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Do date ranges from two different timetables intersect?

Is a specific datetime value within the range of a timetable?

Is the range of row times in a timetable within the limits of a datetime array?

Three new functions in r2020a will help to answer these questions.

In these function inputs, TT is a timetable and input #2 is one of the following:

The tf output is a logical scalar indicating pass|fail and the whichRows output is a logical vector identifying the rows of TT that are within the specified time range.

How do these functions differ?

Let's test all 3 functions with different time ranges and a timetable of electric utility outages in the United States, provided by Matlab. The first few rows of outages.csv are shown below in a timetable. You can see that the row times are not sorted which won't affect the behavior of these functions.

8×5 timetable
     OutageTime          Region         Loss     Customers     RestorationTime            Cause       
  ________________    _____________    ______    __________    ________________    ___________________
  2002-02-01 12:18    {'SouthWest'}    458.98    1.8202e+06    2002-02-07 16:50    {'winter storm'   }
  2003-01-23 00:49    {'SouthEast'}    530.14    2.1204e+05                 NaT    {'winter storm'   }
  2003-02-07 21:15    {'SouthEast'}     289.4    1.4294e+05    2003-02-17 08:14    {'winter storm'   }
  2004-04-06 05:44    {'West'     }    434.81    3.4037e+05    2004-04-06 06:10    {'equipment fault'}
  2002-03-16 06:18    {'MidWest'  }    186.44    2.1275e+05    2002-03-18 23:23    {'severe storm'   }
  2003-06-18 02:49    {'West'     }         0             0    2003-06-18 10:54    {'attack'         }
  2004-06-20 14:39    {'West'     }    231.29           NaN    2004-06-20 19:16    {'equipment fault'}
  2002-06-06 19:28    {'West'     }    311.86           NaN    2002-06-07 00:51    {'equipment fault'}

The range of times in utility.csv is depicted by the gray timeline bar in the plot below labeled "Timetable row times". The timeline bars above it are various time ranges or scalar datetime values used to test the three new functions.

The three columns of checkboxes on the right of the plot show the results of the first output of each function, tf, for each time range.

The time ranges were created by the timerange function using the syntax timerange(startTime,endTime). The default intervalType in timerange() is 'openright' which means that datetimes are matched when they are equal to or greater than startTime and less than but not equal to endTime. The scalar datetime values were created with datetime().

The colorbar along with the colored points at the bottom of each timeline bar show the row numbers of timetable TT that were selected by the whichRows output of the three functions.

The containsrange() function returns true when all of the time range values are within the timetable including the timetable's minimum and maximum datetime.

The overlapsrange() function returns true when any of the time range values are with the timetable's range.

The withinrange() function returns true only when all of the timetable's datetime values are within the time range values. A careful observer may see that comparison number 1 is false even though that time range is exactly equal to the timetable's row time range. This is because the default value for intervalType in the timerange() function is 'openright' which does not match the end values if they are equal. If you change the intervalType to 'closed' the withinrange result for comparison 1 would be true.

The scalar datetime values for comparisons 8, 9 and 10 are all exact matches of datetimes within the timetable and result in a single match in the whichRows output. The datetime values for comparisons 7 and 11 do not match any of the timetable row times and the values in whichRows are all false even though comparison 7 is within the timetable range. For all three tests, the whichRows outputs are identical.

---------------------------------------------------------------

Here is the code used to generate this data, test the functions, and produce the plot.

