I am trying to plot a graph with temperature values(Y) vs. datetime(X).
The datetime is constituted of many equal dates, without hour associated. For example, I would have 1440 values with 2018/01/11, then other 1440 values with 2018/01/12.., whereas for each point I have a different temperature value.
This is what it should look like:
But this is how it ended up when I use plot(temperature, date):
All the values for the same day are accumulated as it was a stem ..
I would need it to map point 1 of Y with point 1 of X, and so on, without recognizing the X axis as a datetime, but instead to recognize it as a string. I don't know if I am explaining it right.
But to give a simple example, basically would be something like:
Y = [1, 2, 3, 4, 5]
X = [2016, 2016, 2016, 2016]
And all the 2016 should be different sequence values on the graph.
Would someone be able to help me, please?
Related
I have daily time series data and I want to calculate 5-day averages of that data while also retrieving the corresponding start date for each of the 5-day averages. For example:
x = [732099 732100 732101 732102 732103 732104 732105 732106 732107 732108];
y= [1 5 3 4 6 2 3 5 6 8];
Where x and y are actually size 92x1.
Firstly, how do I compute the 5-day mean when this time series data is not divisible by 5? Ultimately, I want to compute the 'jumping mean', where the average is not computed continuously (e.g., June 1-5, June 6-10, and so on).
I've tried doing the following:
Pentad_avg = mean(reshape(y(1:90),5,[]))'; %manually adjusted to be divisible by 5
Pentad_dt = x(1:5:90); %select every 5th day for time
However, Pentad_dt gives me dates 01-Jun-2004 and 06-Jun-2004 as output. And, that brings me to my second point.
I am looking to find 5-day averages for x and y that correspond to 5-day averages of another time series. This second time series has 5-day averaged data starting from 15-Jun-2004 until 29-Aug-2004 (instead of starting at 01-Jun-2004). Ultimately, how do I align the dates and 5-day averages between these two time series?
Synchronization between two time series can be accomplished using the timeseries object. Placing your data into an object allows Matlab to intelligently process it. The most useful thing is adds for your usage is the synchronize method.
You'll want to make sure to properly set the time vector on each of the timeseries objects.
An example of what this might look like is as follows:
ts1 = timeseries(y,datestr(x));
ts2 = timeseries(OtherData,OtherTimes);
[ts1 ts2] = synchronize(ts1,ts2,'Uniform','Interval',5);
This should return to you each timeseries aligned to be with the same times. You could also specify a specific time vector to align a timeseries to using the resample method.
I'm trying to draw a temperature graph using iso-charts where the x axis data would be set from a server timestamp but the labels would be readable text.
For instance the graph x-axis label would start at Monday 00:00 and end Tuesday 12pm but the LineChartDataSet would be a collection of temperature (y-axis) and timestamps for the x
To display the timestamp I have a custom valueFormatter set as follow (which works great)
lineChartView.xAxis.valueFormatter = timestampXAxisFormatter() //converts timestamp to Date string
My question: The LineChartDataSet seems to be indexed based which is causing some trouble: if I have 4 data points such as (9am, 10), (9:15am, 11), (12pm, 15), (1pm, 16) the 4 points are set in the chart at regular intervals (I was expecting 2 points to be on the left side of the graph and then last 2 points on the right side) - Is there a way to have a data set that is based on the x value instead of the index?
I saw ChartData has an init that takes an array of NSObjects but then it converts it to Strings...Thanks in advance for any suggestions you may have!
There is no good way to solve it, as you figured out the x axis is index based.
You have two options:
insert many x values between each real x value, like between 9:00 and 9:15, you manually insert 9:01, 9:02, ..., 9:14, but don't add any entry at these values, just ignore it and continue. ios-charts will skip if no entry found and go to next. This will works fine, if you don't have a large number of values to insert. I tried ~1000 values, the performance is acceptable.
you create your own chart, using two y axis, one as x axis and one as y axis, so the distances to 0 point are calculated by value. However this requires you understand the ios-chart logic deeply. If you succeed, you are more than welcome to file a PR.
I have time set up as serial dates. Each number corresponds to a day, in order, from 20100101 to 20130611. How do I convert the serial date to a date in the format month-year? I need this because I want to plot data and need the x axis to show the date.
Thanks!
The first step is to convert your date-format into one of the standard Matlab date formats. The best format to use for plots is the "serial date format". The numbers itself are a bit awkward, since they represent the "amount of time after 0/0/0000, in days", which is a huge number. Also, this date actually never existed, making it really weird when you want to work with dates that are BC.
However, the conversion is easy, since your format also counts the days, but you count after 31st of December, 2009. You can convert this using
numeric_date_vec = datenum(2009, 12, 31) + x;
You then plot your data using
plot(numeric_date_vec, y)
and you let Matlab add the date-ticks automatically by calling
datetick('mmm yyyy')
The problem is, the ticks do not update after zooming in. You can either call
datetick('mmm yyyy','keeplimits')
again, after each zooming or panning, or you download datetickzoom from the Matlab file exchange. It takes the same arguments as datetick, but it hooks into the zoom function and updates the ticks automatically.
Edit:
Sometimes, the dateticks are not spaced in any sensible way, then you can either try to zoom in and out a little until it snaps to something good, or you have to set the ticks manually:
% Set ticks to first day of the months in 2010
tick_locations = datenum(2012,[1:12],1);
% Set ticks on x-axis
set(gca, 'XTick', tick_locations)
% Call datetick again to get the right date labels, use option "keepticks"
datetick('mmm yyyy','keeplimits', 'keepticks')
You might have to modify the tick_locations = datenum(2012,[1:12],1) a bit to get the ticks that you want. For instance, you can use
tick_locations = datenum(2012,[1:2:25],1)
to get every second month between Jan 2012 and Jan 2013.
