to German parliament. |
| 1940 |
Removed of all governmental responsibility. |
| May 1943 |
An issue of Der Stürmer spotlights Jewish crucifixion of a Christian child during Passover. This issue is used as evidence at Nuremberg. |
| 1943 |
Wife dies. |
| 23 May 1945 |
Julius Streicher taken into American custody by Maj. Plitt. |
| 30 Sep 1946 |
Julius Streicher sentenced to hang. |
| 16 Oct 1946 |
Hanged as sentence for Nuremberg trial. Final words: Heil Hitler. He takes 14 minutes to die. |


MAGIC IN THE WATER A film review by James Berardinelli Copyright 1995 James Berardinelli
RATING (0 TO 10): 5.9
United States, 1995 U.S. Availability: 8/30/95 (wide) Running Length: 1:38 MPAA Classification: PG (Profanity, children in jeopardy) Theatrical Aspect Ratio: 1.85:1
Cast: Sarah Wayne, Mark Harmon, Joshua Jackson, Harley Jane Kozak, Frank Sotonoma Salsedo Director: Rick Stevenson Producers: Matthew O'Connor and Rick Stevenson Screenplay: Rick Stevenson and Icel Dobell Massey Cinematography: Thomas Burstyn Music: David Schwartz U.S. Distributor: TriStar Pictures
On its way to being the Loch Ness Monster's answer to ET, MAGIC IN THE WATER has trouble staying afloat. Director/co-writer Mark Stevenson's heart is in the right place, but his screenplay stumbles trying to find the right mix of magic and realism. The result loses too much of its enchantment amidst failed attempts at a FISHER KING subplot and an underwater "adventure" sequence. Nevertheless, one area where MAGIC IN THE WATER is an undisputed success is in the casting of its young lead actress. Newcomer Sarah Wayne is nothing short of radiant.
The '90s have featured a number of impressive child actress' debuts. Anna Paquin garnered an Oscar for her turn in THE PIANO. Tina Majorino, late of WATERWORLD, has won raves for several films. And Kirsten Dunst opened eyes with her roles in INTERVIEW WITH THE VAMPIRE and LITTLE WOMEN. More luminous than any of these, however, is Sarah Wayne, who singlehandedly rescues MAGIC IN THE WATER from turning into something unbearably cheesy. Wayne's portrayal arrests the viewer's attention even when the scene is silly. She has a winning smile, a fresh demeanor devoid of artifice, and is able to successfully convey a wide range of emotions.
Wayne plays Ashley Black, the pre-teen daughter of talk radio shrink Jack Black (Mark Harmon). Ashley's parents are divorced, and she and her teenage brother, Joshua (Joshua Jackson), live with Mom. This summer, however, their workaholic dad has agreed to take them on an extended vacation to Glenorky, British Columbia, home of the mythical, Loch Ness-like "Orky." The problem is, Jack brings along his cellular phones and portable PC, and once he gets to Glenorky, he shuts out his kids and starts working. When Ashley finally gets her father's attention by claiming to have seen the fabled lake monster, Jack is understandably skeptical... until he has a visitation of his own -- one that changes the way he sees life and relates to his children.
The ET element of the story works fine, and even offers a nicely- framed, politically correct message about the evils of environmental pollution. Had MAGIC IN THE WATER concentrated its efforts on this plot element, it might have been more satisfying, but the film spends an inordinate amount of time chronicling Jack's transformation from self- centered work addict to carefree, loving father. Not only is this part scripted with a distinct lack of flair, but Mark Harmon's performance comes across as more childish than child-like. Add to that a completely unnecessary climax featuring an underwater rescue, and MAGIC IN THE WATER ends up with too many bad subplots clinging to its central premise.
Needless to say, given the PG rating, this is family fare, although the screenplay has a little more of an edge than some of the summer's tame entries. It's certainly not a good film, and I can't give it even a lukewarm recommendation, but there are isolated moments when the film works as well for adults as for kids. Above all, however, there's Sarah Wayne, MAGIC IN THE WATER's most noteworthy asset. She may not be enough to lure many people into the theater, but once they're there, her performance will be enough to keep most of them in their seats.