% Read in the outage data as a table and convert it to a timetable TT.
T = readtable('outages.csv');
TT = table2timetable(T);
% Look at the first few rows.
head(TT)
% Show that row time vector is not sorted.
issorted(TT)
% Get the earliest and latest row time.
outageTimeLims = [min(TT.OutageTime), max(TT.OutageTime)];
% Define time ranges to test [start,end] or scalar times [datetime, NaT]
% The scalar times must be listed after time ranges.
dateRanges = [ % start, end
    outageTimeLims;                                 % original data
    outageTimeLims;                                 % equal time range
    datetime(2005,2,1), datetime(2011,2,1);         % all within
    datetime(1998,3,16), datetime(2018,4,11);       % starts before, ends after
    datetime(2000,1,1), datetime(2010,4,11);        % starts before, ends within
    datetime(2009,1,15), datetime(2019, 4,7);       % starts within, ends after
    datetime(2015,6,15), datetime(2019,12,31);      % all outside
    datetime(2008,6,6), NaT;                        % 1-value, inside, not a member
    [TT.OutageTime(find(year(TT.OutageTime)==2010,1)), NaT] % 1 value, inside, is a member
    outageTimeLims(1), NaT;                         % 1-value, on left edge
    outageTimeLims(2), NaT;                         % 1-value, on right edge
    datetime(2000,6,6), NaT;                        % 1-value, outside
    ];
nRanges = size(dateRanges,1);
dateRangeLims = [min(dateRanges,[],'all'), max(dateRanges,[],'all')];
% Set up the figure and axes
uifig = uifigure('Name', 'Timetable_intersection_demo', 'Resize', 'off');
uifig.Position(3:4) = [874,580];
movegui(uifig,'center')
uiax = uiaxes(uifig, 'Position', [0,0,uifig.Position(3:4)], 'box', 'on', 'YAxisLocation', 'right',...
    'ytick', -.5:1:nRanges, 'YTickLabel', [], 'ylim', [-3.5, nRanges], 'FontSize', 18);
hold(uiax, 'on')
grid(uiax, 'on')
uiax.Toolbar.Visible = 'off';
% Add axes labels & title
title(uiax, strrep(uifig.Name,'_',' '))
xlabel(uiax, 'Timeline')
ylab = ylabel(uiax, 'Comparison number');
set(ylab, 'Rotation', -90, 'VerticalAlignment', 'Bottom')
% Add the timetable frame
fill(uiax, outageTimeLims([1,2,2,1]), [-.7,-.7,nRanges-.3,nRanges-.3] , 0.85938*[1,1,1], ... %gainsboro
    'EdgeColor', 0.41016*[1,1,1], 'LineStyle', '--', 'LineWidth', 1.5, 'FaceAlpha', .25)     %dimgray
% Set xtick & xlim after x-axis is converted to datetime
range = @(x)max(x)-min(x); 
uiax.XLim = dateRangeLims + range(dateRangeLims).*[-.01, .40];
uiax.XTick = dateshift(dateRangeLims(1),'start','Year') : calyears(2) : dateshift(dateRangeLims(2),'start','Year','next');
xtickformat(uiax,'yyyy')
% Set up timeline plot
lineColors = [0.41016*[1,1,1]; lines(nRanges-1)]; %dimGray
uiax.Colormap = parula(size(TT,1));
tfUniCodes = {char(09745),char(09746)}; %{true, false} checkbox characters
barHeight = 0.8;
rightMargin = [max(dateRangeLims),max(uiax.XLim)];
tfCenters = linspace(rightMargin(1),rightMargin(2),5);
tfCenters([1,end]) = [];
intervalType = 'openright';  % open, closed, openleft openright(def);  see https://www.mathworks.com/help/matlab/ref/timerange.html#bvdk6vh-intervalType
% Loop through each row of dateRanges
for i = 0:nRanges-1
    % Plot timeline bar
    pObj = fill(uiax, dateRanges(i+1,[1,2,2,1]), i+[-barHeight,-barHeight,barHeight,barHeight]/2, lineColors(i+1,:), 'FaceAlpha', .4);
      % Evaluate date ranges and single values differently
      if any(isnat(dateRanges(i+1,:)))
          % Test single datetime
          tr = dateRanges(i+1,~isnat(dateRanges(i+1,:)));
