To make it even easier to obtain reliable calibration data, we have developed our own processing software to automatically calculate the dimensions of PSFcheck features imaged through your microscope. This is all carried out through our web interface - no downloads or software installations required. Simply upload your image data (all Bioformats data formats are supported) and click "Run PyCalibrate" to start processing. Once complete, the processed data is available to download as either a PDF or CSV file. You can create multiple 'Projects' to allow you keep track of each of your microscopes. Your data files are stored on our cloud-based platform to allow you to track imaging performance over time.
To begin, enter your details below to register. You will then be sent a verification email that you can use to log in and start creating your projects. We hope you enjoy using this new feature. Please see the user guide and introductory video below for more information. As always, we would love to hear from you, so please contact us through .
Purpose: This guide will help you to get started with PyCalibrate and begin automated analysis of your calibration data. The results delivered by PyCalibrate have been rigorously tested against existing free-to-use solutions (e.g. PSFJ and MetroloJ) to ensure they are accurate and consistent.
1. Register for an account
From the “Menu” option above, select “Register” (see 2, Figure 1). Enter your details and click “Register”. An email from will automatically be sent to the address you entered to enable you to confirm your PyCalibrate account. Click the “Confirm my account” link to confirm your account. If you have not received a confirmation email within 10 minutes, select “Confirm account” from the Menu and re-enter your e-mail address and click “Resend confirmation instructions”. It is also worth checking that the confirmation email from hasn’t ended up in a spam filter.
2. Create a project
To help you to organise your calibration files, you can create individual projects. How you do this is entirely up to you. For example, each project could be an individual microscope, or a specific microscope and objective lens combination (Figure 2).
3. Upload you data
Once you have created a project, click on “Choose files” to bring up a dialog box to select your calibration file. Once selected, click “Upload” to upload it to the cloud server. One the file has uploaded you will see two links appear. The raw data file you have just uploaded can be downloaded again by clicking the link with that filename (see 1, Figure 3). This can be useful for reviewing raw data at a later date. Clicking “Run PSF-Check” will run the PyCalibrate software on the raw data file.
The raw data file should only contain a single image stack (z-stack)
PyCalibrate supports all data formats currently supported by BioFormats
If the data file contains multiple colour channels, a report will be generated only for the first colour channel (i.e. the lowest index in the colour channel stack).
After clicking “Run PSF-Check” you will get a pop-up telling you that the data has been submitted. Click “OK”. A message also appears inviting you to refresh the webpage to see your results (Figure 4).
It will typically take 2-5 minutes to process the data.
Refreshing your screen before the results are ready returns the “Run PSF-Check” link – you do not need to click this link again. Simply refresh the page again later on.
Once the results are ready you will see a new “Results” link.
4. Download your results
PyCalibrate offers three different ways of viewing your results. Each of these can be downloaded directly by clicking on the link. The first is a PDF file summarising the appearance of the calibration data, average values across the field of view and the individual fitting values for each detected point. The second and third files are in CSV format; the first containing fitting values for each of the individual points in the field of view, the second containing fitting values averaged across all points in the field of view.
The PDF file begins with filename of the raw data file and the date and time of data processing (Figure 6). On the right is an image of the raw data, showing a maximum intensity projection together with overlays showing which features have been detected and the order in which they appear in the “Raw fit data” table.
Please note: If PyCalibrate has not been able to successfully extract the X, Y or Z pixel dimensions from the image metadata, the parameter value will show as “NA”.
The PDF file continues with an “Average values” summary table containing the averages for all of the features detected across the field of view (Figure 7). The first column shows the parameter measured, the second the average value in nm and the third column shows the average parameter value in pixels, together with ±1 (sigma) uncertainty values. The confidence in the fitting is given by the R^2 values (maximum value of 1).
Q1. PyCalibrate has been processing for > 10 minutes and the results are still not showing.
A1. It is likely that the software has identified a large number of false points and is processing them all to extract dimensions for each point found. To avoid this happening again, ensure that the signal to noise ratio (or more exactly, the signal to background ratio) is sufficiently high (>10) and that the sampling rate is high enough (<100 nm/pixel). See Figure 8 for target values. More recently an upper limit has been placed on the number of points which can be detected within the field of view. If more than 200 points are detected then PyCalibrate will return a blank PDF explaining the error.
For a brief introduction to the motivation behind PyCalibrate and what it can do, click on the video below for a 5 minute summary: