IDL Histograms: Solving the X-Axis Frustration

  • Thread starter taylrl3
  • Start date
In summary, when using the histogram command in IDL, make sure your data is in the desired units and use the "bin" or "range" keywords to specify the bin edges on the x-axis. This should help you display your data correctly.
  • #1
taylrl3
61
0
Hi,

I am currently having an absolute nightmare trying to use the histogram command in IDL. I almost have it as I want, I just want it to show my units on the x-axis rather than the number of bins. I can't find anything that explains how this works on the net it seems no one really understands it at all. Hopefully someone here can help me. This is how I am plotting it at the moment:

plot, histogram(Galaxydiffs, bin=((max-min)/nbins)), xtitle='X/h!u-1!nMpc', psym=10

Galaxydiffs is an array with the data I want in the histogram.
nbins is the number of bins

Currently the x-axis is the number of bins. I want it to show the distances corresponding to each bin.

Any help would be most appreciated as this is driving me crazy

Thanks
Taylrl2
 
Technology news on Phys.org
  • #2


Hi Taylrl2,

I understand your frustration with trying to use the histogram command in IDL. It can be tricky to get the x-axis to display the units you want, but it is definitely possible.

First, make sure that your Galaxydiffs array contains the actual distances you want to plot on the x-axis. If it does not, you will need to convert your data to the desired units before plotting.

Next, you can use the "bin" keyword in the histogram command to specify the bins you want to use. Instead of providing the number of bins, you can provide an array of the bin edges you want to use. For example, if your data ranges from 0 to 10 Mpc and you want 10 bins, you can use the following command:

plot, histogram(Galaxydiffs, bin=[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), xtitle='X/h!u-1!nMpc', psym=10

This will create 10 bins with the corresponding distances on the x-axis.

Alternatively, you can use the "range" keyword to specify the range of your data and the number of bins you want, and IDL will automatically calculate the bin edges for you. For example:

plot, histogram(Galaxydiffs, range=[0, 10], nbins=10), xtitle='X/h!u-1!nMpc', psym=10

I hope this helps to solve your issue with the histogram command. If you continue to have trouble, please provide more information about your data and the specific error message you are receiving.

Best of luck!
 

FAQ: IDL Histograms: Solving the X-Axis Frustration

What is the purpose of solving the X-Axis Frustration in IDL Histograms?

The purpose of solving the X-Axis Frustration in IDL Histograms is to accurately represent the data on the x-axis in a visually appealing and easy to interpret manner. This frustration often arises when the x-axis labels are not evenly spaced or do not correspond to the actual data values. By solving this issue, the histogram becomes a more useful tool for data analysis and presentation.

How does IDL solve the X-Axis Frustration in Histograms?

IDL solves the X-Axis Frustration in Histograms by using the HISTOGRAM function, which automatically generates evenly spaced bins based on the data range. It also allows for customization of the bin size and labels to better represent the data. Additionally, the HISTOGRAM function can handle logarithmically spaced bins for skewed data.

3. Can the X-Axis Frustration in IDL Histograms be solved manually?

Yes, the X-Axis Frustration in IDL Histograms can be solved manually by manually setting the bin size and labels. However, this can be time-consuming and may not result in an accurate representation of the data. It is recommended to use the HISTOGRAM function to automatically solve this issue.

4. What are the benefits of solving the X-Axis Frustration in IDL Histograms?

The benefits of solving the X-Axis Frustration in IDL Histograms include a more accurate and visually appealing representation of the data, making it easier to interpret and analyze. It also saves time and effort compared to manually setting the bin size and labels.

5. Are there any limitations to solving the X-Axis Frustration in IDL Histograms?

While solving the X-Axis Frustration in IDL Histograms can greatly improve the visualization of the data, there are some limitations to consider. For example, the HISTOGRAM function may not work well for data with extreme outliers or a very small data range. In these cases, manual adjustments may be necessary to accurately represent the data on the x-axis.

Similar threads

Replies
9
Views
2K
Replies
7
Views
1K
Replies
4
Views
8K
Replies
5
Views
2K
Replies
1
Views
5K
Replies
3
Views
7K
Replies
1
Views
8K
Replies
2
Views
3K
Back
Top