          set(pObj, 'LineWidth', 3, 'EdgeAlpha', .6, 'EdgeColor', lineColors(i+1,:))
      else
          % Test date range
          tr = timerange(dateRanges(i+1,1), dateRanges(i+1,2),intervalType);
      end
      % Create timerange obj and test for intersections
      [tf(1), whichRows{1}] = containsrange(TT,tr);
      [tf(2), whichRows{2}] = overlapsrange(TT,tr);
      [tf(3), whichRows{3}] = withinrange(TT,tr);
      % Confirm that all 'whichRows' are equal
      assert(isequal(whichRows{1},whichRows{2},whichRows{3}), 'Unequal whichRows outputs.')
      if i>0
          % Add pass/fail checkboxes
          text(uiax, tfCenters(tf), repmat(i,1,sum(tf)), repmat(tfUniCodes(1),1,sum(tf)), ...
              'HorizontalAlignment', 'Center', 'Color', [0 .5 0], 'FontSize', 36, 'FontWeight', 'Bold')
          % Fail checkboxes
          text(uiax, tfCenters(~tf), repmat(i,1,sum(~tf)), repmat(tfUniCodes(2),1,sum(~tf)), ...
              'HorizontalAlignment', 'Center', 'Color', [1 0 0], 'FontSize', 36, 'FontWeight', 'Bold')
          % Plot the TT row number matches
          scatter(uiax, TT.OutageTime(whichRows{1}), repmat(i-barHeight/2+.1,1,sum(whichRows{1})), ...
              10, uiax.Colormap(whichRows{1},:), 'filled', 'MarkerFaceAlpha', 0.2)
      else
          % add stripes to reference bar
          xHatch = linspace(dateRanges(i+1,1)-days(2), dateRanges(i+1,2)+days(2), 20);
          yHatch = repmat(unique(pObj.YData), 1, 19);
          plot(uiax, [xHatch(1:end-1);xHatch(2:end)], yHatch, '-', 'Color', [1 1 1 .5], 'LineWidth', 4)
          pObj.FaceAlpha = .9;
          text(uiax, mean(outageTimeLims), 0, 'Timetable row times', 'FontSize', 20, ...
              'HorizontalAlignment', 'Center', 'VerticalAlignment', 'middle', 'FontWeight', 'Bold')
      end
  end
% Draw frame around checkboxs for duration comparisons and label intervalType
rectEdges = linspace(rightMargin(1),rightMargin(2),33);
nDurations = sum(~isnat(dateRanges(:,2)))-1;
fill(uiax, rectEdges([6,end-5,end-5,6]), [.4 .4 nDurations+[.4,.4]], 'w', ...
    'FaceAlpha', 0, 'LineWidth', 1.5, 'EdgeColor', 0.41016*[1,1,1]) % dimgray
text(uiax, rectEdges(6), nDurations/2+.5, sprintf('intervalType: %s', intervalType), 'FontSize', 16, ...
    'HorizontalAlignment', 'Center', 'VerticalAlignment', 'Bottom', 'Rotation', 90)
% Add text labels for checkboxes and comparison number
text(uiax, tfCenters, [.5 .5 .5], {'containsrange ', 'overlapsrange ', 'withinrange '}, 'Fontsize', 22, 'Rotation', 90, ...
    'HorizontalAlignment', 'right', 'FontWeight', 'b')
text(uiax, repmat(rightMargin(2)-range(xlim(uiax))*.02,1,nRanges-1), 1:nRanges-1, cellstr(num2str((1:nRanges-1)')), ...
    'HorizontalAlignment', 'Right', 'FontSize', 16)
% Add color bar; position it under the timetable bar (must be done after all other axes properties are set)
% requires coordinate tranformation from data units to fig position units.
cb = colorbar(uiax, 'Location', 'South', 'TickDirection', 'Out', 'YAxisLocation', 'Bottom', 'FontSize', 11);
caxis(uiax, [1,size(TT,1)])
cb.Position(3) = range(outageTimeLims)/range(xlim(uiax))  * (uiax.InnerPosition(3)/uifig.Position(3));
cb.Position(1) = ((outageTimeLims(1)-min(xlim(uiax)))/range(xlim(uiax)) * uiax.InnerPosition(3) + uiax.InnerPosition(1)) / uifig.Position(3); 
cb.Position(4) = 0.008;
cb.Position(2) = ((-barHeight-min(ylim(uiax))-.5)/range(ylim(uiax)) * uiax.InnerPosition(4) + uiax.InnerPosition(2)) / uifig.Position(4);
ylabel(cb, 'Timetable row number')

