Search Results

Search found 2479 results on 100 pages for 'operator'.

Page 40/100 | < Previous Page | 36 37 38 39 40 41 42 43 44 45 46 47  | Next Page >

• C++ array of classes

  - by nickik

  I working on a game but I have a problem with the initialization of the level. (feld is just field in german) class level{ private: feld spielfeld[10][10]; public: /* other staff */ void init_feld(); }; void level::init_feld() { for(int i=0;i!=10;i++){ for(int n=0;n!=10;n++){ spielfeld[i][n] = new feld(land, i, n); } } } The Error: Error: no match for »operator=« in »((level*)this)-level::spielfeld[i][n] = (operator new(24u), (, ((feld*))))« /home/nick/stratego/feld.h:18:11: Remark: candidate is: feld& feld::operator=(const feld&) Process terminated with status 1 (0 minutes, 0 seconds) 2 errors, 0 warnings

  Read the article

• C# Neural Networks with Encog

  - by JoshReuben

  Neural Networks ·       I recently read a book Introduction to Neural Networks for C# , by Jeff Heaton. http://www.amazon.com/Introduction-Neural-Networks-C-2nd/dp/1604390093/ref=sr_1_2?ie=UTF8&s=books&qid=1296821004&sr=8-2-spell. Not the 1st ANN book I've perused, but a nice revision.   ·       Artificial Neural Networks (ANNs) are a mechanism of machine learning – see http://en.wikipedia.org/wiki/Artificial_neural_network , http://en.wikipedia.org/wiki/Category:Machine_learning ·       Problems Not Suited to a Neural Network Solution- Programs that are easily written out as flowcharts consisting of well-defined steps, program logic that is unlikely to change, problems in which you must know exactly how the solution was derived. ·       Problems Suited to a Neural Network – pattern recognition, classification, series prediction, and data mining. Pattern recognition - network attempts to determine if the input data matches a pattern that it has been trained to recognize. Classification - take input samples and classify them into fuzzy groups. ·       As far as machine learning approaches go, I thing SVMs are superior (see http://en.wikipedia.org/wiki/Support_vector_machine ) - a neural network has certain disadvantages in comparison: an ANN can be overtrained, different training sets can produce non-deterministic weights and it is not possible to discern the underlying decision function of an ANN from its weight matrix – they are black box. ·       In this post, I'm not going to go into internals (believe me I know them). An autoassociative network (e.g. a Hopfield network) will echo back a pattern if it is recognized. ·       Under the hood, there is very little maths. In a nutshell - Some simple matrix operations occur during training: the input array is processed (normalized into bipolar values of 1, -1) - transposed from input column vector into a row vector, these are subject to matrix multiplication and then subtraction of the identity matrix to get a contribution matrix. The dot product is taken against the weight matrix to yield a boolean match result. For backpropogation training, a derivative function is required. In learning, hill climbing mechanisms such as Genetic Algorithms and Simulated Annealing are used to escape local minima. For unsupervised training, such as found in Self Organizing Maps used for OCR, Hebbs rule is applied. ·       The purpose of this post is not to mire you in technical and conceptual details, but to show you how to leverage neural networks via an abstraction API - Encog   Encog ·       Encog is a neural network API ·       Links to Encog: http://www.encog.org , http://www.heatonresearch.com/encog, http://www.heatonresearch.com/forum ·       Encog requires .Net 3.5 or higher – there is also a Silverlight version. Third-Party Libraries – log4net and nunit. ·       Encog supports feedforward, recurrent, self-organizing maps, radial basis function and Hopfield neural networks. ·       Encog neural networks, and related data, can be stored in .EG XML files. ·       Encog Workbench allows you to edit, train and visualize neural networks. The Encog Workbench can generate code. Synapses and layers ·       the primary building blocks - Almost every neural network will have, at a minimum, an input and output layer. In some cases, the same layer will function as both input and output layer. ·       To adapt a problem to a neural network, you must determine how to feed the problem into the input layer of a neural network, and receive the solution through the output layer of a neural network. ·       The Input Layer - For each input neuron, one double value is stored. An array is passed as input to a layer. Encog uses the interface INeuralData to hold these arrays. The class BasicNeuralData implements the INeuralData interface. Once the neural network processes the input, an INeuralData based class will be returned from the neural network's output layer. ·       convert a double array into an INeuralData object : INeuralData data = new BasicNeuralData(= new double[10]); ·       the Output Layer- The neural network outputs an array of doubles, wraped in a class based on the INeuralData interface. ·        The real power of a neural network comes from its pattern recognition capabilities. The neural network should be able to produce the desired output even if the input has been slightly distorted. ·       Hidden Layers– optional. between the input and output layers. very much a “black box”. If the structure of the hidden layer is too simple it may not learn the problem. If the structure is too complex, it will learn the problem but will be very slow to train and execute. Some neural networks have no hidden layers. The input layer may be directly connected to the output layer. Further, some neural networks have only a single layer. A single layer neural network has the single layer self-connected. ·       connections, called synapses, contain individual weight matrixes. These values are changed as the neural network learns. Constructing a Neural Network ·       the XOR operator is a frequent “first example” -the “Hello World” application for neural networks. ·       The XOR Operator- only returns true when both inputs differ. 0 XOR 0 = 0 1 XOR 0 = 1 0 XOR 1 = 1 1 XOR 1 = 0 ·       Structuring a Neural Network for XOR  - two inputs to the XOR operator and one output. ·       input: 0.0,0.0 1.0,0.0 0.0,1.0 1.0,1.0 ·       Expected output: 0.0 1.0 1.0 0.0 ·       A Perceptron - a simple feedforward neural network to learn the XOR operator. ·       Because the XOR operator has two inputs and one output, the neural network will follow suit. Additionally, the neural network will have a single hidden layer, with two neurons to help process the data. The choice for 2 neurons in the hidden layer is arbitrary, and often comes down to trial and error. ·       Neuron Diagram for the XOR Network ·       ·       The Encog workbench displays neural networks on a layer-by-layer basis. ·       Encog Layer Diagram for the XOR Network:   ·       Create a BasicNetwork - Three layers are added to this network. the FinalizeStructure method must be called to inform the network that no more layers are to be added. The call to Reset randomizes the weights in the connections between these layers. var network = new BasicNetwork(); network.AddLayer(new BasicLayer(2)); network.AddLayer(new BasicLayer(2)); network.AddLayer(new BasicLayer(1)); network.Structure.FinalizeStructure(); network.Reset(); ·       Neural networks frequently start with a random weight matrix. This provides a starting point for the training methods. These random values will be tested and refined into an acceptable solution. However, sometimes the initial random values are too far off. Sometimes it may be necessary to reset the weights again, if training is ineffective. These weights make up the long-term memory of the neural network. Additionally, some layers have threshold values that also contribute to the long-term memory of the neural network. Some neural networks also contain context layers, which give the neural network a short-term memory as well. The neural network learns by modifying these weight and threshold values. ·       Now that the neural network has been created, it must be trained. Training a Neural Network ·       construct a INeuralDataSet object - contains the input array and the expected output array (of corresponding range). Even though there is only one output value, we must still use a two-dimensional array to represent the output. public static double[][] XOR_INPUT ={ new double[2] { 0.0, 0.0 }, new double[2] { 1.0, 0.0 }, new double[2] { 0.0, 1.0 }, new double[2] { 1.0, 1.0 } };   public static double[][] XOR_IDEAL = { new double[1] { 0.0 }, new double[1] { 1.0 }, new double[1] { 1.0 }, new double[1] { 0.0 } };   INeuralDataSet trainingSet = new BasicNeuralDataSet(XOR_INPUT, XOR_IDEAL); ·       Training is the process where the neural network's weights are adjusted to better produce the expected output. Training will continue for many iterations, until the error rate of the network is below an acceptable level. Encog supports many different types of training. Resilient Propagation (RPROP) - general-purpose training algorithm. All training classes implement the ITrain interface. The RPROP algorithm is implemented by the ResilientPropagation class. Training the neural network involves calling the Iteration method on the ITrain class until the error is below a specific value. The code loops through as many iterations, or epochs, as it takes to get the error rate for the neural network to be below 1%. Once the neural network has been trained, it is ready for use. ITrain train = new ResilientPropagation(network, trainingSet);   for (int epoch=0; epoch < 10000; epoch++) { train.Iteration(); Debug.Print("Epoch #" + epoch + " Error:" + train.Error); if (train.Error > 0.01) break; } Executing a Neural Network ·       Call the Compute method on the BasicNetwork class. Console.WriteLine("Neural Network Results:"); foreach (INeuralDataPair pair in trainingSet) { INeuralData output = network.Compute(pair.Input); Console.WriteLine(pair.Input[0] + "," + pair.Input[1] + ", actual=" + output[0] + ",ideal=" + pair.Ideal[0]); } ·       The Compute method accepts an INeuralData class and also returns a INeuralData object. Neural Network Results: 0.0,0.0, actual=0.002782538818034049,ideal=0.0 1.0,0.0, actual=0.9903741937121177,ideal=1.0 0.0,1.0, actual=0.9836807956566187,ideal=1.0 1.0,1.0, actual=0.0011646072586172778,ideal=0.0 ·       the network has not been trained to give the exact results. This is normal. Because the network was trained to 1% error, each of the results will also be within generally 1% of the expected value.

  Read the article

• Are there real world applications where the use of prefix versus postfix operators matters?

