The sampling error for unweighted subgroups is larger: for the 1, registered voters, the sampling error is ±4. For the sampling errors of additional subgroups, please see the table at the end of this section. Sampling error is only one type of error to which surveys are subject. Results may also be affected by factors such as question wording, question order, and survey timing.

We present results for five geographic regions, accounting for approximately 90 percent of the state population. Residents of other geographic areas are included in the results reported for all adults, registered voters, and likely voters, but sample sizes for these less-populous areas are not large enough to report separately. We also present results for congressional districts currently held by Democrats or Republicans, based on residential zip code and party of the local US House member.

We compare the opinions of those who report they are registered Democrats, registered Republicans, and no party preference or decline-to-state or independent voters; the results for those who say they are registered to vote in other parties are not large enough for separate analysis. We also analyze the responses of likely voters—so designated per their responses to survey questions about voter registration, previous election participation, intentions to vote this year, attention to election news, and current interest in politics.

The percentages presented in the report tables and in the questionnaire may not add to due to rounding. Additional details about our methodology can be found at www. pdf and are available upon request through surveys ppic. October 14—23, 1, California adult residents; 1, California likely voters English, Spanish. Margin of error ±3. Percentages may not add up to due to rounding.

Overall, do you approve or disapprove of the way that Gavin Newsom is handling his job as governor of California? Overall, do you approve or disapprove of the way that the California Legislature is handling its job? Do you think things in California are generally going in the right direction or the wrong direction? Thinking about your own personal finances—would you say that you and your family are financially better off, worse off, or just about the same as a year ago?

Next, some people are registered to vote and others are not. Are you absolutely certain that you are registered to vote in California? Are you registered as a Democrat, a Republican, another party, or are you registered as a decline-to-state or independent voter? Would you call yourself a strong Republican or not a very strong Republican? Do you think of yourself as closer to the Republican Party or Democratic Party? Which one of the seven state propositions on the November 8 ballot are you most interested in?

Initiative Constitutional Amendment and Statute. It allows in-person sports betting at racetracks and tribal casinos, and requires that racetracks and casinos that offer sports betting to make certain payments to the state—such as to support state regulatory costs.

The fiscal impact is increased state revenues, possibly reaching tens of millions of dollars annually. Some of these revenues would support increased state regulatory and enforcement costs that could reach the low tens of millions of dollars annually. If the election were held today, would you vote yes or no on Proposition 26? Initiative Constitutional Amendment. It allows Indian tribes and affiliated businesses to operate online and mobile sports wagering outside tribal lands.

It directs revenues to regulatory costs, homelessness programs, and nonparticipating tribes. Some revenues would support state regulatory costs, possibly reaching the mid-tens of millions of dollars annually. If the election were held today, would you vote yes or no on Proposition 27? Initiative Statute. It allocates tax revenues to zero-emission vehicle purchase incentives, vehicle charging stations, and wildfire prevention.

If the election were held today, would you vote yes or no on Proposition 30? Do you agree or disagree with these statements? Overall, do you approve or disapprove of the way that Joe Biden is handling his job as president? Overall, do you approve or disapprove of the way Alex Padilla is handling his job as US Senator?

Overall, do you approve or disapprove of the way Dianne Feinstein is handling her job as US Senator? Overall, do you approve or disapprove of the way the US Congress is handling its job? Do you think things in the United States are generally going in the right direction or the wrong direction? How satisfied are you with the way democracy is working in the United States? Are you very satisfied, somewhat satisfied, not too satisfied, or not at all satisfied? These days, do you feel [rotate] [1] optimistic [or] [2] pessimistic that Americans of different political views can still come together and work out their differences?

What is your opinion with regard to race relations in the United States today? Would you say things are [rotate 1 and 2] [1] better , [2] worse , or about the same than they were a year ago? When it comes to racial discrimination, which do you think is the bigger problem for the country today—[rotate] [1] People seeing racial discrimination where it really does NOT exist [or] [2] People NOT seeing racial discrimination where it really DOES exist?

Next, Next, would you consider yourself to be politically: [read list, rotate order top to bottom]. Generally speaking, how much interest would you say you have in politics—a great deal, a fair amount, only a little, or none? Mark Baldassare is president and CEO of the Public Policy Institute of California, where he holds the Arjay and Frances Fearing Miller Chair in Public Policy.

He is a leading expert on public opinion and survey methodology, and has directed the PPIC Statewide Survey since He is an authority on elections, voter behavior, and political and fiscal reform, and the author of ten books and numerous publications.

Before joining PPIC, he was a professor of urban and regional planning in the School of Social Ecology at the University of California, Irvine, where he held the Johnson Chair in Civic Governance. He has conducted surveys for the Los Angeles Times , the San Francisco Chronicle , and the California Business Roundtable.

He holds a PhD in sociology from the University of California, Berkeley. Dean Bonner is associate survey director and research fellow at PPIC, where he coauthors the PPIC Statewide Survey—a large-scale public opinion project designed to develop an in-depth profile of the social, economic, and political attitudes at work in California elections and policymaking. He has expertise in public opinion and survey research, political attitudes and participation, and voting behavior.

Before joining PPIC, he taught political science at Tulane University and was a research associate at the University of New Orleans Survey Research Center. He holds a PhD and MA in political science from the University of New Orleans.

Rachel Lawler is a survey analyst at the Public Policy Institute of California, where she works with the statewide survey team. In that role, she led and contributed to a variety of quantitative and qualitative studies for both government and corporate clients. She holds an MA in American politics and foreign policy from the University College Dublin and a BA in political science from Chapman University. Deja Thomas is a survey analyst at the Public Policy Institute of California, where she works with the statewide survey team.

