I'm monitoring log data from distributed build system. Each source file has its compile time.
I'm plotting data using average of compilation duration on Y axis and date histogram with #timestamp on X axis. I added Split Lines with Top 10 terms sub aggregation to observe if building of files is shorter or longer in time.
The problem is that I would like to show only data points which are above certain threshold value. I tried to cut plot on Y axis but this caused some lines went off screen connecting to data points which was cut off.
Related
I am writing an application for Windows 10 using Delphi 11 and Steema TeeChart pro 11 components.
I use AddXY(….) to plot a DateTime series of about 1000 values as points in Chart1 with BottomAxis set to DateTime and the Leftaxis set to float.
Thereafter I zoom in a small part of the data in Chart1 using the mouse wheel or drawing a rectangle.
Then I want to plot a new time series (AddXY(….)) of 1000 values in Chart1, keeping the zoomed in min and max values for the bottom axes, but use automatic scaling for LeftAxis. Before plotting the second series I delete the first.
The second series have the same DateTime values as the first series, but the Y values are sometimes very different compared with the first series and may not be visible in the graph.
Now the problem occurs. The Left axis will be automatic scaled based on all the data points and not on the points only falling within the zoomed X boundaries.
Does TChart have a simple method to find the min and max Y-values for the second series within the zoomed in time period. I thought of using the LeftAxis.AdjustMinMax() procedure for rescaling the left axis?
Of course I could scan through all the Y-values within the zoomed in period and calculate the min and max value. Then, how do I know the starting and ending valueindex of the data points falling within the zoomed in time period? I hoped to avoid using this method due to speed resons if number of points are > 1000.
Hopefully someone more experienced TeeChart programmer than I am can give me some suggestions of the best way to achieve this.
When I do a scatter plot, by default it shows the axis from 0.0 to 1.0 fractions.
For example, the following graph contains a straight line that goes from (0,0) to (10m,10m), but it shows:
Detailed data generation show at: Large plot: ~20 million samples, gigabytes of data
How to make the axes show from 0 to 10 million instead?
The inspiration for this comes from this question.
Tested in VisIt 2.13.3.
Since scatter plot associates variables of potentially radically different scales, by default, it maps each variable's range into [0,1]. We have this ticket for it. You can manually change by going to scatter plot attribute's window and Apperance tab and un-checking the 'Normalize the axes to a cube' option
I am working on a project which make use of Python-2.7, pygtk and matplotlib-2 on windows.
My app records data from COM port and plot it like a live plot. I need to put major and minor ticks for grid purpose.
My X-axis data is time duration in seconds.
ax1.set_xticks(np.arange(x_range[0],x_range[1],0.45))
ax1.set_xticks(np.arange(x_range[0],x_range[1],0.09),minor=True)
major ticks # 0.45 sec.
minor ticks # 0.09 sec
x_range[0] is minimum value of x axis data
x_range1 is maximum value of x axis data
Setting ticks this way is taking more time and also it takes lot of time when I plot entire data.
Is there any faster way to set ticks using matplotlib?
Note: I have totally 7 different data sets to be plotted on different subplots.
Sample plot image is given blow.
In following image, you can see grid properly. This plot window is also with a scroll bar at bottom. Total plot size depends on total time of data recording.
I've written a program which reads measurements from an impedance analyzer as it sweeps over a range of frequencies or voltages, saves the data to a text file, and also creates a scatter plot. In one type of measurement, I obtain x and y values for complex impedance, neither of which are the independent parameter. Now when plotting this graph, it appears that it simply puts each x value to the right of the previous one at regular spacings resulting in x axis labels looking like, from left to right, [45000, 43000, 40000,... etc.].
I've tried forcing the x-axis to start from zero which did not change anything and haven't been able to find much else on this. Is there a way to make sure the plot reflects the actual x values of each point?
Here's my current method of creating the chart,which pulls the data from the already created table:
For Each row In table.Rows
Chart1.Series("series1").Points.AddXY(row(0), row(1))
Next
Let's say I have a list of values and I have already chunked them into groups to make a histogram.
Since Excel doesn't have histograms, I made a bar plot using the groups I developed. Specifically, I have the frequencies 2 6 12 10 2 and it produces the bar plot you see below.
Next, I want to add a normal distribution (line plot) with a mean of 0.136 and standard deviation of 0.497 on top of this histogram. How can I do this in excel? I need the axis to line up such that it takes up the width of the bar plot. Otherwise, you get something like I've attached.
But...the normal should be overlayed on the bar plot. How can I get this effect?
There are two main part to this answer:
First, I reverse-engineered the grouped data to come up with an appropriate mean and standard deviation on this scale.
Second, I employed some chart trickery to make the normal distribution curve look right when superimposed on the column chart. I used Excel 2007 for this; hopefully you have the same options available in your version.
Part 1: Reverse-Engineer
The column B formulae are:
Last Point =MAX(A2:A6)
Mean =SUMPRODUCT(B2:B6,A2:A6)/SUM(B2:B6)
E(x^2f) =SUMPRODUCT(A2:A6^2,B2:B6)
E(xf)^2 =SUMPRODUCT(A2:A6,B2:B6)^2
E(f) =SUM(B2:B6)
Variance =B10-B11/B12
StDev =SQRT(B13/(B12-1))
Part 2: Chart Trickery
Data table:
Column D is just an incremental counter. This will be the number of data points in the normal distribution curve.
E2 =D2/$B$8 etc.
F2 =NORMDIST(E2,$B$9,$B$14,FALSE) etc.
Chart:
Now, add Columns E:F to the chart. You will need to massage a few things:
Change the series to be an X-Y plot. This might require some editing of the chart series to force a single series to use your desired X and Y values.
Change the series to use the secondary axes (both X and Y).
Change the secondary X-axis range to 0.5-5.5 (i.e., 0.5 on either side of the column chart category values). This will effectively align the primary and secondary X-axes.
Change the secondary Y-axis range to 0-1
Format the X-Y series appearance to taste (I suggest removing value markers).
The result so far:
Lastly, you can remove the tick marks and labels on the secondary axes to clean up the look.
Postscript: Thanks to John Peltier for innumerable charting inspirations over the years.