- James Berardinelli<EMAIL_ADDRESS>The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
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{% include info-block.html title="What are Counter Questions?"
description="Its a collaborative collection of interview questions collected from both sides of the game: Interviewer(s) and Interviewee."%}
{% include info-block.html title="Why use them?"
description="Ideally, interview process is a conversation between equal parties. Not among superiors and inferior – it's hard to find good companies because it's even harder for them to find good employees.
You, as Interviewee, should have a way to distinguish good from bad - this list of questions will help you facilitate
that process" %}
{% include block-grid-featured.html%}
{% include footer.html %}


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_Reach_the_Rock_ (R) * 1/2 (out of ****)
"An intimate, character-driven drama about a troubled youth at a crossroads in his life," read the press notes for _Reach_the_Rock_. I'm not really sure what film that statement is describing because those words bear little resemblance to the slow, completely uninvolving bore I saw--at least, it certainly does not describe what goes on for most of the film. Alessandro Nivola plays Robin Fleming, a troubled, directionless 21-year-old who has a penchant for breaking storefront windows in a small town. Police sergeant Phil Quinn (William Sadler) takes him in, and what ensues for the first 70 minutes is a tedious series of sneak-outs and sneak-ins where Robin slips out of his jail cell, breaks a window, then returns, all without Quinn ever noticing.
With a half hour (if even that long) remaining, director William Ryan and writer John Hughes (yes, John Hughes of '80s youth films and _Home_Alone_) finally approach something close to a point. Turns out Robin still pines for his high school sweetheart Lise (Brooke Langton), who has long gone on with her life, and Hughes's main concern at long last reveals itself as a tired "live in the present and for the future" message. Most moviegoers, however, will likely be asleep by that time. Wide awake, however, is the cast, who individually tackle their showcase dramatic scenes with energy and skill--thus revealing the _real_ purpose behind this listless enterprise: to serve as a series of acting exercises. Such a glorified workshop may have its rewards for the actors, but it leaves audiences with a booby prize. (opens October 16)
Michael Dequina
<EMAIL_ADDRESS>|<EMAIL_ADDRESS>Mr. Brown's Movie Site: http://welcome.to/mrbrown
CompuServe Hollywood Hotline: http://www.HollywoodHotline.com
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
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belongs to the author.
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| lvq3 {class} | R Documentation |
Moves examples in a codebook to better represent the training set.
lvq3(x, cl, codebk, niter = 100*nrow(codebk$x), alpha = 0.03, win = 0.3, epsilon = 0.1)
x |
a matrix or data frame of examples |
cl |
a vector or factor of classifications for the examples |
codebk |
a codebook |
niter |
number of iterations |
alpha |
constant for training |
win |
a tolerance for the closeness of the two nearest vectors. |
epsilon |
proportion of move for correct vectors |
Selects niter
examples at random with replacement, and adjusts the nearest
two examples in the codebook for each.
A codebook, represented as a list with components x
and cl
giving the examples and classes.
Kohonen, T. (1990) The self-organizing map. Proc. IEEE 78, 1464–1480.
Kohonen, T. (1995) Self-Organizing Maps. Springer, Berlin.
Ripley, B. D. (1996) Pattern Recognition and Neural Networks. Cambridge.
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.
lvqinit
, lvq1
, olvq1
,
lvq2
, lvqtest
train <- rbind(iris3[1:25,,1], iris3[1:25,,2], iris3[1:25,,3]) test <- rbind(iris3[26:50,,1], iris3[26:50,,2], iris3[26:50,,3]) cl <- factor(c(rep("s",25), rep("c",25), rep("v",25))) cd <- lvqinit(train, cl, 10) lvqtest(cd, train) cd0 <- olvq1(train, cl, cd) lvqtest(cd0, train) cd3 <- lvq3(train, cl, cd0) lvqtest(cd3, train)


Plug n' Code uses JSTree to provide you with a fully functional and responsive file browsing and management experience.
The file manager is availabe in the left most pane on the index page.