  - by Kenneth

  In college it is taught how you can do math problems which use the ++ or -- operators on some variable referenced in the equation such that the result of the equation would yield different results if you switched the operator from postfix to prefix or vice versa. Are there any real world applications of using postfix or prefix operator where it makes a difference as to which you use? It doesn't seem to me (maybe I just don't have enough experience yet in programming) that there really is much use to having the different operators if it only applies in math equations. EDIT: Suggestions so far include: function calls //f(++x) != f(x++) loop comparison //while (++i < MAX) != while (i++ < MAX)

  Read the article

• Create user in Oracle 11g with same priviledges as in Oracle 10g XE

  - by Álvaro G. Vicario

  I'm a PHP developer (not a DBA) and I've been working with Oracle 10g XE for a while. I'm used to XE's simplified user management: Go to Administration/ Users/ Create user Assign user name and password Roles: leave the default ones (connect and resource) Privileges: click on "Enable all" to select the 11 possible ones Create This way I get a user that has full access to its data and no access to everything else. This is fine since I only need it to develop my app. When the app is to be deployed, the client's DBAs configure the environment. Now I have to create users in a full Oracle 11g server and I'm completely lost. I have a new concept (profiles) and there're like 20 roles and hundreds of privileges in various categories. What steps do I need to complete in Oracle Enterprise Manager in order to obtain a user with the same privileges I used to assign in XE? ==== UPDATE ==== I think I'd better provide a detailed explanation so I make myself clearer. This is how I create a user in 10g XE: Roles: [X] CONNECT [X] RESOURCE [ ] DBA Direct Asignment System Privileges: [ ] CREATE DATABASE LINK [ ] CREATE MATERIALIZED VIEW [ ] CREATE PROCEDURE [ ] CREATE PUBLIC SYNONYM [ ] CREATE ROLE [ ] CREATE SEQUENCE [ ] CREATE SYNONYM [ ] CREATE TABLE [ ] CREATE TRIGGER [ ] CREATE TYPE [ ] CREATE VIEW I click on Enable All and I'm done. This is what I'm asked when doing the same in 11g: Profile: (*) DEFAULT ( ) WKSYS_PROF ( ) MONITORING_PROFILE Roles: CONNECT: [ ] Admin option [X] Default value Edit List: AQ_ADMINISTRATOR_ROLE AQ_USER_ROLE AUTHENTICATEDUSER CSW_USR_ROLE CTXAPP CWM_USER DATAPUMP_EXP_FULL_DATABASE DATAPUMP_IMP_FULL_DATABASE DBA DELETE_CATALOG_ROLE EJBCLIENT EXECUTE_CATALOG_ROLE EXP_FULL_DATABASE GATHER_SYSTEM_STATISTICS GLOBAL_AQ_USER_ROLE HS_ADMIN_ROLE IMP_FULL_DATABASE JAVADEBUGPRIV JAVAIDPRIV JAVASYSPRIV JAVAUSERPRIV JAVA_ADMIN JAVA_DEPLOY JMXSERVER LOGSTDBY_ADMINISTRATOR MGMT_USER OEM_ADVISOR OEM_MONITOR OLAPI_TRACE_USER OLAP_DBA OLAP_USER OLAP_XS_ADMIN ORDADMIN OWB$CLIENT OWB_DESIGNCENTER_VIEW OWB_USER RECOVERY_CATALOG_OWNER RESOURCE SCHEDULER_ADMIN SELECT_CATALOG_ROLE SPATIAL_CSW_ADMIN SPATIAL_WFS_ADMIN WFS_USR_ROLE WKUSER WM_ADMIN_ROLE XDBADMIN XDB_SET_INVOKER XDB_WEBSERVICES XDB_WEBSERVICES_OVER_HTTP XDB_WEBSERVICES_WITH_PUBLIC System Privileges: <Empty> Edit List: ACCESS_ANY_WORKSPACE ADMINISTER ANY SQL TUNING SET ADMINISTER DATABASE TRIGGER ADMINISTER RESOURCE MANAGER ADMINISTER SQL MANAGEMENT OBJECT ADMINISTER SQL TUNING SET ADVISOR ALTER ANY ASSEMBLY ALTER ANY CLUSTER ALTER ANY CUBE ALTER ANY CUBE DIMENSION ALTER ANY DIMENSION ALTER ANY EDITION ALTER ANY EVALUATION CONTEXT ALTER ANY INDEX ALTER ANY INDEXTYPE ALTER ANY LIBRARY ALTER ANY MATERIALIZED VIEW ALTER ANY MINING MODEL ALTER ANY OPERATOR ALTER ANY OUTLINE ALTER ANY PROCEDURE ALTER ANY ROLE ALTER ANY RULE ALTER ANY RULE SET ALTER ANY SEQUENCE ALTER ANY SQL PROFILE ALTER ANY TABLE ALTER ANY TRIGGER ALTER ANY TYPE ALTER DATABASE ALTER PROFILE ALTER RESOURCE COST ALTER ROLLBACK SEGMENT ALTER SESSION ALTER SYSTEM ALTER TABLESPACE ALTER USER ANALYZE ANY ANALYZE ANY DICTIONARY AUDIT ANY AUDIT SYSTEM BACKUP ANY TABLE BECOME USER CHANGE NOTIFICATION COMMENT ANY MINING MODEL COMMENT ANY TABLE CREATE ANY ASSEMBLY CREATE ANY CLUSTER CREATE ANY CONTEXT CREATE ANY CUBE CREATE ANY CUBE BUILD PROCESS CREATE ANY CUBE DIMENSION CREATE ANY DIMENSION CREATE ANY DIRECTORY CREATE ANY EDITION CREATE ANY EVALUATION CONTEXT CREATE ANY INDEX CREATE ANY INDEXTYPE CREATE ANY JOB CREATE ANY LIBRARY CREATE ANY MATERIALIZED VIEW CREATE ANY MEASURE FOLDER CREATE ANY MINING MODEL CREATE ANY OPERATOR CREATE ANY OUTLINE CREATE ANY PROCEDURE CREATE ANY RULE CREATE ANY RULE SET CREATE ANY SEQUENCE CREATE ANY SQL PROFILE CREATE ANY SYNONYM CREATE ANY TABLE CREATE ANY TRIGGER CREATE ANY TYPE CREATE ANY VIEW CREATE ASSEMBLY CREATE CLUSTER CREATE CUBE CREATE CUBE BUILD PROCESS CREATE CUBE DIMENSION CREATE DATABASE LINK CREATE DIMENSION CREATE EVALUATION CONTEXT CREATE EXTERNAL JOB CREATE INDEXTYPE CREATE JOB CREATE LIBRARY CREATE MATERIALIZED VIEW CREATE MEASURE FOLDER CREATE MINING MODEL CREATE OPERATOR CREATE PROCEDURE CREATE PROFILE CREATE PUBLIC DATABASE LINK CREATE PUBLIC SYNONYM CREATE ROLE CREATE ROLLBACK SEGMENT CREATE RULE CREATE RULE SET CREATE SEQUENCE CREATE SESSION CREATE SYNONYM CREATE TABLE CREATE TABLESPACE CREATE TRIGGER CREATE TYPE CREATE USER CREATE VIEW CREATE_ANY_WORKSPACE DEBUG ANY PROCEDURE DEBUG CONNECT SESSION DELETE ANY CUBE DIMENSION DELETE ANY MEASURE FOLDER DELETE ANY TABLE DEQUEUE ANY QUEUE DROP ANY ASSEMBLY DROP ANY CLUSTER DROP ANY CONTEXT DROP ANY CUBE DROP ANY CUBE BUILD PROCESS DROP ANY CUBE DIMENSION DROP ANY DIMENSION DROP ANY DIRECTORY DROP ANY EDITION DROP ANY EVALUATION CONTEXT DROP ANY INDEX DROP ANY INDEXTYPE DROP ANY LIBRARY DROP ANY MATERIALIZED VIEW DROP ANY MEASURE FOLDER DROP ANY MINING MODEL DROP ANY OPERATOR DROP ANY OUTLINE DROP ANY PROCEDURE DROP ANY ROLE DROP ANY RULE DROP ANY RULE SET DROP ANY SEQUENCE DROP ANY SQL PROFILE DROP ANY SYNONYM DROP ANY TABLE DROP ANY TRIGGER DROP ANY TYPE DROP ANY VIEW DROP PROFILE DROP PUBLIC DATABASE LINK DROP PUBLIC SYNONYM DROP ROLLBACK SEGMENT DROP TABLESPACE DROP USER ENQUEUE ANY QUEUE EXECUTE ANY ASSEMBLY EXECUTE ANY CLASS EXECUTE ANY EVALUATION CONTEXT EXECUTE ANY INDEXTYPE EXECUTE ANY LIBRARY EXECUTE ANY OPERATOR EXECUTE ANY PROCEDURE EXECUTE ANY PROGRAM EXECUTE ANY RULE EXECUTE ANY RULE SET EXECUTE ANY TYPE EXECUTE ASSEMBLY EXPORT FULL DATABASE FLASHBACK ANY TABLE FLASHBACK ARCHIVE ADMINISTER FORCE ANY TRANSACTION FORCE TRANSACTION FREEZE_ANY_WORKSPACE GLOBAL QUERY REWRITE GRANT ANY OBJECT PRIVILEGE GRANT ANY PRIVILEGE GRANT ANY ROLE IMPORT FULL DATABASE INSERT ANY CUBE DIMENSION INSERT ANY MEASURE FOLDER INSERT ANY TABLE LOCK ANY TABLE MANAGE ANY FILE GROUP MANAGE ANY QUEUE MANAGE FILE GROUP MANAGE SCHEDULER MANAGE TABLESPACE MERGE ANY VIEW MERGE_ANY_WORKSPACE ON COMMIT REFRESH QUERY REWRITE READ ANY FILE GROUP REMOVE_ANY_WORKSPACE RESTRICTED SESSION RESUMABLE ROLLBACK_ANY_WORKSPACE SELECT ANY CUBE SELECT ANY CUBE DIMENSION SELECT ANY DICTIONARY SELECT ANY MINING MODEL SELECT ANY SEQUENCE SELECT ANY TABLE SELECT ANY TRANSACTION UNDER ANY TABLE UNDER ANY TYPE UNDER ANY VIEW UNLIMITED TABLESPACE UPDATE ANY CUBE UPDATE ANY CUBE BUILD PROCESS UPDATE ANY CUBE DIMENSION UPDATE ANY TABLE Object Privileges: <Empty> Add: Clase Java Clases de Trabajos Cola Columna de Tabla Columna de Vista Espacio de Trabajo Función Instantánea Origen Java Paquete Planificaciones Procedimiento Programas Secuencia Sinónimo Tabla Tipos Trabajos Vista Consumer Group Privileges: <Empty> Default Consumer Group: (*) None Edit List: AUTO_TASK_CONSUMER_GROUP BATCH_GROUP DEFAULT_CONSUMER_GROUP INTERACTIVE_GROUP LOW_GROUP ORA$AUTOTASK_HEALTH_GROUP ORA$AUTOTASK_MEDIUM_GROUP ORA$AUTOTASK_SPACE_GROUP ORA$AUTOTASK_SQL_GROUP ORA$AUTOTASK_STATS_GROUP ORA$AUTOTASK_URGENT_GROUP ORA$DIAGNOSTICS SYS_GROUP And, of course, I wonder what options I should pick.