Prior to joining PPIC, she was a research assistant with the social and demographic trends team at the Pew Research Center. In that role, she contributed to a variety of national quantitative and qualitative survey studies. She holds a BA in psychology from the University of Hawaiʻi at Mānoa. This survey was supported with funding from the Arjay and Frances F. Ruben Barrales Senior Vice President, External Relations Wells Fargo. Mollyann Brodie Executive Vice President and Chief Operating Officer Henry J.

Kaiser Family Foundation. Bruce E. Cain Director Bill Lane Center for the American West Stanford University. Jon Cohen Chief Research Officer and Senior Vice President, Strategic Partnerships and Business Development Momentive-AI. Joshua J. Dyck Co-Director Center for Public Opinion University of Massachusetts, Lowell. Lisa García Bedolla Vice Provost for Graduate Studies and Dean of the Graduate Division University of California, Berkeley.

Russell Hancock President and CEO Joint Venture Silicon Valley. Sherry Bebitch Jeffe Professor Sol Price School of Public Policy University of Southern California. Carol S. Larson President Emeritus The David and Lucile Packard Foundation. Lisa Pitney Vice President of Government Relations The Walt Disney Company. Robert K. Ross, MD President and CEO The California Endowment. Most Reverend Jaime Soto Bishop of Sacramento Roman Catholic Diocese of Sacramento.

Helen Iris Torres CEO Hispanas Organized for Political Equality. David C. Wilson, PhD Dean and Professor Richard and Rhoda Goldman School of Public Policy University of California, Berkeley.

Chet Hewitt, Chair President and CEO Sierra Health Foundation. Mark Baldassare President and CEO Public Policy Institute of California. Ophelia Basgal Affiliate Terner Center for Housing Innovation University of California, Berkeley. Louise Henry Bryson Chair Emerita, Board of Trustees J. Paul Getty Trust. Sandra Celedon President and CEO Fresno Building Healthy Communities. Marisa Chun Judge, Superior Court of California, County of San Francisco. Steven A. Leon E. Panetta Chairman The Panetta Institute for Public Policy.

Cassandra Walker Pye President Lucas Public Affairs. Gaddi H. Vasquez Retired Senior Vice President, Government Affairs Edison International Southern California Edison.

The Public Policy Institute of California is dedicated to informing and improving public policy in California through independent, objective, nonpartisan research. PPIC is a public charity. It does not take or support positions on any ballot measures or on any local, state, or federal legislation, nor does it endorse, support, or oppose any political parties or candidates for public office.

Short sections of text, not to exceed three paragraphs, may be quoted without written permission provided that full attribution is given to the source. Research publications reflect the views of the authors and do not necessarily reflect the views of our funders or of the staff, officers, advisory councils, or board of directors of the Public Policy Institute of California.

This website uses cookies to analyze site traffic and to allow users to complete forms on the site. PPIC does not share, trade, sell, or otherwise disclose personal information. PPIC Water Policy Center. PPIC Statewide Survey. PPIC Higher Education Center. People Our Team Board of Directors Statewide Leadership Council Adjunct Fellows.

Support Ways to Give Our Contributors. In this case, the attempt to write the tree fails, and the original data is may also be corrupted. In addition, adding a branch to a tree enlarges the tree and increases the amount of memory needed to read an entry, and therefore decreases the performance.

For these reasons, ROOT offers the concept of friends for trees and chains. We encourage you to use TTree::AddFriend rather than adding a branch manually. A tree keeps a list of friends. In the context of a tree or a chain , friendship means unrestricted access to the friends data.

In this way it is much like adding another branch to the tree without taking the risk of damaging it. To add a friend to the list, you can use the TTree::AddFriend method. The TTree tree below has two friends ft1 and ft2 and now has access to the variables a,b,c,i,j,k,l and m. The AddFriend method has two parameters, the first is the tree name and the second is the name of the ROOT file where the friend tree is saved.

AddFriend automatically opens the friend file. If no file name is given, the tree called ft1 is assumed to be in the same file as the original tree. If the friend tree has the same name as the original tree, you can give it an alias in the context of the friendship:. To specify which tree to use in the Draw method, use the syntax:. The picture illustrates the access of the tree and its friends with a Draw command.

When AddFriend is called, the ROOT file is automatically opened and the friend tree ft1 header is read into memory.

The new friend ft1 is added to the list of friends of tree. The number of entries in the friend must be equal or greater to the number of entries of the original tree. If the friend tree has fewer entries, a warning is given and the missing entries are not included in the histogram. When the tree is written to file TTree::Write , the friends list is saved with it.

Moreover, when the tree is retrieved, the trees on the friends list are also retrieved and the friendship restored. When a tree is deleted, the elements of the friend list are also deleted. It is possible to declare a friend tree that has the same internal structure same branches and leaves as the original tree, and compare the same values by specifying the tree.

cxx and where Event objects are saved in a tree. Event is a descendent of TObject. As such it inherits the data members of TObject and its methods such as Dump and Inspect and Write.

In addition, because it inherits from TObject it can be a member of a collection. To summarize, the advantages of inheriting from a TObject are:. Below is the list of the Event data members. It contains a character array, several integers, a floating-point number, and an EventHeader object.

The EventHeader class is described in the following paragraph. Event also has two pointers, one to a TClonesArray of tracks and one to a histogram. The EventHeader class also defined in Event. h does not inherit from TObject. Beginning with ROOT 3. In previous releases branches were restricted to objects inheriting from the TObject. However, it has always been possible to write a class not inheriting from TObject to a tree by encapsulating it in a TObject descending class as is the case in EventHeader and Event.

The Track class descends from TObject since tracks are in a TClonesArray i. a ROOT collection class and contains a selection of basic types and an array of vertices. Its TObject inheritance enables Track to be in a collection and in Event is a TClonesArray of Tracks. We create a simple tree with two branches both holding Event objects. One is split and the other is not. We also create a pointer to an Event object event.

First, we check if the shared library with the class definitions is loaded. If not we load it. Then we read two branches, one for the number of tracks and one for the entire event. We check the number of tracks first, and if it meets our condition, we read the entire event. We show the fist entry that meets the condition. You can see the two branches in the tree in the left panel: the event branch is split and hence expands when clicked on.

The other branch event not split is not expandable and we can not browse the data members. The TClonesArray of tracks fTracks is also split because we set the split level to 2. It shows the first entry with more than tracks:. The method TTree::ReadFile can be used to automatic define the structure of the TTree and read the data from a formatted ascii file. Creates or simply read branches from the file named whose name is passed in 'filename'.

Otherwise branchDescriptor must be specified with the above syntax. A TBranch object is created for each variable in the expression. The total number of rows read from the file is returned. The methods TTree::Draw , TTree::MakeClass and TTree::MakeSelector are available for data analysis using trees. The TTree::Draw method is a powerful yet simple way to look and draw the trees contents.

It enables you to plot a variable a leaf with just one line of code. However, the Draw method falls short once you want to look at each entry and design more sophisticated acceptance criteria for your analysis. For these cases, you can use TTree::MakeClass. It creates a class that loops over the trees entries one by one. You can then expand it to do the logic of your analysis. The TTree::MakeSelector is the recommended method for ROOT data analysis.

It is especially important for large data set in a parallel processing configuration where the analysis is distributed over several processors and you can specify which entries to send to each processor.

With MakeClass the user has control over the event loop, with MakeSelector the tree is in control of the event loop. We will use the tree in cernstaff. Cling allows us to get simply the object by using it. To show the different Draw options, we create a canvas with four sub-pads. We will use one sub-pad for each Draw command. As you can see, the last call TTree::Draw has only one parameter.

It is a string containing the leaf name. A histogram is automatically created as a result of a TTree::Draw. The style of the histogram is inherited from the TTree attributes and the current style gStyle is ignored. The TTree gets its attributes from the current TStyle at the time it was created. You can call the method TTree::UseCurrentStyle to change to the current style rather than the TTree style. This signature still only has one parameter, but it now has two dimensions separated by a colon "x:y".

The item to be plotted can be an expression not just a simple variable. A list of examples follows this introduction. This will draw the Cost vs. The value of the selection is used as a weight when filling the histogram. If the expression includes only Boolean operations as in the example above, the result is 0 or 1. If the result is 0, the histogram is not filled. In general, the expression is:. If the Boolean expression evaluates to true, the histogram is filled with a weight.

If the weight is not explicitly specified it is assumed to be 1. For example, this selection will add 1 to the histogram if x is less than y and the square root of z is less than 3. The Draw method has its own parser, and it only looks in the current tree for variables.

This means that any variable used in the selection must be defined in the tree. You cannot use an arbitrary global variable in the TTree::Draw method. The TTree::Draw method also accepts TCutG objects. A TCut is a specialized string object used for TTree selections.

A TCut object has a name and a title. It does not have any data members in addition to what it inherits from TNamed. It only adds a set of operators to do logical string concatenation.

For example, assume:. The TTree::Draw method creates a histogram called htemp and puts it on the active pad. In a batch program, the histogram htemp created by default, is reachable from the current pad.

If you pipe the result of the TTree::Draw into a histogram, the histogram is also available in the current directory. You can do:. The draw options are the same as for THDraw. In addition to the draw options defined in TH1 , there are three more.

The 'prof' and 'profs' draw a profile histogram TProfile rather than a regular 2D histogram TH2D from an expression with two variables. If the expression has three variables, a TProfile2D is generated. You can combine the draw options in a list separated by commas.

After typing the lines above, you should now have a canvas that looks this. It does not paint the object on the screen. Since nothing has been painted in the pad yet, the pad limits have not been computed. There are two more optional parameters to the TTree::Draw method: one is the number of entries and the second one is the entry to start with.

For example, this command draws entries starting with entry The examples below use the Event. The commands have been tested on the split-levels 0, 1, and 9. Each command is numbered and referenced by the explanations immediately following the examples. It fills the histogram with the number of tracks for each entry.

fNtrack is a member of event. Same as case 1, but use the method of event to get the number of tracks. When using a method, you can include parameters for the method as long as the parameters are literals.

Same as case 2, the object of the method is not specified. The command uses the first instance of the GetNtrack method found in the objects stored in the tree. We recommend using this shortcut only if the method name is unique. Draw the data member of a data member.

In the tree, each entry has a histogram. This command draws the maximum value of the X-axis for each histogram. Use data members in the expression and in the selection parameter to plot fPx or all tracks in every 10th entry. Since fTracks is a TClonesArray of Tracks , there will be d values of fPx for each entry. When the index of the array is left out or when empty brackets are used [] , all values of the array are selected.