It supports all the basic file management functions such as copy, cut, paste, new, delete, etc.
In addition to this, drag n' drop functions are also enabled for cut and copy operations.


June 2020 Batch
The conversation we've had have been very enriching. This has been a very engaged and fun batch. I wish you all the very best in your future projects and careers.
Take what you have learned and teach somebody else. You learn more by teaching. AI is transforming the way we live, jump in and do something good.
Your opinion is very important


The micro:bit has two buttons on the side which has the LED display and these are called Button A and Button B. The Bluetooth profile lets you tell the micro:bit that your application should be informed whenever one or both of those buttons are pressed.
In fact it's even better than that.
Each button can be in one of three 'states'. These states are NOT PRESSED, PRESSED or LONG PRESS. What the first two mean is pretty obvious. A button is said to be in the LONG PRESS state when it's been pressed and held down for at least 2 seconds.
This demo shows a very simple example of how you can have the micro:bit communicate button interactions with a connected application like this one.
The Bluetooth profile includes a service called the Button Service. It contains two characteristics called Button A State and Button B State. Each of these characteristics supports Bluetooth notifications and so one of the first things the ButtonActivity class does is to enable those notifications by writing to their associated Client Characteristic Configuration Descriptors with a call to bluetooth_le_adapter.setNotificationsState. Having done so, every time you press a button on the micro:bit, this application receives a notification message containing the value of the characteristic. Three possible values are defined: 0 = not pressed, 1 = pressed, 2 = long press.
All the code for this demo can be found in ui.ButtonActivity.java except for the Bluetooth operations which are in bluetooth.BleAdapterService.


18 April 2021
Harold is alive!
Harold is a static site and blog generator based on Handlebars templating system and Markdown. There are two types of presentation possibilities (Page and Post) and couple of helpers. Here are some of the features:
- Search system based on pre-generated JSON data, indexed with Lunr
- Configurable posts lists with Handlebars helper
{{postsList
perPageLimit=6,
byTagName='javascript',
currentPage=1,
className='hrld-post-list',
noImage=false,
noExcerpt=false,
noTags=false,
noDate=false,
noReadMoreButton=false,
readMoreButtonLabel='Read more',
dateFormat='yyyy-mm-dd',
}}
- Scss support
- Wide images:
- Embeded media:
- Code highlighter:
const test = 'test';
console.log(test);
- Markdown Front Matter support
---
layout: 'blog-post'
title: 'Harold is alive!'
excerpt: "Excerpt of the featured example post."
coverImage: 'https://picsum.photos/id/82/1500/600'
tags:
- tag7
- featured
publicationDate: '2021-04-18'
---
- Support for social media meta tags
In markdown files (for blog posts):
ogTitle: 'Harold is alive!'
ogDescription: 'Harold is a static site generator based on Handlebars templating system and markdown'
ogUrl: ''
ogImage: ''
twitterTitle: 'Harold is alive!'
twitterDescription: 'Harold is a static site generator based on Handlebars templating system and markdown'
twitterUrl: ''
twitterImage: ''
Using Handlebars head partial (for subpages):
{{> head
title="Homepage"
description="Harold app default theme"
ogTitle="Harold Homepage"
ogDescription="Harold Description"
ogImage=""
twitterTitle="Harold Homepage"
twitterDescription="Harold Description"
twitterImage=""
}}
These are just examples. It can be configured as you need.
- Handlebars support
- Date formatter helper
{{formatDate date=publicationDate format='dd mmmm yyyy'}}
You can customize it as you want. This theme is just an example. It is simple to learn such tools looking into real code example.