  Read the article

• Application Stores, Developer Communities, Content, Games and Widgets: Strategic Market Review and O

  - by Manish Agrawal

  Sample of Alan's one day workshop given on Application Stores, Developer Communities, Content, Games and Widgets: Strategic Market Review and Operator Opportunity / Risk Analysis Thanks to Alan

  Read the article

• SQL SERVER – SQLServer Quiz 2011 – Do you know your execution plan – Two questions – One Answer

  - by pinaldave

  My friend Jacob Sebastian has SQL Server Quiz 2011 launched. This time when he asked me to come up with quiz question – I wanted to come up with something which is new and make participant to think about it. After carefully thinking I come with question which I really like to solve myself. Here is the details: 1) Using Single table only Once in Single SELECT statement generate execution plan which have JOIN operator. Explain the reason for the same. 2) Using Single table only Once in Single SELECT statement generate execution plan which have parallelism operator. Explain the reason for the same. Bonus: Create a single query which satisfy both of the above statement. To answer this question and win exciting gifts please visit the SQL Server Quiz website. Reference: Pinal Dave (http://blog.SQLAuthority.com)   Filed under: Pinal Dave, PostADay, Readers Contribution, Readers Question, SQL, SQL Authority, SQL Puzzle, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

  Read the article

• Graphics module: Am I going the right way?

  - by Paul

  I'm trying to write the graphics module of my engine. That is, this part of the code only provides an interface through which to load images, fonts, etc and draw them on the screen. It is also a wrapper for the library I'm using (SDL in this case). Here are the interfaces for my Image, Font and GraphicsRenderer classes. Please tell me if I'm going the right way. Image class Image { public: Image(); Image(const Image& other); Image(const char* file); ~Image(); bool load(const char* file); void free(); bool isLoaded() const; Image& operator=(const Image& other); private: friend class GraphicsRenderer; void* data_; }; Font class Font { public: Font(); Font(const Font& other); Font(const char* file, int ptsize); ~Font(); void load(const char* file, int ptsize); void free(); bool isLoaded() const; Font& operator=(const Font& other); private: friend class GraphicsRenderer; void* data_; }; GrapphicsRenderer class GraphicsRenderer { public: static GraphicsRenderer* Instance(); void blitImage(const Image& img, int x, int y); void blitText(const char* string, const Font& font, int x, int y); void render(); protected: GraphicsRenderer(); GraphicsRenderer(const GraphicsRenderer& other); GraphicsRenderer& operator=(const GraphicsRenderer& other); ~GraphicsRenderer(); private: void* screen_; bool initialize(); void finalize(); };

  Read the article

• array and array_view from amp.h

  - by Daniel Moth

  This is a very long post, but it also covers what are probably the classes (well, array_view at least) that you will use the most with C++ AMP, so I hope you enjoy it! Overview The concurrency::array and concurrency::array_view template classes represent multi-dimensional data of type T, of N dimensions, specified at compile time (and you can later access the number of dimensions via the rank property). If N is not specified, it is assumed that it is 1 (i.e. single-dimensional case). They are rectangular (not jagged). The difference between them is that array is a container of data, whereas array_view is a wrapper of a container of data. So in that respect, array behaves like an STL container, whereas the closest thing an array_view behaves like is an STL iterator (albeit with random access and allowing you to view more than one element at a time!). The data in the array (whether provided at creation time or added later) resides on an accelerator (which is specified at creation time either explicitly by the developer, or set to the default accelerator at creation time by the runtime) and is laid out contiguously in memory. The data provided to the array_view is not stored by/in the array_view, because the array_view is simply a view over the real source (which can reside on the CPU or other accelerator). The underlying data is copied on demand to wherever the array_view is accessed. Elements which differ by one in the least significant dimension of the array_view are adjacent in memory. array objects must be captured by reference into the lambda you pass to the parallel_for_each call, whereas array_view objects must be captured by value (into the lambda you pass to the parallel_for_each call). Creating array and array_view objects and relevant properties You can create array_view objects from other array_view objects of the same rank and element type (shallow copy, also possible via assignment operator) so they point to the same underlying data, and you can also create array_view objects over array objects of the same rank and element type e.g.   array_view<int,3> a(b); // b can be another array or array_view of ints with rank=3 Note: Unlike the constructors above which can be called anywhere, the ones in the rest of this section can only be called from CPU code. You can create array objects from other array objects of the same rank and element type (copy and move constructors) and from other array_view objects, e.g.   array<float,2> a(b); // b can be another array or array_view of floats with rank=2 To create an array from scratch, you need to at least specify an extent object, e.g. array<int,3> a(myExtent);. Note that instead of an explicit extent object, there are convenience overloads when N<=3 so you can specify 1-, 2-, 3- integers (dependent on the array's rank) and thus have the extent created for you under the covers. At any point, you can access the array's extent thought the extent property. The exact same thing applies to array_view (extent as constructor parameters, incl. convenience overloads, and property). While passing only an extent object to create an array is enough (it means that the array will be written to later), it is not enough for the array_view case which must always wrap over some other container (on which it relies for storage space and actual content). So in addition to the extent object (that describes the shape you'd like to be viewing/accessing that data through), to create an array_view from another container (e.g. std::vector) you must pass in the container itself (which must expose .data() and a .size() methods, e.g. like std::array does), e.g.   array_view<int,2> aaa(myExtent, myContainerOfInts); Similarly, you can create an array_view from a raw pointer of data plus an extent object. Back to the array case, to optionally initialize the array with data, you can pass an iterator pointing to the start (and optionally one pointing to the end of the source container) e.g.   array<double,1> a(5, myVector.begin(), myVector.end()); We saw that arrays are bound to an accelerator at creation time, so in case you don’t want the C++ AMP runtime to assign the array to the default accelerator, all array constructors have overloads that let you pass an accelerator_view object, which you can later access via the accelerator_view property. Note that at the point of initializing an array with data, a synchronous copy of the data takes place to the accelerator, and then to copy any data back we'll see that an explicit copy call is required. This does not happen with the array_view where copying is on demand... refresh and synchronize on array_view Note that in the previous section on constructors, unlike the array case, there was no overload that accepted an accelerator_view for array_view. That is because the array_view is simply a wrapper, so the allocation of the data has already taken place before you created the array_view. When you capture an array_view variable in your call to parallel_for_each, the copy of data between the non-CPU accelerator and the CPU takes place on demand (i.e. it is implicit, versus the explicit copy that has to happen with the array). There are some subtleties to the on-demand-copying that we cover next. The assumption when using an array_view is that you will continue to access the data through the array_view, and not through the original underlying source, e.g. the pointer to the data that you passed to the array_view's constructor. So if you modify the data through the array_view on the GPU, the original pointer on the CPU will not "know" that, unless one of two things happen: you access the data through the array_view on the CPU side, i.e. using indexing that we cover below you explicitly call the array_view's synchronize method on the CPU (this also gets called in the array_view's destructor for you) Conversely, if you make a change to the underlying data through the original source (e.g. the pointer), the array_view will not "know" about those changes, unless you call its refresh method. Finally, note that if you create an array_view of const T, then the data is copied to the accelerator on demand, but it does not get copied back, e.g.   array_view<const double, 5> myArrView(…); // myArrView will not get copied back from GPU There is also a similar mechanism to achieve the reverse, i.e. not to copy the data of an array_view to the GPU. copy_to, data, and global copy/copy_async functions Both array and array_view expose two copy_to overloads that allow copying them to another array, or to another array_view, and these operations can also be achieved with assignment (via the = operator overloads). Also both array and array_view expose a data method, to get a raw pointer to the underlying data of the array or array_view, e.g. float* f = myArr.data();. Note that for array_view, this only works when the rank is equal to 1, due to the data only being contiguous in one dimension as covered in the overview section. Finally, there are a bunch of global concurrency::copy functions returning void (and corresponding concurrency::copy_async functions returning a future) that allow copying between arrays and array_views and iterators etc. Just browse intellisense or amp.h directly for the full set. Note that for array, all copying described throughout this post is deep copying, as per other STL container expectations. You can never have two arrays point to the same data. indexing into array and array_view plus projection Reading or writing data elements of an array is only legal when the code executes on the same accelerator as where the array was bound to. In the array_view case, you can read/write on any accelerator, not just the one where the original data resides, and the data gets copied for you on demand. In both cases, the way you read and write individual elements is via indexing as described next. To access (or set the value of) an element, you can index into it by passing it an index object via the subscript operator. Furthermore, if the rank is 3 or less, you can use the function ( ) operator to pass integer values instead of having to use an index object. e.g. array<float,2> arr(someExtent, someIterator); //or array_view<float,2> arr(someExtent, someContainer); index<2> idx(5,4); float f1 = arr[idx]; float f2 = arr(5,4); //f2 ==f1 //and the reverse for assigning, e.g. arr(idx[0], 7) = 6.9; Note that for both array and array_view, regardless of rank, you can also pass a single integer to the subscript operator which results in a projection of the data, and (for both array and array_view) you get back an array_view of rank N-1 (or if the rank was 1, you get back just the element at that location). Not Covered In this already very long post, I am not going to cover three very cool methods (and related overloads) that both array and array_view expose: view_as, section, reinterpret_as. We'll revisit those at some point in the future, probably on the team blog. Comments about this post by Daniel Moth welcome at the original blog.