Draw all values of fMatrix for each entry in the tree. Four elements of fMatrix are used: fMatrix[1][0] , fMatrix[2][0] , fMatrix[3][0] , fMatrix[4][0]. Four elements of fMatrix are used: fMatrix[1][0] , fMatrix[1][2] , fMatrix[1][3] , fMatrix[1][4]. With two arrays and unspecified element numbers, the number of selected values is the minimum of the first dimension times the minimum of the second dimension.

In this case fVertex is also a two dimensional array since it is a data member of the tracks array. fMatrix has 4 x 4 elements. This case, draws 4 the smaller of fNtrack and 4 times 3 the smaller of 4 and 3 , meaning 12 elements per entry.

The selected values for each entry are:. The first dimension minimum is 2, and the second dimension minimum is 3 from fVertex. Three values are selected from each entry:.

This is the same as case The first dimension minimum is 4 from fMatrix , and the second dimension minimum is 3 from fVertex. Twelve values are selected from each entry. This command selects all elements, but the number per entry depends on the number of vertices of that entry.

Only one per entry is selected. This command shows the use of a mathematical expression. It draws the square root of the sum of the product. The formula can contains call to a function that takes numerical arguments and returns a numerical value.

The function needs to be declared to the dictionary and need to be available from the global namespace. In particular, global functions and public static member functions can be called. To compare strings, you can also use strstr. The size of the array fPoints varies with each track of each event.

This command draws all the value in the fPoints arrays. When fAvgPoints is a data member of the Event class, this example selects:.

Where max0 , max1 , max n , is the size of the fPoints array for the respective track. For each event and each track, this expression is selected. It is the difference between fPoints and of fVertex. The number of elements used for each track is the minimum of fNpoint and 3 the size of the fVertex array. The selection argument is used as a weight. The expression returns a multiplier and in case of a Boolean the multiplier is either 0 for false or 1 for true.

The first command draws fPx for the range between with conditions on fBx and fBy , the second command draws fPx for the same conditions, but adds a weight using the result of the second expression. When using arrays in the selection and the expression, the selection is applied to each element of the array. When using a specific element for a variable length array the entries with fewer elements are ignored. Thus these two commands are equivalent. The axis will have the Nation values.

fTriggerBits is a data member of TTrack of type TBits. Objects of class TBits can be drawn directly. This command will create a 1D histogram from 0 to nbits which is filled for each non-null bit-number. Assuming that fClosestDistance is a smaller array than fMatrix. This example draws a 2D plot with, for all entries, fClosestDistance[i]:i for each value of i between 0 and the size of fClosestDistance. TRef and TRefArray are automatically deferenced and this shows the value of the fPx of the track referenced by fLastTrack.

This auto dereferencing can be extended via an implementation of TVirtualRefProxy to any reference type. You can also call any TTree methods.

TString and std::string object are plotted directly. The example 45 draws the same results - i. You can plot plot objects of any class which has either AsDouble or AsString AsDouble has priority.

For such a class for example TTimeStamp , the line 46 will plot the same as:. They use the human ability to spot un-symmetry. Variables are represented on individual axes displayed along a circle. Spider plots are not suitable for an accurate graph reading since, by their nature, it can be difficult to read out very detailed values, but they give quickly a global view of an event in order to compare it with the others. In ROOT the spider plot facility is accessed from the tree viewer GUI.

The variables to be visualized are selected in the tree viewer and can be scanned using the spider plot button. The Parallel Coordinates Plots are a common way of studying and visualizing multiple variables data sets. They were proposed by in A. Inselberg in as a new way to represent multi-dimensional information. In traditional Cartesian coordinates, axes are mutually perpendicular. In Parallel coordinates, all axes are parallel which allows representing data in much more than three dimensions.

To show a set of points in Parallel Coordinates, a set of parallel lines is drawn, typically vertical and equally spaced. A point in n-dimensional space is represented as a polyline with vertices on the parallel axes. The position of the vertex on the i-th axis corresponds to the i-th coordinate of the point.

The three following figures show some very simple examples:. The Parallel Coordinates technique is good at: spotting irregular events, seeing the data trend, finding correlations and clusters. Its main weakness is the cluttering of the output.

If the events are plotted as solid lines and no special techniques are used to clarify the picture, the result is the previous picture which is very cluttered and useless.

To improve the readability of the Parallel Coordinates output and to explore interactively the data set, many techniques are available. We have implemented a few in ROOT.

First of all, in order to show better where the clusters on the various axes are, a 1D histogram is associated to each axis.

These histograms one per axis are filled according to the number of lines passing through the bins. These histograms can be represented which colors get from a palette according to the bin contents or as bar charts.

Both representations can be cumulated on the same plot. This technique allows seeing clearly where the clusters are on an individual axis but it does not give any hints about the correlations between the axes. Avery simple technique allows to make the clusters appearing: Instead of painting solid lines we paint dotted lines.

The cluttering of each individual line is reduced and the clusters show clearly as we can see on the next figure. The spacing between the dots is a parameter which can be adjusted in order to get the best results.

Interactivity is a very important aspect of the Parallel Coordinates plots. To really explore the data set it is essential to act directly with the events and the axes. For instance, changing the axes order may show clusters which were not visible in a different order. On the next figure the axes order has been changed interactively. Having moved the variables u,v,w after the variables x,y,z the correlation between these two sets of variables is clear also.

To pursue further data sets exploration we have implemented the possibility to define selections interactively. A selection is a set of ranges combined together.

Within a selection, ranges along the same axis are combined with logical OR, and ranges on different axes with logical AND. A selection is displayed on top of the complete data set using its own color.

Only the events fulfilling the selection criteria ranges are displayed. Ranges are defined interactively using cursors, like on the first axis on the figure. Several selections can be defined at the same time, each selection having its own color.

