CALPHAD tools for designing thermodynamic models, calculating phase diagrams and investigating phase equilibria.
Or do you expect me to actually test my code before i make a PR?! :-D
I'll see if I can quickly add an action that will run on PRs and get that merged into develop, then we can rebase #292 onto develop
#293 should enable CI to run on PRs. Just verifying that the test pass and then I'll merge into develop
looks good
@dschwen you should be able to rebase #292 onto develop now (now at commit
8ed33ba) and that should trigger the tests to run our GitHub Actions workflow. Thank you for your patience! We're still learning the ins-and-outs of GitHub Actions and refining our test and CI stack.
ah well, looks like the sizes are all hardcoded...
by default the ternary plot tick labels are too small to be used in a publication. Looks like we need a bit of customizability. I wonder if a good approach could be to just scale relative to
font.size...
that way not another slew of parameters needs to be added and propagated through function calls
@dschwen Looks like there is some information here: https://matplotlib.org/3.1.1/tutorials/introductory/customizing.html
## note that font.size controls default text sizes. To configure
## special text sizes tick labels, axes, labels, title, etc, see the rc
## settings for axes and ticks. Special text sizes can be defined
## relative to font.size, using the following values: xx-small, x-small,
## small, medium, large, x-large, xx-large, larger, or smaller
The lack of a good default stylesheet for our plots is definitely a gap.
but that requires me to also patch
ax.set_ylabel(_axis_label(y), position=(0.18,0.45), fontsize=2*base_font_size)adding a hard coded position for the y axis label (the one on the slanted upper axis in the triangle). Otherwise labels collide, and labelpad does not do anything
I would suggest that you do something like this:
%matplotlib inline
from pycalphad import Database, eqplot, equilibrium, variables as v
import matplotlib.pyplot as plt
dbf = Database("Cr-Fe-Ni_Miettinen.tdb")
comps = ['CR', 'FE', 'NI', 'VA']
phases = sorted(dbf.phases.keys())
conditions = {v.N: 1, v.P: 101325, v.T: 1000, v.X('NI'): (0.0, 1.0, 0.1), v.X('CR'): (0.0, 1.0, 0.1)}
eq = equilibrium(dbf, comps, phases, conditions)
# plot the result
fig = plt.figure(dpi=200)
ax = fig.gca(projection='triangular')
eqplot(eq, x=v.X('CR'), y=v.X('NI'), ax=ax)
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width, box.height])
ax.tick_params(axis='both', which='major', labelsize=8, pad=10000)
ax.grid(True)
plot_title = '-'.join([component.title() for component in sorted(comps) if component != 'VA'])
ax.set_title(plot_title, fontsize=16)
ax.set_xlabel('X(CR)', fontsize=10, labelpad=8)
ax.set_ylabel('X(NI)', fontsize=10, labelpad=5)You can pass in your own axes and set all the parameters after the fact.
I'm seeing an issue where the
triangular projection seems to break the pad argument for ax.tick_params (it has no effect). Othat than that, you can set everything except the parameters for the lines outside of ternplot/eqplot.
you can probably supply a transform for the tick labels
git blame has me on the hook for all that code, but I have no recollection of writing it. It's several years old, so it's unclear whether it worked at some point and broke or whether it never worked.
It's from this paper by Miettinen: https://doi.org/10.1016/S0364-5916(99)00027-9. It will show up if you search the TDBDB for "Cr,Fe,Ni". This particular TDB file was constructed from the paper and is hosted by NIMS, which requires you to register (it's free).
thanks for sharing directly
Hi everybody! I understand that the scripting in python is very powerful, but has anyone started an initiative to create a GUI for it? It can be 100% done in python, i'm experienced in pyqt and can help. This way i believe we can reach out to an even broader audience. What do you think?
@fernando109_gitlab I did some prototyping using ipywidgets earlier this year, where the concept was something like a 'wizard' which would guide the user through a common calculation type and provide the corresponding Python code as output. You can see the idea here: https://github.com/pycalphad/binder/blob/builder_test/Builder.ipynb - it may or may not actually run on Binder as-is, but it should be possible to execute the notebook locally using Voila to see the output
Also, for analyzing the results of equilibrium calculations and building charts/plots, I've had a little luck using dtale: https://github.com/man-group/dtale - you can import the xarray objects in directly. The automatic subgrouping isn't very advanced yet though, and there are some UI bugs. I don't recommend dtale for general pycalphad use at this time, but perhaps as a starting point for future extensions
You'll notice all of these are browser-based UIs. I've tended to gravitate toward those approaches because you can deploy them in / next to Jupyter. So it doesn't matter if it's local, or on Binder, or your own JupyterHub deployment, etc. With the new Jupyter Server core project ( https://github.com/jupyter-server/jupyter_server ) arbitrary web UIs can be integrated into Jupyter, and I'm bullish on that approach long-term
I'm open to a pyqt approach, but I'd want to hear solutions to the multi-OS package distribution problem before I invested much of my own time into it. Python apps (especially ones with Cython extensions, like pycalphad) are so hard to package consistently, and you end up with something that is not close to the native desktop experience
If you're interested in exploring (in my opinion) the future of Python-based data science GUIs, I'd take a look at Dash: https://github.com/plotly/dash - you can use it to build GUIs entirely from Python, but it also integrates really nicely with the JS framework React. It's what dtale was built on top of. If someone wanted to explore forking dtale's chart builder to build a 'pycalphad GUI', I would make time available for that person during my office hours (the limit of what I can promise outright, but potentially other opportunities too)