  Read the article

• Date Compare Validator Control ASP.NET

  - by Sahanr

  Compare two input dates to avoid invalid dates. In this example I have created two textboxes and namded as "TextBoxSeminarDate" and "TextBoxBookingDeadline". Booking deadline date must be before date to the Seminar date. Therefore I used Operator as "LesThanEqual". I have validated "TextBoxBookingDeadline" value comparing with the "TextBoxSeminarDate" value as follow.   <asp:CompareValidator ID="CompareValidatorBookingDeadline" runat="server" ControlToCompare="TextBoxSeminarDate" ControlToValidate="TextBoxBookingDeadline" Display="Dynamic" ErrorMessage="Please check the seminar date and select appropriate date for booking deadline" Operator="LessThanEqual" Type="Date"  ValueToCompare="<%= TextBoxSeminarDate.Text.ToShortString() %>">*</asp:CompareValidator> The important thing is "ValueToCompare" property of the compare validator. Here I have assined it to the value of the TextboxSeminarDate and then compered it with the booking deadline date.  

  Read the article

• Unable to install VMWare Workstation v8

  - by pst007x

  Installing VMware 8.0.2 64bit Ubuntu 12.04LTS 64bit BETA My Kernel version is: 3.2.0-20-generic pst007x@pst007x-Aspire-5741:~$ sudo sh VMware-Workstation-Full-8.0.2- 591240.x86_64.bundle Installs ok When I launch I am asked to install modules which are compiled and loaded into the running kernel. A window opens VMware Kernel Module Updater This fails on Virtual Network Device ERROR LOG. UPDATE: PATCH. When I try to add patch, following error: pst007x@pst007x-Aspire-5741:~$ sudo sh patch-modules_3.2.0.sh [sudo] password for pst007x: patch-modules_3.2.0.sh: 27: [: workstation8.0.2: unexpected operator patch-modules_3.2.0.sh: 28: [: workstation8.0.2: unexpected operator Sorry, this script is only for VMWare WorkStation 8.0.2 or VMWare Player 4.0.2. Exiting pst007x@pst007x-Aspire-5741:~$ I have fully un-installed, and re-installed. I am installing the correct version. Probably a problem with the patch. VMware installs perfectly on Ubuntu 11.10 This is how I uninstalled.

  Read the article

• Great Programmer Productivity - Accounting for 10,000 fold difference?

  - by TheImpact

  "A great lathe operator commands several times the wage of an average lathe operator, but a great writer of software code is worth 10,000 times the price of an average software writer." - Bill Gates Say there's a "great" software engineer and an "average" software engineer on the same team. How can you account for one engineer being 10,000 times more productive? I can't quite fathom this, given they're both taking on their share of features, bugs and investigations, and consistently deliver with quality. Would my description possibly justify them to be above "average"? "great"? In a corporation like Microsoft, what % of software engineers are "average"? What % "great"?

  Read the article

• Windows in StreamInsight: Hopping vs. Snapshot

  - by Roman Schindlauer

  Three weeks ago, we explained the basic concept of windows in StreamInsight: defining sets of events that serve as arguments for set-based operations, like aggregations. Today, we want to discuss the so-called Hopping Windows and compare them with Snapshot Windows. We will compare these two, because they can serve similar purposes with different behaviors; we will discuss the remaining window type, Count Windows, another time. Hopping (and its syntactic-sugar-sister Tumbling) windows are probably the most straightforward windowing concept in StreamInsight. A hopping window is defined by its length, and the offset from one window to the next. They are aligned with some absolute point on the timeline (which can also be given as a parameter to the window) and create sets of events. The diagram below shows an example of a hopping window with length of 1h and hop size (the offset) of 15 minutes, hence creating overlapping windows:   Two aspects in this diagram are important: Since this window is overlapping, an event can fall into more than one windows. If an (interval) event spans a window boundary, its lifetime will be clipped to the window, before it is passed to the set-based operation. That’s the default and currently only available window input policy. (This should only concern you if you are using a time-sensitive user-defined aggregate or operator.) The set-based operation will be applied to each of these sets, yielding a result. This result is: A single scalar value in case of built-in or user-defined aggregates. A subset of the input payloads, in case of the TopK operator. Arbitrary events, when using a user-defined operator. The timestamps of the result are almost always the ones of the windows. Only the user-defined  operator can create new events with timestamps. (However, even these event lifetimes are subject to the window’s output policy, which is currently always to clip to the window end.) Let’s assume we were calculating the sum over some payload field: var result = from window in source.HoppingWindow( TimeSpan.FromHours(1), TimeSpan.FromMinutes(15), HoppingWindowOutputPolicy.ClipToWindowEnd) select new { avg = window.Avg(e => e.Value) }; Now each window is reflected by one result event:   As you can see, the window definition defines the output frequency. No matter how many or few events we got from the input, this hopping window will produce one result every 15 minutes – except for those windows that do not contain any events at all, because StreamInsight window operations are empty-preserving (more about that another time). The “forced” output for every window can become a performance issue if you have a real-time query with many events in a wide group & apply – let me explain: imagine you have a lot of events that you group by and then aggregate within each group – classical streaming pattern. The hopping window produces a result in each group at exactly the same point in time for all groups, since the window boundaries are aligned with the timeline, not with the event timestamps. This means that the query output will become very bursty, delivering the results of all the groups at the same point in time. This becomes especially obvious if the events are long-lasting, spanning multiple windows each, so that the produced result events do not change their value very often. In such a case, a snapshot window can remedy. Snapshot windows are more difficult to explain than hopping windows: they represent those periods in time, when no event changes occur. In other words, if you mark all event start and and times on your timeline, then you are looking at all snapshot window boundaries:   If your events are never overlapping, the snapshot window will not make much sense. It is commonly used together with timestamp modification, which make it a very powerful tool. Or as Allan Mitchell expressed in in a recent tweet: “I used to look at SnapshotWindow() with disdain. Now she is my mistress, the one I turn to in times of trouble and need”. Let’s look at a simple example: I want to compute the average of some value in my events over the last minute. I don’t want this output be produced at fixed intervals, but at soon as it changes (that’s the true event-driven spirit!). The snapshot window will include all currently active event at each point in time, hence we need to extend our original events’ lifetimes into the future: Applying the Snapshot window on these events, it will appear to be “looking back into the past”: If you look at the result produced in this diagram, you can easily prove that, at each point in time, the current event value represents the average of all original input event within the last minute. Here is the LINQ representation of that query, applying the lifetime extension before the snapshot window: var result = from window in source .AlterEventDuration(e => TimeSpan.FromMinutes(1)) .SnapshotWindow(SnapshotWindowOutputPolicy.Clip) select new { avg = window.Avg(e => e.Value) }; With more complex modifications of the event lifetimes you can achieve many more query patterns. For instance “running totals” by keeping the event start times, but snapping their end times to some fixed time, like the end of the day. Each snapshot then “sees” all events that have happened in the respective time period so far. Regards, The StreamInsight Team

  Read the article

• Tomcat Manager Application and HTTP 404 Error

  - by David

  I am trying to set up the admin application for a Tomcat 6.0.24 instance. None of the searches I've done turn up anything I can use. I am using this configuration for Apache 2.2.14: Alias /manager /usr/share/tomcat6-admin/manager <Directory "/usr/share/tomcat6-admin/manager"> Options Indexes FollowSymLinks AllowOverride None allow from all </Directory> ProxyPass /manager ajp://localhost:8009/manager In the tomcat-users.xml I have this: <tomcat-users> <role rolename="tomcat"/> <role rolename="admin"/> <role rolename="operator"/> <role rolename="manager"/> <user username="admin" password="nopasswordforyou" roles="admin,tomcat,manager"/> <user username="operator" password="nevermind" roles="operator"/> </tomcat-users> I found the docs that suggested I needed manager-gui role installed and defined, but that appears to be Tomcat 7, not Tomcat 6. The manager.xml is the default provided with Ubuntu Lucid Lynx 10.04: <Context path="/manager" docBase="/usr/share/tomcat6-admin/manager" antiResourceLocking="false" privileged="true" /> If I access /manager from a web browser, I get a 404 error from Tomcat: "requested resource not available." If I access /manager/images I get the same thing. If I access /manager/401.jsp I get the actual page. In addition, the server.xml has not only the usual Realm (UserDatabaseRealm) but also one for MySQL authentication (JDBCRealm). Investigating this showed that the role of manager was not present there for the user admin; I fixed that by doing: INSERT USER_ROLE_DB SET USER_NAME='admin', ROLE_NAME='manager'; I restarted Tomcat, although I suspect that was overkill. No change. I don't see any errors in catalina.out or in localhost.* log files. What am I missing? What is the interaction between the different realms? How do I get the manager application working?

  Read the article

• What measures can be taken to increase Google indexing speed for a given newly created page?