Several selections can been defined. Each cluster is now clearly visible and the zone with crossing clusters is now understandable whereas, without any selection or with only a single one, it was not easy to understand.

Interactive selections on Parallel Coordinates are a powerful tool because they can be defined graphically on many variables graphical cuts in ROOT can be defined on two variables only which allow a very accurate events filtering.

Such selection to filter one single event on a scatter plot would be much more difficult. Once a selection has been defined, it is possible to use it to generate a TEntryList which is applied on the tree and used at drawing time. Another technique has been implemented in order to show clusters when the picture is cluttered.

A weight is assigned to each event. The events having the bigger weights are those belonging to clusters. It is possible to paint only the events having a weight above a given value and the clusters appear. Only the events with a weight greater than 50 are displayed.

In case only a few events are displayed, drawing them as smooth curves instead of straight lines helps to differentiate them. Interactivity and therefore the Graphical User Interface are very important to manipulate the Parallel Coordinates plots.

The ROOT framework allows to easily implement the direct interactions on the graphical area and the graphical editor facility provides dedicated GUI. Transparency is very useful with parallel coordinates plots. It allows to show clearly the clusters.

It was invented in by John Tukey. The five numbers are:. will print the values of var1 , var2 and var3. A selection can be applied in the second argument:. will print the values of var1 , var2 and var3 for the entries where var1 is exactly 0. TTree::Scan returns the number of entries passing the selection. By default 50 rows are shown before TTree::Scan pauses and ask you to press the Enter key to see the next 50 rows.

If maxrows is set to 0 all rows of the Tree are shown. This option is interesting when dumping the contents of a Tree to an ascii file, eg from the command line:. Arrays within an entry are printed in their linear forms. If several arrays with multiple dimensions are printed together, they will NOT be synchronized. For example, with a tree containing arr1[4][2] and arr2[2][3] ,.

However, if there is a selection criterium which is an array, then all the formulas will be synchronized with the selection criterium see TTree::Draw for more information. If this options is not specified, the default column size is 9.

will print 3 columns, the first 2 columns will be 30 characters long, the third columns will be 20 characters long. The TTree::Draw method can also be used to build a list of the entries. As a result, a TEventList or a TEntryList object is created in the current directory. For example, to create a TEventList of all entries with more than tracks, do:.

This list contains the entry number of all entries with more than tracks. To see the entry numbers use the Print "all" command. For example to add the entries, with exactly tracks:. This command does not add any new entries to the list because all entries with more than tracks have already been found by the previous command for entries with more than tracks.

The functionality is essentially the same: both are used to store entry numbers. TEntryList , however, uses considerably less memory for storage, and is optimized for both very high and very low selectivity of cuts see TEntryListBlock class description for the details of internal storage.

Unlike the TEventList , TEntryList makes a distinction between indices from a TChain and from a TTree. While a TEntryList for a TTree can be seen as just a list of numbers, a TEntryList for a TChain is a collection of TEntryList s for the TTree s that constitute this TChain.

and then be used to construct a new TEntryList for a new TChain , or processed independently as normal TEntryList s for TTree s. This modularity makes TEntryList much better suited for PROOF processing than the TEventList. A TEventList or a TEntryList can be used to limit the TTree to the events in the list.

The methods SetEventList and SetEntryList tell the tree to use the list and hence limit all subsequent calls to Draw , Scan , Process , Query , Principal and CopyTree methods to the entries in the list.

In general, it affects the GetEntryNumber method and all functions using it for looping over the tree entries. The GetEntry and GetEntries methods are not affected. Note, that in the SetEventList method, the TEventList argument is internally transformed into a TEntryList , and this operation, in case of a TChain , requires loading of all the tree headers. In this example, we create a list with all entries with more than tracks and then set it so that the tree will use this list.

To reset the TTree to use all events use SetEventList 0 or SetEntryList 0. If you have entry lists that were created using different cuts, you can combine the lists to get a new list, with entries passing at least one of the cuts. list1 now contains entries with more than or less than tracks. Check this by calling:. You can also subtract TEntryList from each other, so that the first list contains only the entries, passing the selection of the first list and not present in the second list.

To add some individual entries, use TEntryList::Enter function. To see if the entry is in the list, use TEntryList::Contains. Remember, that all operation in a TEntryList for a TChain are on the TTree level. This is illustrated by the following example:. The result is a TEntryList for a TChain of tree1 and tree2. If the second list was for the same TTree in the same file as the first list, the result would be as follows:. This is a special kind of TEntryList , used only when processing TChain objects see the method TChain::SetEntryListFile.

It is used in the case, when the entry lists, corresponding to the trees of this chain, are stored in separate files. It allows to load the entry lists in memory one by one, keeping only the list for the currently processed tree loaded. The TTree::Draw method can also be used to fill a specific histogram.

The syntax is:. As we can see, this created a TH1 , called myHisto. If you want to append more entries to the histogram, you can use this syntax:. If you do not create a histogram ahead of time, ROOT will create one at the time of the Draw command as is the case above.

If you would like to draw the variable into a specific histogram where you, for example, set the range and bin number, you can define the histogram ahead of time and use it in the Draw command.

The histogram has to be in the same directory as the tree. When you project a TTree into a histogram, the histogram inherits the TTree attributes and not the current style attributes.

This allows you to project two Trees with different attributes into the same picture. You can call the method TTree::UseCurrentStyle to change the histogram to use the current style gStyle. See "Graphics and the Graphical User Interface. The binning of the newly created histogram can be specified in two ways. You can set a default in the. To set number of bins default for the 1-D, 2-D, 3-D histograms can be specified in the. rootrc file via the environment variables, e.

