Scipion can launch streaming workflows in several ways. The most basic one is achieved creating an empty project to start a new workflow with an Import Movies protocol pointing to the microscope’s deposition directory. Since we want to process the movies that are currently located at that directory but, also, those movies that are continuously arriving, we must activate the streaming mode in the streaming tab as shown in the figure below. Afterwards, the rest of the protocols can be added to the workflow in the same way that in the non streaming workflows (from the protocols tree at left of finding them with ctrl+F), but now all the protocols will wait for new data to process.
The two main parameters associated to the streaming mode are:
- Timeout: The time to wait, after not receiving new images, to close the acquisition.
- File timeout: Scipion is checking if a new file is growing up. If it do not change after this time, Scipion will consider that it is ready to be imported.
Usually the general timeout is a huge value (43,200 seconds = 12 hours) in order to prevent ending the acquisition in an eventual acquisition issue at the microscope side. Therefore, EM operator has this time to solve the issue.
When we know that the acquisition is finished, we can manually stop the online processing by selecting the Import Movies > right-click > STOP STREAMING. Then, all protocols will be finishing as soon as all the last data is being processed.
As any Scipion project, the directory placed at
$SCIPION_USER_DATA` usually is `~/ScipionUserData` and
``myAcquisitionProject is the project name to export) is a self contained
project directory and, then, it can be exported to any other computer
in order to continue with an user-assisted and more in-deep processing
by just coping this directory to the $SCIPION_USER_DATA/projects on the
other computer. Take into account that this directory usually doesn’t contain
the initial movies to save disk space (this behavior can be modified in the
Import Movies protocol).
The procedure of creating manual workflows by adding every protocol to use it might be tedious for a facility, where the same workflow will be usually employed for most users (or a small number of different workflows). For this reason, Scipion is able to automatically launch whole workflows by means of (at least) 3 ways:
- Launching static templates.
- Launching dynamic templates.
- Launching Python scripts using the Scipion’s API.
You can design a workflow by using Scipion GUI as usual. Adding an import, attaching some processing protocols, including the summary monitor… When you are happy with your workflow, you can export it by selecting all protocols that you want to export (ctrl+click to select more than one) and, then, click the Export button at top. You can save it as a template (a JSON file) at any directory on your system.
Additionally, Scipion has a public workflows repository at http://workflows.scipion.i2pc.es. The workflows are classified in different categories, such as Data Collection, 2D classification, 3D classification, Model Building… If you click on a certain workflow, you can see a preview of that workflow. Use the mouse-wheel to zoom in/out, click and drag in an empty zone to move and click on a box/protocol to inspect the internal parameters. You can download a certain workflow to any directory on you system. In addition, anyone can upload workflows (without any log up) by selecting all the protocols in your Scipion’s project and by clicking Export & Upload.
In order to launch any template (downloaded or made by yourself), open Scipion and create an empty project. Then, you can import the workflow with Project > Import Workflow at the menu bar on top and browsing to where the template is stored/downloaded (Scipion’s templates are JSON files). As the template is opened, the workflow is loaded to the project as saved protocols. At this point, you can check/modify any parameter of a certain protocol by opening the protocol form by right-click > Edit or double-click. When you are happy with all the parameters, store the protocol by clicking Save (do not click Execute/Schedule). When you are happy with all protocols, select the Import protocol, right-click > Restart workflow. Then, the Import should start to import data and the rest of the protocols should change to the Schedule mode. A scheduled protocol is waiting for ready inputs, i.e. when all inputs become ready for it, that protocol should automatically start to process the incoming data changing to the Running mode.
Alternatively, a JSON template can be launched from the command line as follow
scipion python pyworkflow/project/scripts/create.py name="myAcquisition" workflow="path/to/your/workflow.json" scipion python pyworkflow/project/scripts/schedule.py myAcquisition scipion project myAcquisition
where the first command creates the project named myAcquisition from the workflow.json file (in this case), the second starts the processing and the third opens the Scipion GUI to see the project.