| Package | Description |
|---|---|
| uk.co.caprica.vlcj.binding |
Provides the JNA bindings, and related classes, to use the libvlc native
library.
|
| uk.co.caprica.vlcj.player |
This is the main package for vlcj client applications, providing the classes
necessary to create and control native media players and associated
resources.
|
| Modifier and Type | Method and Description |
|---|---|
libvlc_media_player_t |
LibVlc.libvlc_media_player_new_from_media(libvlc_media_t p_md)
Create a Media Player object from a Media
|
libvlc_media_player_t |
LibVlc.libvlc_media_player_new(libvlc_instance_t p_libvlc_instance)
Create an empty Media Player object
|
| Modifier and Type | Method and Description |
|---|---|
int |
LibVlc.libvlc_audio_get_channel(libvlc_media_player_t p_mi)
Get current audio channel.
|
long |
LibVlc.libvlc_audio_get_delay(libvlc_media_player_t p_mi)
Get current audio delay.
|
int |
LibVlc.libvlc_audio_get_mute(libvlc_media_player_t p_mi)
Get current mute status.
|
int |
LibVlc.libvlc_audio_get_track_count(libvlc_media_player_t p_mi)
Get number of available audio tracks.
|
libvlc_track_description_t |
LibVlc.libvlc_audio_get_track_description(libvlc_media_player_t p_mi)
Get the description of available audio tracks.
|
int |
LibVlc.libvlc_audio_get_track(libvlc_media_player_t p_mi)
Get current audio track.
|
int |
LibVlc.libvlc_audio_get_volume(libvlc_media_player_t p_mi)
Get current software audio volume.
|
libvlc_audio_output_device_t |
LibVlc.libvlc_audio_output_device_enum(libvlc_media_player_t mp)
Gets a list of potential audio output devices, see
LibVlc.libvlc_audio_output_device_set(libvlc_media_player_t, String, String) . |
com.sun.jna.Pointer |
LibVlc.libvlc_audio_output_device_get(libvlc_media_player_t mp)
Get the current audio output device identifier.
|
void |
LibVlc.libvlc_audio_output_device_set(libvlc_media_player_t p_mi,
String psz_audio_output,
String psz_device_id)
Configures an explicit audio output device.
|
int |
LibVlc.libvlc_audio_output_set(libvlc_media_player_t p_mi,
String psz_name)
Sets the audio output.
|
void |
LibVlc.libvlc_audio_set_callbacks(libvlc_media_player_t mp,
libvlc_audio_play_cb play,
libvlc_audio_pause_cb pause,
libvlc_audio_resume_cb resume,
libvlc_audio_flush_cb flush,
libvlc_audio_drain_cb drain,
com.sun.jna.Pointer opaque)
Set callbacks and private data for decoded audio.
|
int |
LibVlc.libvlc_audio_set_channel(libvlc_media_player_t p_mi,
int channel)
Set current audio channel.
|
int |
LibVlc.libvlc_audio_set_delay(libvlc_media_player_t p_mi,
long i_delay)
Set current audio delay.
|
void |
LibVlc.libvlc_audio_set_format_callbacks(libvlc_media_player_t mp,
libvlc_audio_setup_cb setup,
libvlc_audio_cleanup_cb cleanup)
Set decoded audio format.
|
void |
LibVlc.libvlc_audio_set_format(libvlc_media_player_t mp,
String format,
int rate,
int channels)
Set decoded audio format.
|
void |
LibVlc.libvlc_audio_set_mute(libvlc_media_player_t p_mi,
int status)
Set mute status.
|
int |
LibVlc.libvlc_audio_set_track(libvlc_media_player_t p_mi,
int i_track)
Set current audio track.
|
void |
LibVlc.libvlc_audio_set_volume_callback(libvlc_media_player_t mp,
libvlc_audio_set_volume_cb set_volume)
Set callbacks and private data for decoded audio.
|
int |
LibVlc.libvlc_audio_set_volume(libvlc_media_player_t p_mi,
int i_volume)
Set current software audio volume.
|
void |
LibVlc.libvlc_audio_toggle_mute(libvlc_media_player_t p_mi)
Toggle mute status.
|
int |
LibVlc.libvlc_get_fullscreen(libvlc_media_player_t p_mi)
Get current fullscreen status.
|
void |
LibVlc.libvlc_media_list_player_set_media_player(libvlc_media_list_player_t p_mlp,
libvlc_media_player_t p_mi)
Replace media player in media_list_player with this instance.