To set the number of bins for a specific histogram when using TTree::Draw, add up to nine numbers following the histogram name. The numbers meaning is:. When a bin number is specified, the value becomes the default. Any of the numbers can be skipped. If you would like to fill a histogram, but not draw it you can use the TTree::Project method. The prof option is automatically selected when the output is redirected into a TProfile. Once we have drawn a tree, we can get information about the tree.

These are the methods used to get information from a drawn tree TTree :. GetSelectedRows : Returns the number of entries accepted by the selection expression. In case where no selection was specified, it returns the number of entries processed. GetW : Returns a pointer to the float array of Weights where the weight equals the result of the selection expression.

To read the drawn values of fNtrack into an array, and loop through the entries follow the lines below. First, open the file and draw the fNtrack variable:. Then declare a pointer to a float and use the GetV1 method to retrieve the first dimension of the tree.

In this example we only drew one dimension fNtrack if we had drawn two, we could use GetV2 to get the second one. By default, TTree::Draw creates these arrays with fEstimate words where fEstimate can be set via TTree::SetEstimate.

If you have more entries than fEstimate only the first fEstimate selected entries will be stored in the arrays. The arrays are used as buffers. When fEstimate entries have been processed, ROOT scans the buffers to compute the minimum and maximum of each coordinate and creates the corresponding histograms.

You can use these lines to read all entries into these arrays:. Obviously, this will not work if the number of entries is very large. This technique is useful in several cases, for example if you want to draw a graph connecting all the x , y or z points.

Note that you may have a tree or chain with 1 billion entries, but only a few may survive the cuts and will fit without problems in these arrays. The TTree::Draw method is convenient and easy to use; however it falls short if you need to do some programming with the variable.

For example, for plotting the masses of all oppositely changed pairs of tracks, you would need to write a program that loops over all events, finds all pairs of tracks, and calculates the required quantities. We have shown how to retrieve the data arrays from the branches of the tree in the previous section, and you could just write that program from scratch.

Since this is a very common task, ROOT provides a utility that generates a skeleton class designed to loop over the entries of the tree.

This is the TTree::MakeClass method. We will now go through the steps of using MakeClass with a simplified example. The methods used here obviously work for complex event loop calculations.

These are our assumptions: we would like to do selective plotting and loop through each entry of the tree and tracks. We chose a simple example: we want to plot fPx of the first tracks of each entry. Execute Event and instruct it to split the object with this command from the UNIX command line. The person who designed the tree makes a shared library available to you, which defines the classes needed. In this case, the classes are Event, EventHeader , and Track and they are defined in the shared library libEvent.

The designer also gives you the Event. h file to see the definition of the classes. You can locate Event. If you have already built it, you can now use it again. From the output of print we can see that the tree has one branch for each data member of Event , Track , and EventHeader.

MakeClass takes one parameter, a string containing the name of the class to be made. Cling informs us that it has created two files. h contains the class definition and MyClass. C contains the MyClass::Loop method. MyClass has more methods than just Loop. The other methods are a constructor, a destructor, GetEntry , LoadTree , Notify , Cut and Show. The implementations of these methods are in the. h file. This division of methods was done intentionally.

C file is kept as short as possible, and contains only code that is intended for you to customize. h file contains all the other methods. It is clear that you want to be as independent as possible of the header file i. h generated by MakeClass.

The solution is to implement a derived class, for example MyRealClass deriving from MyClass such that a change in your Tree or regeneration of MyClass. h does not force you to change MyRealClass. You can imagine deriving several classes from MyClass. h , each with a specific algorithm. h and the class declaration:.

We can see data members in the generated class. The first data member is fChain. Once this class is instantiated, fChain will point to the original tree or chain this class was made from. If the class is instantiated with a tree as a parameter to the constructor, fChain will point to the tree named in the parameter. Its role is only relevant when we have multiple trees chained together in a TChain.

The class definition shows us that this tree has one branch and one leaf per data member. The methods of MyClass are:. If you pass a tree, MyClass will use it rather than the tree from which it was created. It associates each branch with the corresponding leaf data member. Once you have executed GetEntry , the leaf data members in MyClass are set to the values of the entry.

For example, GetEntry 12 loads the 13th event into the event data member of MyClass note that the first entry is 0. GetEntry returns the number of bytes read from the file. In this case GetEntry returns 1. It does not return 0, because many people assume a return of 0 means an error has occurred while reading.

LoadTree will load the tree containing the specified entry from a chain of trees. Notify is called by LoadTree to adjust the branch addresses. void Loop - it is the skeleton method that loops through each entry of the tree. This is interesting to us, because we will need to customize it for our analysis.

MyClass::Loop consists of a for-loop calling GetEntry for each entry. In the template, the numbers of bytes are added up, but it does nothing else. If we were to execute it now, there would be no output. At the beginning of the file are instructions about reading selected branches. They are not reprinted here, but please read them from your own file.

Let us continue with the goal of going through the first tracks of each entry and plot Px. To do this we change the Loop method. In the for-loop, we need to add another for-loop to go over all the tracks. In the outer for-loop, we get the entry and the number of tracks. In the inner for-loop, we fill the large histogram myHisto with all tracks and the small histogram smallHisto with the track if it is in the first Save these changes to MyClass.

