best visualization software

By placing different game objects in different layers can be very convenient control of different types of game objects, if you do not want to change some of the game objects, such as ground decoration, you can click on the Layer drop-down menu to lock themYou can also set whether to show or hide objects in the layer by controlling the eye icon in the Layer drop-down menu.It's important to note that there are up to 25 layers in unity, but that's enough for us.TIPS3: Use the Layer drop-down menu

Http://blog.csdn.net/pipisorryBrowse LDA Topic ModelsThis is allows you to create a set of the HTML files to browse a topic model. It creates a word cloud and time-graph per topic, and annotates a selection of documents with the topic for each word.See the [The example] (Http://rpubs.com/vanatteveldt/topicbrowser) for a collection of the the The Union addresses.Installing installationOn the R command line, enter: if (! Require (devtools )) {install.packages ( " devtools " ); Library (devtools

Learning is really a wonderful thing. I've seen this book before, and some of the knowledge points are completely out of the picture.Summary: The use of knowledge to study well, usually can understand the basis of other technologies, the relevant information and difficulties recorded.JavaScript traps1, variable type var myName = ' SFP '; typeOf myName; ' String ' 2, variable elevation for (var i=0; iSvgYou need to specify width,height for SVG; the element's attribute values are not unit

See this message on @wolframchina Weibo:But directly with:EntityValue["PopularCurve","Entities"]Just show a very long curve name that is far more than 3,500 (which should currently be 3750) and does not print picture information. The fun is still the picture ah.Find someone to ask, the original to do this:Print[Labeled{"Image", "Name"}]] /@ EntityValue["PopularCurve""Entities"];As long as the computer's memory is large enough, it will be shown in alphabetical order of these curve names. Here t

, where you can design the main body of the new analysis.650) this.width=650; "src=" http://pic.pc6.com/up/2015-1/14224140158935530.jpg "style=" border:0px; "alt=" 14224140158935530.jpg "/>Here, the data source and the new data analysis are done, and the next step is to do a detailed analysis of the data, such as documentation examples.Gender dimension analysis by sectorThe distribution of male and female workers in various departments, through the theory of enterprise management, enterprise tec

with the GGPLOT2 in the R language, it seems that two packages are used and the likelihood is developed by the same person! The original author also said on GITHUB that the PYTHON library will no longer be updated! However, ggplot2 is really a drawing artifact, which is almost the only reason I am still using the R language. Therefore, matplotlib is required no matter which library you want to use. Although his syntax is complex, he is flexible. you can draw almost any image you want. Here we

It is a simple visualization of domestic airports and route information. The dot represents the location of 163 airports in China, and the line shows 5381 routes. I have seen on this website that the author used the r language to visualize route entries around the world. This figure is the result of imitating the shanzhai. However, the generation of this image is not as complex as that of the original image. The geographic chart package and steps used

Revoke strative rendering often also depicted as non-photorealistic rendering or stylized rendering, employs modify action techniques to convey the relevant information, and de-emphasize less important details. the question remains how this happens action process is guided and in the particle how can we ensure that relevant information is maintained. consequently, research on semantic strative rendering needs to address how the information is perceived by the human observer, next to the investig

After listening to nividia's visualization computing technology recently, I feel quite deeply. If transactions or data can be displayed graphically, the most direct feeling can be given. The number of rows in the financial market is huge, and there are more and more types of transactions in the financial market (number of shares, number of funds, number of bonds, derivatives, etc ), if this data is displayed in a more direct way before the eyes of inv

The mininet 2.2.0 version has a built-in Mininet visualizer miniedit, which facilitates user-defined topology creation with the Mininet visual interface, creating a simpler environment for users unfamiliar with Python scripts, intuitive interface and strong operability.In short, it is simpler than writing a Python script, reducing the threshold of SDN entry, embarrassing, I also recently know that there is this function, together to learn a wave.Mininet are all started with root privileges, so M

method is simple to add the marginal carpet function on the basis of the original scatter plot function. The R language implementation code is as follows:# base function Ggplot (Faithful, AES (x = eruptions, y = waiting)) + # Scatter graph function geom_point () + # Marginal carpet function Geom_rug ()　　Operation Result:add a label to a scatter plotThis example uses the following test data set:The method of adding labels to scatter plots is also simple, adding text functions on the basis