Usually, we always must set the same parameters that are specific for each acquisition, such as deposition path, gain image path, dose per frame, particle size… Then, in order to avoid manually editing this parameters by opening every protocol in which belongs (using the procedure explained for the static templates in the previous section), Scipion has a mode to open modified templates in such a way that a wizard is launched asking for all that specific parameters, at once.
To see a demo of this you just have to run
This will pop up a small wizard like the one below
You can fill the form according to your data or just leave all the displayed fields untouched since it goes right with the test data (*see requirements below). As you click on the Start demo button, Scipion should appear with the new project loaded and running in streaming mode.
Import movies should already be importing files, whereas the rest should be scheduled. As soon as there is any input available for each protocol, that protocol will start processing it and making it available for the next protocol in line. Also, the Monitor summary should be monitoring the progress and generating an HTML report with the outcome of the data.
(*) Requirements for the demo:
To run the demo as it is, you need to have installed
scipion installp -p scipion-em-motioncorr -p scipion-em-grigoriefflab scipion-em-eman2
Notice that motioncor2 needs GPU acceleration.
In addition, the demo use either the jmbFalconMovies dataset for v1.2-Caligula version or the relion13_tutorial dataset for later versions (also for devel branch). Thus, you can download the dataset that you need by
scipion testdata --download jmbFalconMovies relion13_tutorial
Creating custom dynamic templates¶
The dynamic template explained above is just an example, but you can create your custom dynamic templates according with your preferences, system requirements/availability… using static templates (explained in the previous section above) as a starting points to create the dynamic ones.
A Scipion’s template is a JSON file, which are composed by a list of all the protocols in the workflow. In the figure below, we have highlight with a blue box the Import movies protocol part, where it has listed inside all the internal parameters/fields for the Import movies, such as the label, the files path, the voltage, the sampling rate… (underlined in yellow)
In a common JSON file, all fields are made of key-value pairs where key (what is before ‘:’) is always a string and the value (what is after ‘:’) can be a string (“something coated”), a number, a boolean (true or false), a list, a dictionary, a null… (more info).
Additionally, we have created a easy syntax to add dynamic fields to that JSON file. Then, to add a dynamic field, you only have to substitute the value (what is after the ‘:’) of a certain field for a string starting and ending by ‘~’, and with three strings separated by ‘|’, something like
where label will be the name for the filed in the form, defaultValue will be the default value inserted in that field and typeValue is a number fixing the type of the value (0 for strings, 1 for booleans, 2 for paths, 3 for integers, and 4 for floats).
In the figure above, there are three examples: the filesPath, dosePerFrame and gainFile fields (follow the arrows to see their behavior). In this case all three belongs to the same protocol. However there is no restriction in this way and, thus, you can add a dynamic field to any parameter to any protocol.
Notice that the type for the filesPath field is set to 2, which means path, then Scipion will check if this path exists before starting to process. gainFile is set to 0 (string) to allow an empty value (to skip using a gain image if not needed). Finally, the 4 (float type) set to the dosePerFrame allows to introduce non integer values.
When you are happy with the modified JSON file, you must save it to
where $SCIPION_HOME is where you have installed Scipion. The extension of this file must be .json.template. You can make as dynamic templates as you want by storing them in the mentioned directory with certain different file name as long as they finishes with .json.template.
When more than one dynamic template are found in the $SCIPION_HOME/pyworkflow/templates directory, then the command
opens a menu to choose the dynamic template to launch
Using Scipion’s API¶
A Scipion’s project can be created, designed (adding protocols) and launched by a Python script using the Scipion’s API.
We have a repository destined to share Scipion’s scripts potentially useful in EM-facilities. Specially, we have an example of creating a Scipion project using the API. See the acquisition simulation section to learn how to use this script.
Go to API workflows to see in detail how to make projects with a Python script.