C and start a fresh root session. We will now load MyClass and experiment with its methods. The first step is to load the library and the class file. Then we can instantiate a MyClass object. Now we can get a specific entry and populate the event leaf. In the code snipped below, we get entry 0, and print the number of tracks Then we get entry 1 and print the number of tracks With a TTree we can make a selector and use it to process a limited set of entries.

This is especially important in a parallel processing configuration where the analysis is distributed over several processors and we can specify which entries to send to each processor. The TTree::Process method is used to specify the selector and the entries. Before we can use TTree::Process we need to make a selector. We can call the TTree::MakeSelector method. It creates two files similar to TTree::MakeClass. In the resulting files is a class that is a descendent of TSelector and implements the following methods:.

TSelector::Begin - this method is called every time a loop over the tree starts. This is a convenient place to create your histograms. TSelector::Notify - it is called at the first entry of a new tree in a chain. TSelector::Process - it is called to process an event. Once the entry is in memory one can apply a selection and if the event is selected histograms can be filled. Processing stops when this function returns kFALSE.

It combines the methods TSelector::ProcessCut and TSelector ::ProcessFill in one, avoiding the necessity to maintain the state in the class to communicate between these two functions. It reduces the information that needs to be shared between them and promotes a more granular data access by reading branches as they are needed. TSelector::Terminate - it is called at the end of a loop on a TTree.

This is a convenient place to draw and fit your histograms. TSelector::Version - this function provides backward compatibility for old versions and support for the future upgrades.

The TSelector , unlike the resulting class from MakeClass , separates the processing into a ProcessCut and ProcessFill , so we can limit reading of branches to the ones we need. When a selector is used with a TChain in methods Process , ProcessFill , ProcessCut , you must use the pointer to the current TTree to call the method GetEntry entry. The parameter entry is always the local entry number in the current tree.

Assuming that fChain is the pointer to the TChain being processed, use. Where T is the TTree and MySelector is the name of created class and the name of the. h and. C files. The resulting TSelector is the argument to TTree::Process.

The argument can be the file name or a pointer to the selector object. This call will interpret the class defined in MySelector. C and process entries beginning with entry When it is called again, it recompiles only if the macro MySelector. C has changed since it was compiled last. If not, it loads the existing library. The next example shows how to create a selector with a pointer:. TTree::Process is aware of PROOF, ROOT parallel processing facility.

If PROOF is setup, it divides the processing amongst the slave CPUs. The next graphs show the two columns on the right which represent the split and non-split TClonesArray , are significantly lower than the vectors. The most significant difference is in reading a file without compression. The file size with compression, write times with and without compression and the read times with and without compression all favor the TClonesArray.

This benchmark illustrates the pros and cons of the compression option. The data file contains a TTree. The program was invoked with:. The Total Time is the real time in seconds to run the program. The program Event generates in average tracks per event. Each track has 17 data members. The read benchmark runs in the interactive version of ROOT. We did not correct this time for the overhead coming from the interpreter itself.

Welcome to Mocha, tracking and rotoscoping tools that make your tracking and rotoscoping work much easier. Our tools are based on our proprietary Planar Tracking technology, an awesome approach to 2D tracking which will help you to generate accurate corner-pins and track and transform your roto splines in a powerful way.

Tracking and rotoscoping are part of almost any visual effects project. For 2D tracking, point trackers are most commonly used, but to get good point tracks requires a mix of experience and luck.

If the point being tracked exits frame, you get into offset tracking, which presents its own set of challenges. If it all fails, you are into hand tracking, which is time consuming and very hard to get accurate. Mocha is a 2D tracker that requires less experience and luck to be successful with, does not require the image to be primed and is less likely to require a lot of tricks or hand tracking on difficult shots.

In Mocha splines are used for both tracking and rotoscoping. This is a different method from standard 1-point or multi-point tracking tools. This is itself a difficult task, especially when tracking a shot that was not originally designed to be tracked. If you wish to also track rotation, perspective and shear you need even more clear and consistent points to track.

Even when using multi-point trackers to impart rotation and scale to the roto spline, the results are often unusable if there is any perspective change during the shot. A plane is any flat surface having only two dimensions, such as a table top, a wall, or a television screen. Even as an object leaves and enters a frame, there is usually enough information for the Planar Tracker to maintain a solid track of the object. When you work with the Mocha tools, you will need to look for planes in the clip.

More specifically, you will need to look for planes that coincide with movements you want to track. If someone is waving goodbye, you can break their arm into two planes - the upper and lower limbs. Although not all of the points on the arm sections actually lie on the same two-dimensional surface, the apparent parallax will be minimal. With the addition of PowerMesh, subplanar tracking is also possible, tracking warp and bending of objects that standard planar tracking would struggle to do alone.

For more information on using the PowerMesh feature, see the PowerMesh section of the Tracking Basics chapter. PowerMesh Export to After Effects Nulls: You can export PowerMesh tracks to After Effects nulls via the plug-in interface.

See Creating PowerMesh Nulls in the Plug-In section of the User Guide. PowerMesh Export to Alembic: You can export tracks to a Alembic Mesh with a camera based on the PowerMesh tracking. See the section on Exporting to Alembic for more details on how to use the format. Mesh Warp Stabilize: Using the PowerMesh, you can now warp or unwarp the mesh area in the Stabilize module.

This option is also available in the plug-in render options so you can easily unwarp an area, modify it, then rewarp with a copy of the original effect. For more information on using AdjustTrack V2, see the AdjustTrack Module chapter.