frame before merging is called wide data, is it appropriate?The following R language code uses the MELT function to "elongate" the above data set:# Melt function: The first election to set the data frame, the election of the Record Identification column, Variable.name selected the Elongated property name, Value.name selected the elongated attribute Value column melt (anthoming, id.vars = "angle", Variable.name = "condition", Value.name = "Count")The effect after stretching:2. Long data-wide dat

bordercolor:uicolor?{didset {layer.bordercolor= BorderColor?. Cgcolor}}OverrideInit (frame:cgrect) {super.init (frame:frame) initialfromxib ()} required init?(coder Adecoder:nscoder) {super.init (Coder:adecoder) Initialfromxib ()} func initialfromxib () {Let bundle=NSBundle (forClass:self.dynamicType) let nib= Uinib (nibname:"Idcard", Bundle:bundle) Contentview= Nib.instantiatewithowner (self, options:nil) [0] as!UIView Contentview.frame=bounds Addsubview (Contentview)}}6. Drag into view at Mai

Python development [module]: CSV file data visualization,CSV Module 1. CSV file format To store data in a text file, the simplest way is to write data into a file as a series of comma-separated values (CSV). Such a file becomes a CSV file, as shown below: AKDT,Max TemperatureF,Mean TemperatureF,Min TemperatureF,Max Dew PointF,MeanDew PointF,Min DewpointF,Max Humidity, Mean Humidity, Min Humidity, Max Sea Level PressureIn, Mean Sea Level PressureIn, Mi

= Rev (levels (Uspopage$agegroup)))Operation Result:If you need to draw a percentage stacked chart, simply modify the underlying data based on the work above.The R language implementation code is as follows:# Convert data to percent format Uspopage_prop = ddply (Uspopage, "year", transform, Percent = Thousands/sum (Thousands) * 100) # base function Ggplot (USP Opage_prop, AES (x = year, y = Percent, fill = agegroup)) + # area graph function Geom_area () + # palette ruler Scale_fill_brewer (

1. Introduction to the three major mapping systems of R1.1 Basic drawing System (base plotting systems)-Artist's palette: drawing suitable for blank canvas· need to implement plans; visualize the logic of drawing and analyzing data in real time-Two steps = figure + Modify/Add = Perform a series of functions-Suitable for drawing 2D graphs1.2 Lattice Drawing System (Lattice plotting systems)-draw = Use a function call once (a graph)-Ideal for interacting with observational variables: How variable

5. Color of the R language drawing· Grdevice Bag-Colorramp () and Colorramppalette ()-color names can be obtained using colors ()· Rcolorbrewer Bag-Three types of palettes:1. Sequential: From an extreme gradient to another extreme, suitable for rendering sequential data　　　　　　　　2. Diverging: Bright at both ends and lighter in the middle, suitable to highlight the extreme values, that is, to emphasize the choice of high and low contrast　　　　　　　　3. Qualitative: color contrast between colors, suitabl

])cluster analysis based on results　　numpy.vstack: https://docs.scipy.org/doc/numpy/reference/generated/numpy.vstack.html　　Scipy.cluster.vq.kmeans: https://docs.scipy.org/doc/scipy/reference/generated/ Scipy.cluster.vq.kmeans.html#scipy.cluster.vq.kmeans　　scipy.cluster.vq.vq: https://docs.scipy.org/doc/scipy/reference/generated/scipy.cluster.vq.vq.html2. Matplotlib Drawing Basics3. Matplotlib Image Attribute Control4. Pandas drawing5. Data access6. Python's Engineering applications7. Python's hu

visualization forms. Bokeh's documents are well combed and contain a lot of examples to show you what you can do with it. It's worth browsing through its documentation so you can see what other charts look like and how short the code is to produce such beautiful results. The only thing I'm complaining about is that Bokeh doesn't provide a way to save pictures programmatically. For two years, this has been a bug they've been working on to modify. The

CODE:#!/usr/bin/python #-*-Coding:utf-8-*-"Created on 2014-7-8@author:guaguastd@name:plot_frequencies_words.py" if _ _name__ = = ' __main__ ': #import JSON # import Counter from collections Import Counter # import Search From search Import Search_for_tweet # import visualize from visualize import visualize_for_frequencies # import login, see http://blog.csdn.net/guaguastd/article/details/31706155 from login import Twitter_login # ge T the twitter access API Twitter_api = Twitter_login