  - by knorv

  Consider a website with a large number of pages. New pages are published regularly. When publishing a new page the website operator wants to get the newly created paged indexed in Google as soon as possible. The website operator wants to minimize the time spent between publication and indexing. Consider the site http://www.example.com/ with hundreds of thousands of pages. The page page http://www.example.com/something/important-page.html is created at say 12:00. How do I get important-page.html indexed as soon as possible after 12:00? Ideally within seconds or minutes. Or more generally: What options are available to try to get Google to index a specific newly created page as soon as possible?

  Read the article

• How to setup the c++ rule of three in a virtual base class

  - by Minion91

  I am trying to create a pure virtual base class (or simulated pure virtual) my goal: User can't create instances of BaseClass. Derived classes have to implement default constructor, copy constructor, copy assignment operator and destructor. My attempt: class Base { public: virtual ~Base() {}; /* some pure virtual functions */ private: Base() = default; Base(const Base& base) = default; Base& operator=(const Base& base) = default; } This gives some errors complaining that (for one) the copy constructor is private. But i don't want this mimicked constructor to be called. Can anyone give me the correct construction to do this if this is at all possible?

  Read the article

• How To Create Your Own Custom Google Search Engine

  - by Chris Hoffman

  Have you ever wanted to create a custom Google search engine that searches only specific websites? You can easily do this with Google’s Custom Search Engine tool. You can bookmark your search engine and even share it with other people. This trick works similarly to Google’s site: operator, but you won’t have to type the operator every time you search. It’s particularly useful if you want to search a large number of sites at once. How To Create a Customized Windows 7 Installation Disc With Integrated Updates How to Get Pro Features in Windows Home Versions with Third Party Tools HTG Explains: Is ReadyBoost Worth Using?

  Read the article

• What measures can be taken to make sure Google is aware of the existence of a newly created page?

  - by knorv

  Consider a website with a large number of pages. New pages are published regularly. When publishing a new page the website operator wants to get the newly created paged indexed in Google as soon as possible. The website operator wants to minimize the time spent between publication and indexing. Consider the site http://www.example.com/ with hundreds of thousands of pages. The page page http://www.example.com/something/important-page.html is created at say 12:00. I want to get important-page.html indexed as soon as possible after 12:00. Ideally within seconds or minutes. What options are available to try to get Google to index a specific newly created page as soon as possible?

  Read the article

• Deep Cloning C++ class that inherits CCNode in Cocos2dx

  - by A Devanney

  I stuck with something in Cocos2dx ... I'm trying to deep clone one of my classes that inherits CCNode. Basically i have.... GameItem* pTemp = new GameItem(*_actualItem); // loops through all the blocks in gameitem and updates their position pTemp->moveDown(); // if in boundary or collision etc... if (_gameBoard->isValidMove(pTemp)) { _actualItem = pTemp; // display the position CCLog("pos (1) --- (X : %d,Y : %d)", _actualItem->getGridX(),_actualItem->getGridY()); } Then doesn't work, because the gameitem inherits CCNode and has the collection of another class that also inherits CCNode. its just creating a shallow copy and when you look at children of the gameitem node in the copy, just point to the original? class GameItem : public CCNode { // maps to the actual grid position of the shape CCPoint* _rawPosition; // tracks the current grid position int _gridX, _gridY; // tracks the change if the item has moved CCPoint _offset; public: //constructors GameItem& operator=(const GameItem& item); GameItem(Shape shape); ... } then in the implementation.... GameItem& GameItem::operator=(const GameItem& item) { _gridX = item.getGridX(); _gridY = item.getGridY(); _offset = item.getOffSet(); _rawPosition = item.getRawPosition(); // how do i copy the node? return *this; } // shape contains an array of position for the game character GameItem::GameItem(Shape shape) { _rawPosition = shape.getShapePositions(); //loop through all blocks in position for (int i = 0; i < 7; i++) { // get the position of the first block in the shape and add to the position of the first block int x = (int) (getRawPosition()[i].x + getGridX()); int y = (int) (getRawPosition()[i].y + getGridY()); //instantiate a block with the position and type Block* block = Block::blockWithFile(x,y,(i+1), shape); // add the block to the this node this->addChild(block); } } And for clarity here is the block class class Block : public CCNode{ private: // using composition over inheritance CCSprite* _sprite; // tracks the current grid position int _gridX, _gridY; // used to store actual image number int _blockNo; public: Block(void); Block(int gridX, int gridY, int blockNo); Block& operator=(const Block& block); // static constructor for the creation of a block static Block* blockWithFile(int gridX, int gridY,int blockNo, Shape shape); ... } The blocks implementation..... Block& Block::operator=(const Block& block) { _sprite = new CCSprite(*block._sprite); _gridX = block._gridX; _gridY = block._gridY; _blockNo = block._blockNo; //again how to clone CCNode? return *this; } Block* Block::blockWithFile(int gridX, int gridY,int blockNo, Shape shape) { Block* block = new Block(); if (block && block->initBlockWithFile(gridX, gridY,blockNo, shape)) { block->autorelease(); return block; } CC_SAFE_DELETE(block); return NULL; } bool Block::initBlockWithFile(int gridX, int gridY,int blockNo, Shape shape) { setGridX(gridX); setGridY(gridY); setBlockNo(blockNo); const char* characterImg = helperFunctions::Format(shape.getFileName(),blockNo); // add to the spritesheet CCTexture2D* gameArtTexture = CCTextureCache::sharedTextureCache()->addImage("Character.pvr.ccz"); CCSpriteBatchNode::createWithTexture(gameArtTexture); // block settings _sprite = CCSprite::createWithSpriteFrameName(characterImg); // set the position of the block and add it to the layer this->setPosition(CONVERTGRIDTOACTUALPOS_X_Y(gridX,gridY)); this->addChild(_sprite); return true; } Any ideas are welcome at this point!! thanks

  Read the article

• Do you use i-->0 for backward loops?

  - by maaartinus

  Some people write for (int i=N; i-->0; ) doSomething(i); instead of for (int i=N-1; i>=0; --i) doSomething(i); for backward loops. The --> "operator"1 looks very confusing at the first glance, but it's trivial: i-->0 simply parses as (i--)>0, and once you get it, you see it immediately. The main disadvantage is the strange look. The advantage is that you'll get it always right (unlike the more verbose version offering the possibility to forget something, which really happened to me a couple of times). What do you think about using the --> "operator"? 1First time I saw the funny term in a comment to this question today.

  Read the article

• Hash Function Added To The PredicateEqualityComparer

  - by Paulo Morgado

  Sometime ago I wrote a predicate equality comparer to be used with LINQ’s Distinct operator. The Distinct operator uses an instance of an internal Set class to maintain the collection of distinct elements in the source collection which in turn checks the hash code of each element (by calling the GetHashCode method of the equality comparer) and only if there’s already an element with the same hash code in the collection calls the Equals method of the comparer to disambiguate. At the time I provided only the possibility to specify the comparison predicate, but, in some cases, comparing a hash code instead of calling the provided comparer predicate can be a significant performance improvement, I’ve added the possibility to had a hash function to the predicate equality comparer. You can get the updated code from the PauloMorgado.Linq project on CodePlex,