Out of Process Mocha Plug-In: The Mocha Plug-in now operates as a separate process, which allows far greater resource management and stability. Plug-in Python Support: Once restricted to Standalone users, you can now run Python scripts in the Mocha Pro plug-in. See the separate Python Guide for more details. To quickly get familiar with Mocha before you dive into the rest of the manual, here is a breakdown of the interface and its controls. Mocha begins in the Essentials layout, which provides a simplified interface for basic tracking and roto.

The Essentials panel on the left side of the window combines everything you need for a basic track. To attach a spline layer to an existing track, or detach it from a track entirely.

See Tracking Basics and Rotoscoping Basics for more information on the benefits of Link to Track. These buttons control viewing and expanding the surface. See Tracking Basics for how to use the surface effectively. Show surface tracking data : Reveals the blue surface that represents the tracking data.

Show grid: Reveals a useful grid for lining up the surface or monitoring for drift in a track. Align surface: Expands the surface to fit the dimensions of the footage on the current frame.

Like the Essentials layout, this layout is optimized specifically for roto sessions where only the most necessary panels and tools are shown. If you want to reduce all clutter entirely, the Big Picture layout is very useful for previewing shots without any elements getting in the way.

These can either be access by right clicking the area of the interface and choosing a GUI element to show or hide, or selecting from the View menu. Any changes you make to a layout will not be saved unless you choose View Layout Save Current Layout.

For example if you like the Essentials layout, but would like the Advanced toolbar from the Classic layout:. You can add, order or remove layouts from the Manage Custom Layouts dialog in the same sub-menu.

If you have made changes to a saved layout want to revert back to the saved version, just choose View Layout Revert to saved. If you want to revert back to the original default layout, just choose View Layout Revert to default. At the very top of the interface you have the tools that form the brunt of your time inside Mocha.

Select: Selection tool for splines and points. Hold the button to choose between Marquee selection and Lasso selection. Select Both: Selects both the Inner spline points and the edge points. Hold this button down to select further options See below. Select Auto: Automatically selects between Inner and Edge points.

Add X-Spline to Layer: Draw an X-spline that is added to the current spline layer. Add Bezier-Spline to Layer: Draw a B-spline that is added to the current spline layer. Create New Magnetic Layer: Draw a magnetic line that converts to an X-Spline.

Add Magnetic Shape Selected to Layer: Add a new magnetic line that converts to an X-Spline in the existing layer. Create New Freehand Layer: Draw a freehand line that converts to an X-Spline. Add Freehand Shape Selected to Layer: Add a new freehand line that converts to an X-Spline in the existing layer. Create Area Brush Layer: Paint on the canvas to generate an X-Spline.

Add Area Brush to Layer: Paint on the canvas to add an X-Spline to an existing layer. Create Rectangle X-Spline Layer: Draw a new Rectangle X-Spline layer. Add Rectangle X-Spline to Layer: Draw an Rectangle X-spline that is added to the current spline layer. Create Rectangle Bezier-Spline Layer: Draw a new Rectangle B-Spline layer. Add Rectangle Bezier-Spline to Layer: Draw a Rectangle B-spline that is added to the current spline layer. Create Circle X-Spline Layer: Draw a new Rectangle X-Spline layer.

Add Circle X-Spline to Layer: Draw an Rectangle X-spline that is added to the current spline layer. Create Circle Bezier-Spline Layer: Draw a new Rectangle B-Spline layer. Add Circle Bezier-Spline to Layer: Draw a Rectangle B-spline that is added to the current spline layer. Useful for lining up individual splines. Rotate: Rotate selection around the axis of the point you click in the viewer.

EditMesh: Toggles layer into Edit Mesh Mode for editing mesh vertices. Transform Tool: Toggles the transform bounding box for manipulating selections. Show Planar Grid: Toggles a grid relative to the planar surface view. You can adjust the number of grid lines under Viewer Preferences See below.

Align Surface: Expands the layer surface to fit the dimensions of the footage at the current frame. All tracked data is made relative to this new alignment. Add Vertex: Adds a vertex to a selected edge when in Edit Mesh Mode.

Proxy Scale: Adjust the resolution of the footage for performance Mocha Standalone only. Show Layer Mattes: Toggle on or off to show the mattes.

Select from the dropdown to choose the type of matte. Color Layer Mattes: Fills matte with Color. Decreasing the value lessens the opacity. Overlays: Toggles all viewer overlays, including splines, tangents, surface and grid. Show Layer Outlines: Toggles all spline overlays, including splines, points and tangents. Show Spline Tangents: Toggles spline tangents view.

Select from the dropdown to choose the type of view. View Mesh: Toggles Mesh view. Select from the dropdown to choose either the mesh or just the vertices. Stabilize: Turns on stabilize view. This centers the footage around your tracked surface. Trace: Turns on the traced path of the tracked surface. You can adjust the amount of frames to trace under Viewer Preferences See below.

Enable Brightness Scaling: Toggles brightness adjustment to work with low-contrast footage. Viewer Preferences: Adjustments dialog for parameters such as grid lines and trace frames. Also controls for viewer OCIO colourspaces. Reset In-Point: Set the in-point back to the start of the clip.

Current Frame: The frame the playhead is currently on.

To scan one or more variables, drop them into the Scan box, then double click on the box. If you are using corner pin, select the 'Four Corners' option from the 'Type' drop down. Once you have applied the Mocha effect, you can click on the 'Launch Mocha UI' button to launch the main interface. Here is an example of the time a TClonesArray can save over a TObjArray. Create New Magnetic Layer: Draw a magnetic line that converts to an X-Spline. In After Effects, import the same footage and ensure that the frame rate and pixel aspect ratio are the same as those used when generating the shape.

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