The following is a list of updates and new features for File Exchange and Cody.

New Features

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Let us know what you think about these new features by replying below.

Take a look at this handy cheatsheet from Peijin Zhang, a PhD student of solar radio at USTC, China. This is especially helpful for those preparing figures for a paper.

https://github.com/Pjer-zhang/matlabPlotCheatsheet

Do you know of any other cheatsheets for MATLAB?

goc3
goc3
Last activity 2020-4-6

Cody has a wealth of problem groups that allow users of various skill levels to improve programming skills vis-à-vis MATLAB in an engaging way.

I would like to highlight the Draw Letters group, composed of problems created by Majid Farzaneh.

If you haven't yet visited Cody or solved that problem group, I would recommend that you head over there now. What are you waiting for?

We have created a new distance learning community for educators who are teaching remotely or online using MathWorks tools. It houses resources, such as articles, code examples, and videos, as well as an area where community members can ask questions or hold discussions around best practices in distance learning. Jiro Doke , who also writes for the File Exchange Pick of the Week blog, will be moderating this community.

We encourage you to visit the new community and share best practices, examples, and ask questions.

David
David
Last activity 2020-3-30

We have created a new page in MATLAB Answers that aggregates the most frequently asked MATLAB questions (FAQs). FAQs are common and a good starting point for anyone learning something new and having them all in one place can be a useful resource. Our new FAQ page lists the top 100 MATLAB questions asked and answered in MATLAB Central . They are grouped into the following 9 categories:

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I recommend that everyone scans the new FAQ page as you might find some useful tips.

We will be updating the FAQ page regularly as new questions are asked in the community. We welcome any feedback you have.

Check out this pick of the week from Emma Gau. Emma's submission is featured on the Live Script gallery. Check out the blog post to see why Owen picked it.

In problem 16 I used the following solution:
function b = nearZero(a)
b = max(a(imdilate(a == 0, [1 1 1])));
end
It is working pretty well on mathlab but when I submit my answer to cody, the following error is generated:
Undefined function 'imdilate' for input arguments of type 'double'.
Error in nearZero (line 2)
b = max(a(imdilate(a == 0, [1 1 1])));
Error in Test1 (line 3)
assert(isequal(nearZero(a),b))
In number 5, its written that the correct answer is c = 1 but the secomnd person has more change than the first person, therefor the correct answer should be 2.Likewise in number 6.

Check out this pick of the week from Will. Steve's progressbar submission has been around since 2005 and still runs perfectly. Check out the blog post to see why Will picked it.

We are excited to announce that Adam Danz has accepted our invitation and now is a member of the Community Advisory Board (CAB)!

Adam has been a rising star in Answers, obtaining 4500+ reputation points in the past year! Furthermore, he has contributed high-quality files to File Exchange, with an average rating of 4.8. Adam also demonstrates good communication skills and the ability to work with others. Those characteristics are what we expect to see from a CAB advisor. You can learn more about him and CAB on the CAB page .

On behalf of all the community team, we would like to extend our warmest welcome to Adam!

Check out Sean's blog posts ( Intro , Authoring ) on Spider Plots. He's using spider_plot by Moses to create beautiful plots like this.

The following is a list of updates and new features for MATLAB Central, including MATLAB Answers, File Exchange, Blogs, and Cody.

New Features

Community highlights channel released - See this post for more details.

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Hey everyone! I'm spotlighting Nikolaos Nikolaou today because of the sheer quantity of his Cody solutions over such a relatively short time span. Nikolaos has submitted 1,161 Cody solutions over the last 6 months of 2019, averaging 6.4 solutions per day. Achieving a Cody rank of 19 with a score of 18,820 and earning him a plethora of badges (including the Speed Demon badge of course). He's completed 24 problem groups and is well into most of the remaining 35.

Way to go Nikolaos!

Check out digCircs by Graham W Griffiths, this weeks pick by Sean . Read Sean's blog post about why he picked Graham's submission this week.

Please post any comments to Seans's blog post here.

Check out nextname by Stephen Cobeldick, this weeks pick by Jiro. Read Jiro's blog post about why he picked Stephen's submission this week.

Please post any comments to Jiro's blog post here.

I'm please to announce this new MATLAB Central feature for posting community highlights. This new channel will:

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What do we mean by newsworthy?  In short, this means anything we think some or all of the community might like to know. Here are some examples of what we’re thinking about posting to this new channel.

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New highlights will appear on the community home page at the time they are posted and all past highlights can be found by going to the community home page and clicking the Highlights link in the right column.

As always, let us know what you think by liking this post or commenting below.

The following is a list of updates and new features for MATLAB Central, including MATLAB Answers, File Exchange, Blogs, and Cody.

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Walter Roberson does it again by winning the coveted MOST ACCEPTED answers badge for all his contributions in MATLAB Answers this past year. Walter has won this badge every year since 2015. It was way back in 2014 when Image Analyst out paced Walter and was awarded the badge.

There are 10 community members who have achieved the Top Downloads badge for their popular File Exchange submissions in 2019. Do you recognize any of these names? There's a good chance you've used one or more of their toolboxes or scripts in your work if you're a frequent visitor to File Exchange, if you're not you might want to check out what they've posted, it may save you a lot of time writing your own code.

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