|
int |
LibVlc.libvlc_media_player_can_pause(libvlc_media_player_t p_mi)
Can this media player be paused?
|
libvlc_event_manager_t |
LibVlc.libvlc_media_player_event_manager(libvlc_media_player_t p_mi)
Get the Event Manager from which the media player send event.
|
int |
LibVlc.libvlc_media_player_get_agl(libvlc_media_player_t p_mi)
Get the agl handler previously set with libvlc_media_player_set_agl().
|
int |
LibVlc.libvlc_media_player_get_chapter_count_for_title(libvlc_media_player_t p_mi,
int i_title)
Get title chapter count
|
int |
LibVlc.libvlc_media_player_get_chapter_count(libvlc_media_player_t p_mi)
Get movie chapter count
|
int |
LibVlc.libvlc_media_player_get_chapter(libvlc_media_player_t p_mi)
Get movie chapter.
|
float |
LibVlc.libvlc_media_player_get_fps(libvlc_media_player_t p_mi)
Get movie fps rate
|
com.sun.jna.Pointer |
LibVlc.libvlc_media_player_get_hwnd(libvlc_media_player_t p_mi)
Get the Windows API window handle (HWND) previously set with libvlc_media_player_set_hwnd().
|
long |
LibVlc.libvlc_media_player_get_length(libvlc_media_player_t p_mi)
Get the current movie length (in ms).
|
libvlc_media_t |
LibVlc.libvlc_media_player_get_media(libvlc_media_player_t p_mi)
Get the media used by the media_player.
|
com.sun.jna.Pointer |
LibVlc.libvlc_media_player_get_nsobject(libvlc_media_player_t p_mi)
Get the NSView handler previously set with libvlc_media_player_set_nsobject().
|
float |
LibVlc.libvlc_media_player_get_position(libvlc_media_player_t p_mi)
Get movie position.
|
float |
LibVlc.libvlc_media_player_get_rate(libvlc_media_player_t p_mi)
Get the requested movie play rate.
|
int |
LibVlc.libvlc_media_player_get_state(libvlc_media_player_t p_mi)
Get current movie state
|
long |
LibVlc.libvlc_media_player_get_time(libvlc_media_player_t p_mi)
Get the current movie time (in ms).
|
int |
LibVlc.libvlc_media_player_get_title_count(libvlc_media_player_t p_mi)
Get movie title count
|
int |
LibVlc.libvlc_media_player_get_title(libvlc_media_player_t p_mi)
Get movie title
|
int |
LibVlc.libvlc_media_player_get_xwindow(libvlc_media_player_t p_mi)
Get the X Window System window identifier previously set with
libvlc_media_player_set_xwindow().
|
int |
LibVlc.libvlc_media_player_has_vout(libvlc_media_player_t p_mi)
How many video outputs does this media player have?
|
int |
LibVlc.libvlc_media_player_is_playing(libvlc_media_player_t p_mi)
is_playing
|
int |
LibVlc.libvlc_media_player_is_seekable(libvlc_media_player_t p_mi)
Is this media player seekable?
|
void |
LibVlc.libvlc_media_player_navigate(libvlc_media_player_t p_mi,
int navigate)
Navigate through DVD Menu
|
void |
LibVlc.libvlc_media_player_next_chapter(libvlc_media_player_t p_mi)
Set next chapter (if applicable)
|
void |
LibVlc.libvlc_media_player_next_frame(libvlc_media_player_t p_mi)
Display the next frame (if supported)
|
void |
LibVlc.libvlc_media_player_pause(libvlc_media_player_t p_mi)
Toggle pause (no effect if there is no media)
|
int |
LibVlc.libvlc_media_player_play(libvlc_media_player_t p_mi)
Play
|
void |
LibVlc.libvlc_media_player_previous_chapter(libvlc_media_player_t p_mi)
Set previous chapter (if applicable)
|
int |
LibVlc.libvlc_media_player_program_scrambled(libvlc_media_player_t p_mi)
Is the current program scrambled?
|
void |
LibVlc.libvlc_media_player_release(libvlc_media_player_t p_mi)
Release a media_player after use Decrement the reference count of a media player object.
