EPICS is a flexible and powerful controls system that gives access to experimental information, however, the relation and meaning of process variables is often obscure. Many of the user interfaces for EPICS information reflect this, as walls of buttons and flashing lights bombard the user with little thought to structure or cohesion.
Typhos addresses this by providing an automated way to generate screens based on a provided hierarchy of devices and signals. Built using PyDM, a PyQt based display manager developed at SLAC National Laboratory, Typhos utilizes a large toolkit of widgets to display EPICS information. For each process variable, a corresponding widget is created based on; the importance to the average operator, the type of value the EPICS PV will return, and whether a user should be allowed to write to the variable. These widgets are then placed in a convenient tab-based system to only show the necessary information for basic function, but still allow access to more advanced signals.
Instead of reinventing a new way to specify device structures, Typhos uses
Ophyd
, a library to abstract EPICS information into consistently structured
Python objects. Originally built for scripting experimental procedures at
NSLSII, Ophyd represents devices as combinations of components which are
either signals or nested devices. Then, either at runtime or by using the
defaults of the representative Python class, these signals are sorted into
different categories based on their relevance to operators. Typhos uses this
information to craft user interfaces.
Recommended installation on Linux:
conda install typhos -c conda-forge -c pcds-tag
All -tag
channels have -dev
counterparts for bleeding edge installations.
Both requirements.txt
and optional dev-requirements.txt
are kept up to date
as well for those who prefer installation via pip
typhos utilizes PyDM's designer widget entrypoints. This means that if you have PyDM working correctly with the Qt Designer, typhos widgets will also be available. No further customization or environment settings are required.
happi
is an optional dependency but is recommended. This must be installed
manually if not using the CONDA recipe.
There have been some observed inconsistencies between installations of Qt
available on pip
, defaults
and conda-forge
. It is recommended that if you
want to use the full typhos
feature to install via conda-forge
. We have
found this the most reliable, especially when it comes to using the
QtDesigner
. It is worth noting that since this library uses qtpy
as an
interface layer to the various options for Qt Python bindings, the bare
requirements will not install a specific one for you. The testing suite runs
using PyQt5
.
Creating your first typhos
panel for anophyd.Device
only takes two
lines:
import sys
from ophyd.sim import motor
from qtpy.QtWidgets import QApplication
import typhos
# Create our application
app = QApplication.instance() or QApplication(sys.argv)
typhos.use_stylesheet() # Optional
suite = typhos.TyphosSuite.from_device(motor)
# Launch
suite.show()
app.exec_()
Typhos has three major building blocks that combine into the final display seen by the operator:
TyphosSuite
: The overall view for a Typhos window. It allows the
operator to view all of the loaded components and tools
TyphosDeviceDisplay
: This is the widget created for a standard
ophyd.Device
. Signals are organized based on their
Kind
and description.
typhos.tools
: These are widgets that interface with external
applications. While you may have other GUIs for these systems,
typhos.tools
are built especially to handle the handshaking between all the
information stored on your device and the tool you are interfacing with. This
saves your operator clicks and ensures consistency in use.
All three of the widgets listed above share a similar API for creation.
Instantiating the object by itself handles loading the container widgets and
placing them in the correct place, but these do not accept ophyd.Device
arguments. The reason for this is to ensure that we can use all of the
typhos
screens as templates, and regardless or not of whether you have an
ophyd.Device
you can always populate the screens by hand. If you do in fact
have an ophyd.Device
every class has an add_device
method and
alternatively and be constructed using the from_device
classmethod.
PyDM - PyQT Display Manager for EPICS information
Ophyd - Device abstraction for Experimental Control