  Read the article

• Python: Improving long cumulative sum

  - by Bo102010

  I have a program that operates on a large set of experimental data. The data is stored as a list of objects that are instances of a class with the following attributes: time_point - the time of the sample cluster - the name of the cluster of nodes from which the sample was taken code - the name of the node from which the sample was taken qty1 = the value of the sample for the first quantity qty2 = the value of the sample for the second quantity I need to derive some values from the data set, grouped in three ways - once for the sample as a whole, once for each cluster of nodes, and once for each node. The values I need to derive depend on the (time sorted) cumulative sums of qty1 and qty2: the maximum value of the element-wise sum of the cumulative sums of qty1 and qty2, the time point at which that maximum value occurred, and the values of qty1 and qty2 at that time point. I came up with the following solution: dataset.sort(key=operator.attrgetter('time_point')) # For the whole set sys_qty1 = 0 sys_qty2 = 0 sys_combo = 0 sys_max = 0 # For the cluster grouping cluster_qty1 = defaultdict(int) cluster_qty2 = defaultdict(int) cluster_combo = defaultdict(int) cluster_max = defaultdict(int) cluster_peak = defaultdict(int) # For the node grouping node_qty1 = defaultdict(int) node_qty2 = defaultdict(int) node_combo = defaultdict(int) node_max = defaultdict(int) node_peak = defaultdict(int) for t in dataset: # For the whole system ###################################################### sys_qty1 += t.qty1 sys_qty2 += t.qty2 sys_combo = sys_qty1 + sys_qty2 if sys_combo > sys_max: sys_max = sys_combo # The Peak class is to record the time point and the cumulative quantities system_peak = Peak(time_point=t.time_point, qty1=sys_qty1, qty2=sys_qty2) # For the cluster grouping ################################################## cluster_qty1[t.cluster] += t.qty1 cluster_qty2[t.cluster] += t.qty2 cluster_combo[t.cluster] = cluster_qty1[t.cluster] + cluster_qty2[t.cluster] if cluster_combo[t.cluster] > cluster_max[t.cluster]: cluster_max[t.cluster] = cluster_combo[t.cluster] cluster_peak[t.cluster] = Peak(time_point=t.time_point, qty1=cluster_qty1[t.cluster], qty2=cluster_qty2[t.cluster]) # For the node grouping ##################################################### node_qty1[t.node] += t.qty1 node_qty2[t.node] += t.qty2 node_combo[t.node] = node_qty1[t.node] + node_qty2[t.node] if node_combo[t.node] > node_max[t.node]: node_max[t.node] = node_combo[t.node] node_peak[t.node] = Peak(time_point=t.time_point, qty1=node_qty1[t.node], qty2=node_qty2[t.node]) This produces the correct output, but I'm wondering if it can be made more readable/Pythonic, and/or faster/more scalable. The above is attractive in that it only loops through the (large) dataset once, but unattractive in that I've essentially copied/pasted three copies of the same algorithm. To avoid the copy/paste issues of the above, I tried this also: def find_peaks(level, dataset): def grouping(object, attr_name): if attr_name == 'system': return attr_name else: return object.__dict__[attrname] cuml_qty1 = defaultdict(int) cuml_qty2 = defaultdict(int) cuml_combo = defaultdict(int) level_max = defaultdict(int) level_peak = defaultdict(int) for t in dataset: cuml_qty1[grouping(t, level)] += t.qty1 cuml_qty2[grouping(t, level)] += t.qty2 cuml_combo[grouping(t, level)] = (cuml_qty1[grouping(t, level)] + cuml_qty2[grouping(t, level)]) if cuml_combo[grouping(t, level)] > level_max[grouping(t, level)]: level_max[grouping(t, level)] = cuml_combo[grouping(t, level)] level_peak[grouping(t, level)] = Peak(time_point=t.time_point, qty1=node_qty1[grouping(t, level)], qty2=node_qty2[grouping(t, level)]) return level_peak system_peak = find_peaks('system', dataset) cluster_peak = find_peaks('cluster', dataset) node_peak = find_peaks('node', dataset) For the (non-grouped) system-level calculations, I also came up with this, which is pretty: dataset.sort(key=operator.attrgetter('time_point')) def cuml_sum(seq): rseq = [] t = 0 for i in seq: t += i rseq.append(t) return rseq time_get = operator.attrgetter('time_point') q1_get = operator.attrgetter('qty1') q2_get = operator.attrgetter('qty2') timeline = [time_get(t) for t in dataset] cuml_qty1 = cuml_sum([q1_get(t) for t in dataset]) cuml_qty2 = cuml_sum([q2_get(t) for t in dataset]) cuml_combo = [q1 + q2 for q1, q2 in zip(cuml_qty1, cuml_qty2)] combo_max = max(cuml_combo) time_max = timeline.index(combo_max) q1_at_max = cuml_qty1.index(time_max) q2_at_max = cuml_qty2.index(time_max) However, despite this version's cool use of list comprehensions and zip(), it loops through the dataset three times just for the system-level calculations, and I can't think of a good way to do the cluster-level and node-level calaculations without doing something slow like: timeline = defaultdict(int) cuml_qty1 = defaultdict(int) #...etc. for c in cluster_list: timeline[c] = [time_get(t) for t in dataset if t.cluster == c] cuml_qty1[c] = [q1_get(t) for t in dataset if t.cluster == c] #...etc. Does anyone here at Stack Overflow have suggestions for improvements? The first snippet above runs well for my initial dataset (on the order of a million records), but later datasets will have more records and clusters/nodes, so scalability is a concern. This is my first non-trivial use of Python, and I want to make sure I'm taking proper advantage of the language (this is replacing a very convoluted set of SQL queries, and earlier versions of the Python version were essentially very ineffecient straight transalations of what that did). I don't normally do much programming, so I may be missing something elementary. Many thanks!

  Read the article

• Partial string search in boost::multi_index_container

  - by user361699

  I have a struct to store info about persons and multi_index_contaider to store such objects struct person { std::string m_first_name; std::string m_last_name; std::string m_third_name; std::string m_address; std::string m_phone; person(); person(std::string f, std::string l, std::string t = "", std::string a = DEFAULT_ADDRESS, std::string p = DEFAULT_PHONE) : m_first_name(f), m_last_name(l), m_third_name(t), m_address(a), m_phone(p) {} }; typedef multi_index_container , ordered_non_unique, member, member persons_set; operator< and operator<< implementation for person bool operator<(const person &lhs, const person &rhs) { if(lhs.m_last_name == rhs.m_last_name) { if(lhs.m_first_name == rhs.m_first_name) return (lhs.m_third_name < rhs.m_third_name); return (lhs.m_first_name < rhs.m_first_name); } return (lhs.m_last_name < rhs.m_last_name); } std::ostream& operator<<(std::ostream &s, const person &rhs) { s << "Person's last name: " << rhs.m_last_name << std::endl; s << "Person's name: " << rhs.m_first_name << std::endl; if (!rhs.m_third_name.empty()) s << "Person's third name: " << rhs.m_third_name << std::endl; s << "Phone: " << rhs.m_phone << std::endl; s << "Address: " << rhs.m_address << std::endl; return s; } Add several persons into container: person ("Alex", "Johnson", "Somename"); person ("Alex", "Goodspeed"); person ("Petr", "Parker"); person ("Petr", "Goodspeed"); Now I want to find person by lastname (the first member of the second index in multi_index_container) persons_set::nth_index<1::type &names_index = my_set.get<1(); std::pair::type::const_iterator, persons_set::nth_index<1::type::const_iterator n_it = names_index.equal_range("Goodspeed"); std::copy(n_it.first ,n_it.second, std::ostream_iterator(std::cout)); It works great. Both 'Goodspeed' persons are found. Now lets try to find person by a part of a last name: std::pair::type::const_iterator, persons_set::nth_index<1::type::const_iterator n_it = names_index.equal_range("Good"); std::copy(n_it.first ,n_it.second, std::ostream_iterator(std::cout)); This returns nothing, but partial string search works as a charm in std::set. So I can't realize what's the problem. I only wraped strings by a struct. May be operator< implementation? Thanks in advance for any help.

  Read the article

• VHDL - Problem with std_logic_vector

  - by wretrOvian

  Hi, i'm coding a 4-bit binary adder with accumulator: library ieee; use ieee.std_logic_1164.all; entity binadder is port(n,clk,sh:in bit; x,y:inout std_logic_vector(3 downto 0); co:inout bit; done:out bit); end binadder; architecture binadder of binadder is signal state: integer range 0 to 3; signal sum,cin:bit; begin sum<= (x(0) xor y(0)) xor cin; co<= (x(0) and y(0)) or (y(0) and cin) or (x(0) and cin); process begin wait until clk='0'; case state is when 0=> if(n='1') then state<=1; end if; when 1|2|3=> if(sh='1') then x<= sum & x(3 downto 1); y<= y(0) & y(3 downto 1); cin<=co; end if; if(state=3) then state<=0; end if; end case; end process; done<='1' when state=3 else '0'; end binadder; The output : -- Compiling architecture binadder of binadder ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(15): No feasible entries for infix operator "xor". ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(15): Type error resolving infix expression "xor" as type std.standard.bit. ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(16): No feasible entries for infix operator "and". ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(16): Bad expression in right operand of infix expression "or". ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(16): No feasible entries for infix operator "and". ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(16): Bad expression in left operand of infix expression "or". ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(16): Bad expression in right operand of infix expression "or". ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(16): Type error resolving infix expression "or" as type std.standard.bit. ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(28): No feasible entries for infix operator "&". ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(28): Type error resolving infix expression "&" as type ieee.std_logic_1164.std_logic_vector. ** Error: C:/Modeltech_pe_edu_6.5a/examples/binadder.vhdl(39): VHDL Compiler exiting I believe i'm not handling std_logic_vector's correctly. Please tell me how? :(

  Read the article

• Using 32 bit g++ to build 64bit binaries on AIX

  - by Thumbeti

  I am trying to build a 64 bit binary from C++ code using 32bit g++ compiler. I am getting the following errors while building: ============================================================================= => /usr/local/bin/g++ -shared -maix64 -fPIC -Wl,-bM:SRE -Wl,-bnoentry -Wl,-bE:gcc_shr_lib.so.exp -o gcc_shr_lib.so gcc_shr_lib.o -L/usr/local/lib ld: 0711-319 WARNING: Exported symbol not defined: gcc_whereAmI ld: 0711-317 ERROR: Undefined symbol: typeinfo for std::bad_alloc ld: 0711-317 ERROR: Undefined symbol: __gxx_personality_v0 ld: 0711-317 ERROR: Undefined symbol: vtable for std::exception ld: 0711-317 ERROR: Undefined symbol: vtable for std::bad_alloc ld: 0711-317 ERROR: Undefined symbol: .std::ios_base::Init::Init() ld: 0711-317 ERROR: Undefined symbol: .std::ios_base::Init::~Init() ld: 0711-317 ERROR: Undefined symbol: .operator new(unsigned long) ld: 0711-317 ERROR: Undefined symbol: .operator delete(void*) ld: 0711-317 ERROR: Undefined symbol: ._Unwind_Resume ld: 0711-317 ERROR: Undefined symbol: .__cxa_get_exception_ptr ld: 0711-317 ERROR: Undefined symbol: .__cxa_begin_catch ld: 0711-317 ERROR: Undefined symbol: std::cout ld: 0711-317 ERROR: Undefined symbol: .std::basic_ostream<char, std::char_traits<char> >& std::operator<< <std::char_traits<char> >(std::basic_ostream<char, std::char_traits<char> >&, char const*) ld: 0711-317 ERROR: Undefined symbol: std::basic_ostream<char, std::char_traits<char> >& std::endl<char, std::char_traits<char> >(std::basic_ostream<char, std::char_traits<char> >&) ld: 0711-317 ERROR: Undefined symbol: .std::basic_ostream<char, std::char_traits<char> >::operator<<(std::basic_ostream<char, std::char_traits<char> >& (*)(std::basic_ostream<char, std::char_traits<char> >&)) ld: 0711-317 ERROR: Undefined symbol: .std::bad_alloc::~bad_alloc() ld: 0711-317 ERROR: Undefined symbol: .__cxa_end_catch ld: 0711-317 ERROR: Undefined symbol: .__register_frame_info_table ld: 0711-317 ERROR: Undefined symbol: .__deregister_frame_info ld: 0711-345 Use the -bloadmap or -bnoquiet option to obtain more information. collect2: ld returned 8 exit status ============================================================================= It seems I need 64bit libstdc++ available on my build system. Could you please throw some light to solve this. Q1) Is it ok to build 64 bit binaries using 32 bit g++ compiler on AIX 5.2 Q2) Where should I get 64 bit libstdc++? Will this 64 bit libstdc++ work with 32bit g++ compiler?