|
void |
LibVlc.libvlc_media_player_retain(libvlc_media_player_t p_mi)
Retain a reference to a media player object.
|
void |
LibVlc.libvlc_media_player_set_agl(libvlc_media_player_t p_mi,
int drawable)
Set the agl handler where the media player should render its video output.
|
void |
LibVlc.libvlc_media_player_set_chapter(libvlc_media_player_t p_mi,
int i_chapter)
Set movie chapter (if applicable).
|
int |
LibVlc.libvlc_media_player_set_equalizer(libvlc_media_player_t p_mi,
libvlc_equalizer_t p_equalizer)
Apply new equalizer settings to a media player.
|
void |
LibVlc.libvlc_media_player_set_hwnd(libvlc_media_player_t p_mi,
com.sun.jna.Pointer drawable)
Set a Win32/Win64 API window handle (HWND) where the media player should render its video
output.
|
void |
LibVlc.libvlc_media_player_set_media(libvlc_media_player_t p_mi,
libvlc_media_t p_md)
Set the media that will be used by the media_player.
|
void |
LibVlc.libvlc_media_player_set_nsobject(libvlc_media_player_t p_mi,
long drawable)
Set the NSView handler where the media player should render its video output.
|
void |
LibVlc.libvlc_media_player_set_pause(libvlc_media_player_t mp,
int do_pause)
Pause or resume (no effect if there is no media)
|
void |
LibVlc.libvlc_media_player_set_position(libvlc_media_player_t p_mi,
float f_pos)
Set movie position.
|
int |
LibVlc.libvlc_media_player_set_rate(libvlc_media_player_t p_mi,
float rate)
Set movie play rate
|
void |
LibVlc.libvlc_media_player_set_time(libvlc_media_player_t p_mi,
long i_time)
Set the movie time (in ms).
|
void |
LibVlc.libvlc_media_player_set_title(libvlc_media_player_t p_mi,
int i_title)
Set movie title
|
void |
LibVlc.libvlc_media_player_set_video_title_display(libvlc_media_player_t p_mi,
int position,
int timeout)
Set if, and how, the video title will be shown when media is played.
|
void |
LibVlc.libvlc_media_player_set_xwindow(libvlc_media_player_t p_mi,
int drawable)
Set an X Window System drawable where the media player should render its video output.
|
void |
LibVlc.libvlc_media_player_stop(libvlc_media_player_t p_mi)
Stop (no effect if there is no media)
|
int |
LibVlc.libvlc_media_player_will_play(libvlc_media_player_t p_mi)
Is the player able to play
|
void |
LibVlc.libvlc_set_fullscreen(libvlc_media_player_t p_mi,
int b_fullscreen)
Enable or disable fullscreen.
|
void |
LibVlc.libvlc_toggle_fullscreen(libvlc_media_player_t p_mi)
Toggle fullscreen status on non-embedded video outputs.
|
void |
LibVlc.libvlc_toggle_teletext(libvlc_media_player_t p_mi)
Toggle teletext transparent status on video output.
|
float |
LibVlc.libvlc_video_get_adjust_float(libvlc_media_player_t p_mi,
int option)
Get float adjust option.
|
int |
LibVlc.libvlc_video_get_adjust_int(libvlc_media_player_t p_mi,
int option)
Get integer adjust option.
|
com.sun.jna.Pointer |
LibVlc.libvlc_video_get_aspect_ratio(libvlc_media_player_t p_mi)
Get current video aspect ratio.
|
libvlc_track_description_t |
LibVlc.libvlc_video_get_chapter_description(libvlc_media_player_t p_mi,
int i_title)
Get the description of available chapters for specific title.
|
com.sun.jna.Pointer |
LibVlc.libvlc_video_get_crop_geometry(libvlc_media_player_t p_mi)
Get current crop filter geometry.
|
int |
LibVlc.libvlc_video_get_cursor(libvlc_media_player_t p_mi,
int num,
com.sun.jna.Pointer px,
com.sun.jna.Pointer py)
Get the mouse pointer coordinates over a video.