For day number n use
datestr(datenum(2009, 12, 31) + n, 'yyyy-mm')
for example
>> datestr(datenum(2009, 12, 31)+365, 'yyyy-mm')
ans =
2010-12
>> datestr(datenum(2009, 12, 31)+366, 'yyyy-mm')
ans =
2011-01
I have been searching various forums for hours but it seems impossible to do a thing in Matlab that's automatic in excel...
I used uiimport to import an xls file with into two arrays (? total newbie), one containing dates for my x-axis and the other the values I want to plot.
I have 180 values. The dates are three dates per month, more or less ranging from May 2008 until now, end of March.
Using
plot(mynumbers)
set(gca,'XTickLabel',dates)
only puts dates for May 2008 on my x-axis!
where did all the other dates go?
Instead using
plot(mynumbers)
set(gca,'XTick',mynumbers,'XTickLabel',dates)
gives error message
"??? Error using ==> set
Values must be monotonically increasing."
Please help!
where did all the other dates go?
The answer to your first question is that MATLAB only uses the first N number of strings corresponding to the default N number of tick marks on the x axis.
"??? Error using ==> set Values must be monotonically increasing."
The error is telling you that your date ticks must be evenly spaced. Instead of using dates corresponding to your actual data points, you could grab the x tick values that MATLAB automatically assigned to your graph, translate them to text, and then reassign the dates as x tick labels, like so:
% generate example unevenly spaced date vector
time = [now,now+1,now+25,now+28.5,now+36,now+40,now+51,now+65];
% generate random data points
data = rand(size(time));
% plot time vs data, storing the axes handle in the process
figure;
axH = axes;
plot(axH,time,data)
% get the x-axis tick locations
ticLoc = get(axH,'XTick');
% format tick labels (substitute any date format you wish)
ticLab = cellfun(#(x) datestr(x,'mm/dd'),num2cell(ticLoc),'UniformOutput',false);
% apply tick labels
set(axH,'XTickLabel',ticLab)
MATLAB's built-in function datetick also performs similarly.
However, if you zoom afterwards, you won't have accurate tick labels. So you may want to use datetick2 on the File Exchange.
If you're having trouble converting a cell array of dates from Excel into a numeric array, use:
dateNumeric = cell2mat(cellfun(#datenum,dateStrings,'UniformOutput',false));
try set (gca,'XTickLabel',num2str(dates))
I have 500,000 values for a variable derived from financial markets. Specifically, this variable represents distance from the mean (in standard deviations). This variable has a arbitrary distribution. I need a formula that will allow me to select a range around any value of this variable such that an equal (or close to it) amount of data points fall within that range.
This will allow me to then analyze all of the data points within a specific range and to treat them as "similar situations to the input."
From what I understand, this means that I need to convert it from arbitrary distribution to uniform distribution. I have read (but barely understood) that what I am looking for is called "probability integral transform."
Can anyone assist me with some code (Matlab preferred, but it doesn't really matter) to help me accomplish this?
Here's something I put together quickly. It's not polished and not perfect, but it does what you want to do.
clear
randList=[randn(1e4,1);2*randn(1e4,1)+5];
[xCdf,xList]=ksdensity(randList,'npoints',5e3,'function','cdf');
xRange=getInterval(5,xList,xCdf,0.1);
and the function getInterval is
function out=getInterval(yPoint,xList,xCdf,areaFraction)
yCdf=interp1(xList,xCdf,yPoint);
yCdfRange=[-areaFraction/2, areaFraction/2]+yCdf;
out=interp1(xCdf,xList,yCdfRange);
Explanation:
The CDF of the random distribution is shown below by the line in blue. You provide a point (here 5 in the input to getInterval) about which you want a range that gives you 10% of the area (input 0.1 to getInterval). The chosen point is marked by the red cross and the
interval is marked by the lines in green. You can get the corresponding points from the original list that lie within this interval as
newList=randList(randList>=xRange(1) & randList<=xRange(2));
You'll find that on an average, the number of points in this example is ~2000, which is 10% of numel(randList)
numel(newList)
ans =
2045
NOTE:
Please note that this was done quickly and I haven't made any checks to see if the chosen point is outside the range or if yCdfRange falls outside [0 1], in which case interp1 will return a NaN. This is fairly straightforward to implement, and I'll leave that to you.
Also, ksdensity is very CPU intensive. I wouldn't recommend increasing npoints to more than 1e4. I assume you're only working with a fixed list (i.e., you have a list of 5e5 points that you've obtained somehow and now you're just running tests/analyzing it). In that case, you can run ksdensity once and save the result.
I do not speak Matlab, but you need to find quantiles in your data. This is Mathematica code which would do this:
In[88]:= data = RandomVariate[SkewNormalDistribution[0, 1, 2], 10^4];
Compute quantile points:
In[91]:= q10 = Quantile[data, Range[0, 10]/10];
Now form pairs of consecutive quantiles:
In[92]:= intervals = Partition[q10, 2, 1];
In[93]:= intervals
Out[93]= {{-1.397, -0.136989}, {-0.136989, 0.123689}, {0.123689,
0.312232}, {0.312232, 0.478551}, {0.478551, 0.652482}, {0.652482,
0.829642}, {0.829642, 1.02801}, {1.02801, 1.27609}, {1.27609,
1.6237}, {1.6237, 4.04219}}
Verify that the splitting points separate data nearly evenly:
In[94]:= Table[Count[data, x_ /; i[[1]] <= x < i[[2]]], {i, intervals}]
Out[94]= {999, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000}