  Read the article

• build error with boost spirit grammar (boost 1.43 and g++ 4.4.1) part II

  - by lurscher

  I'm having issues getting a small spirit/qi grammar to compile. i am using boost 1.43 and g++ 4.4.1. the input grammar header: inputGrammar.h #include <boost/config/warning_disable.hpp> #include <boost/spirit/include/qi.hpp> #include <boost/spirit/include/phoenix_core.hpp> #include <boost/spirit/include/phoenix_operator.hpp> #include <boost/spirit/include/phoenix_fusion.hpp> #include <boost/spirit/include/phoenix_stl.hpp> #include <boost/fusion/include/adapt_struct.hpp> #include <boost/variant/recursive_variant.hpp> #include <boost/foreach.hpp> #include <iostream> #include <fstream> #include <string> #include <vector> namespace sp = boost::spirit; namespace qi = boost::spirit::qi; using namespace boost::spirit::ascii; //using namespace boost::spirit::arg_names; namespace fusion = boost::fusion; namespace phoenix = boost::phoenix; using phoenix::at_c; using phoenix::push_back; template< typename Iterator , typename ExpressionAST > struct InputGrammar : qi::grammar<Iterator, ExpressionAST(), space_type> { InputGrammar() : InputGrammar::base_type( block ) { tag = sp::lexeme[+(alpha) [sp::_val += sp::_1]];//[+(char_ - '<') [_val += _1]]; block = sp::lit("block") [ at_c<0>(sp::_val) = sp::_1] >> "(" >> *instruction[ push_back( at_c<1>(sp::_val) , sp::_1 ) ] >> ")"; command = tag [ at_c<0>(sp::_val) = sp::_1] >> "(" >> *instruction [ push_back( at_c<1>(sp::_val) , sp::_1 )] >> ")"; instruction = ( command | tag ) [sp::_val = sp::_1]; } qi::rule< Iterator , std::string() , space_type > tag; qi::rule< Iterator , ExpressionAST() , space_type > block; qi::rule< Iterator , ExpressionAST() , space_type > function_def; qi::rule< Iterator , ExpressionAST() , space_type > command; qi::rule< Iterator , ExpressionAST() , space_type > instruction; }; the test build program: #include <iostream> #include <string> #include <vector> using namespace std; //my grammar #include <InputGrammar.h> struct MockExpressionNode { std::string name; std::vector< MockExpressionNode > operands; typedef std::vector< MockExpressionNode >::iterator iterator; typedef std::vector< MockExpressionNode >::const_iterator const_iterator; iterator begin() { return operands.begin(); } const_iterator begin() const { return operands.begin(); } iterator end() { return operands.end(); } const_iterator end() const { return operands.end(); } bool is_leaf() const { return ( operands.begin() == operands.end() ); } }; BOOST_FUSION_ADAPT_STRUCT( MockExpressionNode, (std::string, name) (std::vector<MockExpressionNode>, operands) ) int const tabsize = 4; void tab(int indent) { for (int i = 0; i < indent; ++i) std::cout << ' '; } template< typename ExpressionNode > struct ExpressionNodePrinter { ExpressionNodePrinter(int indent = 0) : indent(indent) { } void operator()(ExpressionNode const& node) const { cout << " tag: " << node.name << endl; for (int i=0 ; i < node.operands.size() ; i++ ) { tab( indent ); cout << " arg "<<i<<": "; ExpressionNodePrinter(indent + 2)( node.operands[i]); cout << endl; } } int indent; }; int test() { MockExpressionNode root; InputGrammar< string::const_iterator , MockExpressionNode > g; std::string litA = "litA"; std::string litB = "litB"; std::string litC = "litC"; std::string litD = "litD"; std::string litE = "litE"; std::string litF = "litF"; std::string source = litA+"( "+litB+" ,"+litC+" , "+ litD+" ( "+litE+", "+litF+" ) "+ " )"; string::const_iterator iter = source.begin(); string::const_iterator end = source.end(); bool r = qi::phrase_parse( iter , end , g , space , root ); ExpressionNodePrinter< MockExpressionNode > np; np( root ); }; int main() { test(); } finally, the build error is the following: (the full error trace is 20 times bigger than the allowed size for a stackoverflow question, so i posted the full version of it at http://codepad.org/Q74IVCUc) /usr/bin/make -f nbproject/Makefile-linux_amd64_devel.mk SUBPROJECTS= .build-conf make[1]: se ingresa al directorio `/home/mineq/NetBeansProjects/InputParserTests' /usr/bin/make -f nbproject/Makefile-linux_amd64_devel.mk dist/linux_amd64_devel/GNU-Linux-x86/vpuinputparsertests make[2]: se ingresa al directorio `/home/mineq/NetBeansProjects/InputParserTests' mkdir -p build/linux_amd64_devel/GNU-Linux-x86 rm -f build/linux_amd64_devel/GNU-Linux-x86/tests_main.o.d g++ `llvm-config --cxxflags` `pkg-config --cflags unittest-cpp` `pkg-config --cflags boost-1.43` `pkg-config --cflags boost-coroutines` -c -g -I../InputParser -MMD -MP -MF build/linux_amd64_devel/GNU-Linux-x86/tests_main.o.d -o build/linux_amd64_devel/GNU-Linux-x86/tests_main.o tests_main.cpp from /home/mineq/third_party/boost_1_43_0/boost/spirit/include/phoenix_operator.hpp:11, from ../InputParser/InputGrammar.h:14, from tests_main.cpp:14: /home/mineq/third_party/boost_1_43_0/boost/spirit/home/phoenix/operator/self.hpp: In instantiation of ‘const int boost::phoenix::result_of_assign<MockExpressionNode&, boost::variant<MockExpressionNode, std::basic_string<char, std::char_traits<char>, std::allocator<char> >, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_>&>::size’: In file included from /home/mineq/third_party/boost_1_43_0/boost/spirit/home/phoenix/operator.hpp:16, /home/mineq/third_party/boost_1_43_0/boost/spirit/home/phoenix/operator/self.hpp:27: instantiated from ‘const int boost::phoenix::result_of_assign<MockExpressionNode&, boost::variant<MockExpressionNode, std::basic_string<char, std::char_traits<char>, std::allocator<char> >, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_>&>::index’ /home/mineq/third_party/boost_1_43_0/boost/spirit/home/phoenix/operator/self.hpp:27: instantiated from ‘boost::phoenix::result_of_assign<MockExpressionNode&, boost::variant<MockExpressionNode, std::basic_string<char, std::char_traits<char>, std::allocator<char> >, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_>&>’ /home/mineq/third_party/boost_1_43_0/boost/mpl/eval_if.hpp:38: instantiated from ‘boost::mpl::eval_if<boost::mpl::or_<boost::phoenix::is_actor<MockExpressionNode&>, boost::phoenix::is_actor<boost::variant<MockExpressionNode, std::basic_string<char, std::char_traits<char>, std::allocator<char> >, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_>&>, mpl_::bool_<false>, mpl_::bool_<false>, mpl_::bool_<false> >, boost::phoenix::re_curry<boost::phoenix::assign_eval, MockExpressionNode&, boost::variant<MockExpressionNode, std::basic_string<char, std::char_traits<char>, std::allocator<char> >, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_>&, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_>, boost::phoenix::result_of_assign<MockExpressionNode&, boost::variant<MockExpressionNode, std::basic_string<char, std::char_traits<char>, std::allocator<char> >, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_>&> >’ /home/mineq/third_party/boost_1_43_0/boost/spirit/home/phoenix/operator/self.hpp:69: instantiated from ‘boost::phoenix::assign_eval::result<boost::phoenix::basic_environment<boost::fusion::vector1<boost::variant<MockExpressionNode, std::basic_string<char, std::char_traits<char>, std::allocator<char> >, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_>&>, boost::spirit::context<boost::fusion::cons<MockExpressionNode&, boost::fusion::nil>, boost::fusion::vector0<void> >, bool, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_>, boost::spirit::attribute<0>, boost::spirit::argument<0> >’ /home/mineq/third_party/boost_1_43_0/boost/spirit/home/phoenix/core/detail/composite_eval.hpp:89: instantiated from ‘boost::phoenix::detail::composite_eval<2>::result<boost::phoenix::composite<boost::phoenix::assign_eval, boost::fusion::vector<boost::spirit::attribute<0>, boost::spirit::argument<0>, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_> >, boost::phoenix::basic_environment<boost::fusion::vector1<boost::variant<MockExpressionNode, std::basic_string<char, std::char_traits<char>, std::allocator<char> >, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_>&>, boost::spirit::context<boost::fusion::cons<MockExpressionNode&, boost::fusion::nil>, boost::fusion::vector0<void> >, bool, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_> >’ /home/mineq/third_party/boost_1_43_0/boost/spirit/home/phoenix/core/composite.hpp:61: instantiated from ‘boost::phoenix::composite<boost::phoenix::assign_eval, boost::fusion::vector<boost::spirit::attribute<0>, boost::spirit::argument<0>, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_> >::result<boost::phoenix::basic_environment<boost::fusion::vector1<boost::variant<MockExpressionNode, std::basic_string<char, std::char_traits<char>, std::allocator<char> >, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_>&>, boost::spirit::context<boost::fusion::cons<MockExpressionNode&, boost::fusion::nil>, boost::fusion::vector0<void> >, bool, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_> >’ /home/mineq/third_party/boost_1_43_0/boost/spirit/home/phoenix/core/actor.hpp:56: instantiated from ‘boost::phoenix::eval_result<boost::phoenix::composite<boost::phoenix::assign_eval, boost::fusion::vector<boost::spirit::attribute<0>, boost::spirit::argument<0>, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_> >, boost::phoenix::basic_environment<boost::fusion::vector1<boost::variant<MockExpressionNode, std::basic_string<char, std::char_traits<char>, std::allocator<char> >, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_>&>, boost::spirit::context<boost::fusion::cons<MockExpressionNode&, boost::fusion::nil>, boost::fusion::vector0<void> >, bool, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_> >’ /home/mineq/third_party/boost_1_43_0/boost/spirit/home/phoenix/core/actor.hpp:65: instantiated from ‘boost::phoenix::actor<boost::phoenix::composite<boost::phoenix::assign_eval, boost::fusion::vector<boost::spirit::attribute<0>, boost::spirit::argument<0>, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_> > >::result<boost::phoenix::actor<boost::phoenix::composite<boost::phoenix::assign_eval, boost::fusion::vector<boost::spirit::attribute<0>, boost::spirit::argument<0>, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_> > >(boost::fusion::vector1<boost::variant<MockExpressionNode, std::basic_string<char, std::char_traits<char>, std::allocator<char> >, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_>&>&, boost::spirit::context<boost::fusion::cons<MockExpressionNode&, boost::fusion::nil>, boost::fusion::vector0<void> >&, bool&)>’ /home/mineq/third_party/boost_1_43_0/boost/spirit/home/support/action_dispatch.hpp:44: instantiated from ‘bool boost::spirit::traits::action_dispatch<Component>::operator()(const boost::phoenix::actor<Eval>&, Attribute&, Context&) [with Eval = boost::phoenix::composite<boost::phoenix::assign_eval, boost::fusion::vector<boost::spirit::attribute<0>, boost::spirit::argument<0>, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_> >, Attribute = boost::variant<MockExpressionNode, std::basic_string<char, std::char_traits<char>, std::allocator<char> >, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_>, Context = boost::spirit::context<boost::fusion::cons<MockExpressionNode&, boost::fusion::nil>, boost::fusion::vector0<void> >, Component = boost::spirit::qi::alternative<boost::fusion::cons<boost::spirit::qi::reference<const boost::spirit::qi::rule<__gnu_cxx::__normal_iterator<const char*, std::basic_string<char, std::char_traits<char>, std::allocator<char> > >, MockExpressionNode(), boost::proto::exprns_::expr<boost::proto::tag::terminal, boost::proto::argsns_::term<boost::spirit::tag::char_code<boost::spirit::tag::space, boost::spirit::char_encoding::ascii> >, 0l>, boost::fusion::unused_type, boost::fusion::unused_type> >, boost::fusion::cons<boost::spirit::qi::reference<const boost::spirit::qi::rule<__gnu_cxx::__normal_iterator<const char*, std::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::string(), boost::proto::exprns_::expr<boost::proto::tag::terminal, boost::proto::argsns_::term<boost::spirit::tag::char_code<boost::spirit::tag::space, boost::spirit::char_encoding::ascii> >, 0l>, boost::fusion::unused_type, boost::fusion::unused_type> >, boost::fusion::nil> > >]’ /home/mineq/third_party/boost_1_43_0/boost/spirit/home/qi/action/action.hpp:62: instantiated from ‘bool boost::spirit::qi::action<Subject, Action>::parse(Iterator&, const Iterator&, Context&, const Skipper&, Attribute&) const [with Iterator = __gnu_cxx::__normal_iterator<const char*, std::basic_string<char, std::char_traits<char>, std::allocator<char> > >, Context = boost::spirit::context<boost::fusion::cons<MockExpressionNode&, boost::fusion::nil>, boost::fusion::vector0<void> >, Skipper = boost::spirit::qi::char_class<boost::spirit::tag::char_code<boost::spirit::tag::space, boost::spirit::char_encoding::ascii> >, Attribute = const boost::fusion::unused_type, Subject = boost::spirit::qi::alternative<boost::fusion::cons<boost::spirit::qi::reference<const boost::spirit::qi::rule<__gnu_cxx::__normal_iterator<const char*, std::basic_string<char, std::char_traits<char>, std::allocator<char> > >, MockExpressionNode(), boost::proto::exprns_::expr<boost::proto::tag::terminal, boost::proto::argsns_::term<boost::spirit::tag::char_code<boost::spirit::tag::space, boost::spirit::char_encoding::ascii> >, 0l>, boost::fusion::unused_type, boost::fusion::unused_type> >, boost::fusion::cons<boost::spirit::qi::reference<const boost::spirit::qi::rule<__gnu_cxx::__normal_iterator<const char*, std::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::string(), boost::proto::exprns_::expr<boost::proto::tag::terminal, boost::proto::argsns_::term<boost::spirit::tag::char_code<boost::spirit::tag::space, boost::spirit::char_encoding::ascii> >, 0l>, boost::fusion::unused_type, boost::fusion::unused_type> >, boost::fusion::nil> > >, Action = boost::phoenix::actor<boost::phoenix::composite<boost::phoenix::assign_eval, boost::fusion::vector<boost::spirit::attribute<0>, boost::spirit::argument<0>, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_> > >]’ /home/mineq/third_party/boost_1_43_0/boost/spirit/home/qi/nonterminal/detail/parser_binder.hpp:33: instantiated from ‘bool boost::spirit::qi::detail::parser_binder<Parser, Auto>::call(Iterator&, const Iterator&, Context&, const Skipper&, mpl_::true_) const [with Iterator = __gnu_cxx::__normal_iterator<const char*, std::basic_string<char, std::char_traits<char>, std::allocator<char> > >, Skipper = boost::spirit::qi::char_class<boost::spirit::tag::char_code<boost::spirit::tag::space, boost::spirit::char_encoding::ascii> >, Context = boost::spirit::context<boost::fusion::cons<MockExpressionNode&, boost::fusion::nil>, boost::fusion::vector0<void> >, Parser = boost::spirit::qi::action<boost::spirit::qi::alternative<boost::fusion::cons<boost::spirit::qi::reference<const boost::spirit::qi::rule<__gnu_cxx::__normal_iterator<const char*, std::basic_string<char, std::char_traits<char>, std::allocator<char> > >, MockExpressionNode(), boost::proto::exprns_::expr<boost::proto::tag::terminal, boost::proto::argsns_::term<boost::spirit::tag::char_code<boost::spirit::tag::space, boost::spirit::char_encoding::ascii> >, 0l>, boost::fusion::unused_type, boost::fusion::unused_type> >, boost::fusion::cons<boost::spirit::qi::reference<const boost::spirit::qi::rule<__gnu_cxx::__normal_iterator<const char*, std::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::string(), boost::proto::exprns_::expr<boost::proto::tag::terminal, boost::proto::argsns_::term<boost::spirit::tag::char_code<boost::spirit::tag::space, boost::spirit::char_encoding::ascii> >, 0l>, boost::fusion::unused_type, boost::fusion::unused_type> >, boost::fusion::nil> > >, boost::phoenix::actor<boost::phoenix::composite<boost::phoenix::assign_eval, boost::fusion::vector<boost::spirit::attribute<0>, boost::spirit::argument<0>, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_, boost::fusion::void_> > > >, Auto = mpl_::bool_<false>]’ /home/mineq/third_party/boost_1_43_0/boost/spirit/home/qi/nonterminal/detail/parser_binder.hpp:53: instantiated from ‘bool boost::spirit::qi::detail::parser_binder<Parser, Auto>::operator()(Iterator&, const Iterator&, Context&, const Skipper&) const [with Iterator = __gnu_cxx::__normal_iterator<const char*, std::basic_string<char, std::char_traits<char>, std::allocator<char> > >, Skipper = boost::spirit::qi::char_class<boost::spirit::tag::char_code<boost::spirit::tag::space, boost::spirit::char_encoding::ascii> >, Context = boost::spirit::context<boost::fusion::cons<MockExpressionNode&, boost::fusion::nil>, boost::fusion::vector0<void> >, Parser = boost::spirit::qi::action<boost::spirit::qi::alternative<boost::fusion::cons<boost::spirit::qi::reference<const boost::spirit::qi::rule<__gnu_cxx::__normal_iterator<const char*, std::basic_string<char, std::char_traits<char>, std::allocator<char> > >, MockExpressionNode(), boost::proto::exprns_::expr<boost::proto::tag::terminal, boost::proto::argsns_::term<boost::spirit::tag::char_code<boost::spirit::tag::space, boost::spirit::char_encoding::ascii> >, 0l>, boost::fusion::unused_type, boost::fusion::unused_type> >, boost::fusion::cons<boost::spirit::qi::reference<const boost::spirit::qi::rule<__gnu_cxx::__normal_iterator<const char*, std::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::string(), boost::proto::exprns_::expr<boost::proto::tag::terminal, boost::proto::argsns_::term<boost::spirit::tag::char_code<boost::spirit::tag::space, boost::spirit::char_encoding::ascii> >, 0l>, boost::fusion::unused_type, boost::fusion::unused_type> >, boost::fusion::nil> > >, ... ... more errors but i had to truncate to fit the 30k limit make[2]: *** [build/linux_amd64_devel/GNU-Linux-x86/tests_main.o] Error 1 make[2]: se sale del directorio `/home/mineq/NetBeansProjects/InputParserTests' make[1]: *** [.build-conf] Error 2 make[1]: se sale del directorio `/home/mineq/NetBeansProjects/InputParserTests' make: *** [.build-impl] Error 2 BUILD FAILED (exit value 2, total time: 2m 13s)

  Read the article

< Previous Page | 36 37 38 39 40 41 42 43 44 45 46 47  | Next Page >