|
int |
LibVlc.libvlc_video_get_logo_int(libvlc_media_player_t p_mi,
int option)
Get integer logo option.
|
int |
LibVlc.libvlc_video_get_marquee_int(libvlc_media_player_t p_mi,
int option)
Get an integer marquee option value
|
String |
LibVlc.libvlc_video_get_marquee_string(libvlc_media_player_t p_mi,
int option)
Get a string marquee option value
|
float |
LibVlc.libvlc_video_get_scale(libvlc_media_player_t p_mi)
Get the current video scaling factor.
|
int |
LibVlc.libvlc_video_get_size(libvlc_media_player_t p_mi,
int num,
com.sun.jna.ptr.IntByReference px,
com.sun.jna.ptr.IntByReference py)
Get the pixel dimensions of a video.
|
int |
LibVlc.libvlc_video_get_spu_count(libvlc_media_player_t p_mi)
Get the number of available video subtitles.
|
long |
LibVlc.libvlc_video_get_spu_delay(libvlc_media_player_t p_mi)
Get the current subtitle delay.
|
libvlc_track_description_t |
LibVlc.libvlc_video_get_spu_description(libvlc_media_player_t p_mi)
Get the description of available video subtitles.
|
int |
LibVlc.libvlc_video_get_spu(libvlc_media_player_t p_mi)
Get current video subtitle.
|
int |
LibVlc.libvlc_video_get_teletext(libvlc_media_player_t p_mi)
Get current teletext page requested.
|
libvlc_track_description_t |
LibVlc.libvlc_video_get_title_description(libvlc_media_player_t p_mi)
Get the description of available titles.
|
int |
LibVlc.libvlc_video_get_track_count(libvlc_media_player_t p_mi)
Get number of available video tracks.
|
libvlc_track_description_t |
LibVlc.libvlc_video_get_track_description(libvlc_media_player_t p_mi)
Get the description of available video tracks.
|
int |
LibVlc.libvlc_video_get_track(libvlc_media_player_t p_mi)
Get current video track.
|
void |
LibVlc.libvlc_video_set_adjust_float(libvlc_media_player_t p_mi,
int option,
float value)
Set adjust option as float.
|
void |
LibVlc.libvlc_video_set_adjust_int(libvlc_media_player_t p_mi,
int option,
int value)
Set adjust option as integer.
|
void |
LibVlc.libvlc_video_set_aspect_ratio(libvlc_media_player_t p_mi,
String psz_aspect)
Set new video aspect ratio.
|
void |
LibVlc.libvlc_video_set_callbacks(libvlc_media_player_t mp,
libvlc_lock_callback_t lock,
libvlc_unlock_callback_t unlock,
libvlc_display_callback_t display,
com.sun.jna.Pointer opaque)
Set callbacks and private data to render decoded video to a custom area in memory.
|
void |
LibVlc.libvlc_video_set_crop_geometry(libvlc_media_player_t p_mi,
String psz_geometry)
Set new crop filter geometry.
|
void |
LibVlc.libvlc_video_set_deinterlace(libvlc_media_player_t p_mi,
String psz_mode)
Enable or disable deinterlace filter
|
void |
LibVlc.libvlc_video_set_format_callbacks(libvlc_media_player_t mp,
libvlc_video_format_cb setup,
libvlc_video_cleanup_cb cleanup)
Set decoded video chroma and dimensions.
|
void |
LibVlc.libvlc_video_set_format(libvlc_media_player_t mp,
String chroma,
int width,
int height,
int pitch)
Set decoded video chroma and dimensions.
|
void |
LibVlc.libvlc_video_set_key_input(libvlc_media_player_t p_mi,
int on)
Enable or disable key press events handling, according to the LibVLC hotkeys configuration.
|
void |
LibVlc.libvlc_video_set_logo_int(libvlc_media_player_t p_mi,
int option,
int value)
Set logo option as integer.
|
void |
LibVlc.libvlc_video_set_logo_string(libvlc_media_player_t p_mi,
int option,
String psz_value)
Set logo option as string.
|
void |
LibVlc.libvlc_video_set_marquee_int(libvlc_media_player_t p_mi,
int option,
int i_val)
Enable, disable or set an integer marquee option Setting libvlc_marquee_Enable has the side
effect of enabling (arg !0) or disabling (arg 0) the marq filter.
|
void |
LibVlc.libvlc_video_set_marquee_string(libvlc_media_player_t p_mi,
int option,
String psz_text)
Set a marquee string option
|
void |
LibVlc.libvlc_video_set_mouse_input(libvlc_media_player_t p_mi,
int on)
Enable or disable mouse click events handling.
|
void |
LibVlc.libvlc_video_set_scale(libvlc_media_player_t p_mi,
float f_factor)
Set the video scaling factor.
|
int |
LibVlc.libvlc_video_set_spu_delay(libvlc_media_player_t p_mi,
long i_delay)
Set the subtitle delay.
|
int |
LibVlc.libvlc_video_set_spu(libvlc_media_player_t p_mi,
int i_spu)
Set new video subtitle.
|
int |
LibVlc.libvlc_video_set_subtitle_file(libvlc_media_player_t p_mi,
String psz_subtitle)
Set new video subtitle file.
|
void |
LibVlc.libvlc_video_set_teletext(libvlc_media_player_t p_mi,
int i_page)
Set new teletext page to retrieve.
|
int |
LibVlc.libvlc_video_set_track(libvlc_media_player_t p_mi,
int i_track)
Set video track.
|
int |
LibVlc.libvlc_video_take_snapshot(libvlc_media_player_t p_mi,
int num,
String psz_filepath,
int i_width,
int i_height)
Take a snapshot of the current video window.
|
| Modifier and Type | Method and Description |
|---|---|
libvlc_media_player_t |
MediaPlayer.mediaPlayerInstance()
Provide access to the native media player instance.
|
libvlc_media_player_t |
DefaultMediaPlayer.mediaPlayerInstance() |
Copyright © 2009–2015 Caprica Software Limited. All rights reserved.


{% extends "_base.htm" %} {% block title %} {{page}} {% endblock %} {% block app_params %}'{{page}}', '{{user}}', '{{login}}', '{{logout}}' {% endblock %} {% block content %}
{{memo.content}}
Pin a fixed-height footer to the bottom of the viewport in desktop browsers with this custom HTML and CSS. A fixed navbar has been added within #wrap
with padding-top: 60px;
on the .container
.


Welcome to the Accelerator
Hey Techies,
We are happy that you are interested and joined our between-semester program. Now that you have finished your Digital Shaper projects, you have realised that developing data science solutions takes longer then expected and that you would like to become faster and improve your knowledge in data science. This is what the Data Science Accelerator is for, to accelerate your data science skills! The Data Science Accelerator will give you a deeper understanding of Python & Data Science, as well as a sneak peek for your next steps as data scientist: Artifical Intelligence.
Based on these, the track is seperated into three parts:
-
Python Deep-Dive
Data Science is like every craft: The better you know your tools, the faster and better are your results. The main tool you will be using for data science will be Python and its various libraries, so learning more about them will accelerate your data science skills, by quite a bit! This section won`t be an introduction into Python, instead we will build on your foundation and introduce more complex & powerful topics.
-
Data Science Deep-Dive
What is the second best way of getting faster and better in data science, after learning more about Python? The answer is more data science. Just as in the previous section, we will build on your existing skill set and dive deeper into data science. While a big part of data science is about coding and models, we will also introduce more soft topics of data science, such as how to define a data science problem and how to communicate with your non-ds team mates.
-
Artifical Intelligence Sneak Peek
While the differences are not always clear, and many people (especially the ones who don`t know anything about tech) will use them interchangable, AI is nothing else then a subgroup of data science. You feed a model some data, and it will be able to predict some output. To give you a better insight, that it is not magic we will give you a sneak peak into this whole field.
Before you start learning the real material, please go through our introduction docuemnts to get you into the right mindset, to see what is the difference between the digital shaper program and the accelerator and how to set up your working environment.
Hope you have a great time
Merlin & Max!