Property diagrams and psychrometric charts for engineering thermodynamics, with CoolProp as the source of every property: log(p)-h, T-s, h-s, p-s, p-rho, T-rho and p-T diagrams for pure fluids and refrigerant blends, cycles drawn on top of them, and psychrometric charts for humid air.

from coolplot import PropertyDiagram
from coolplot.thermo.cycles import simple_compression

diagram = PropertyDiagram("R290", "ph", units="engineering", tp_limits="ACHP")
diagram.set_default_lines(labels=True, rounding=True)
diagram.add_cycle(simple_compression("R290", T_evap_C=-5, T_cond_C=45, dT_sh_K=5))
diagram.save("R290_ph.png")           # or .pdf, .svg; show() opens a window

Cycles can be given state by state in the chart's units, by two properties or by the process that leads to a state:

diagram.add_cycle("Heat pump", [
    {"p": 3.0, "T": 0.0},                               # 1 compressor inlet, bar and deg C
    {"p": 15.0, "via": "compression", "eta_is": 0.7},   # 2 compressor outlet
    {"p": 15.0, "Q": 0.0},                              # 3 condenser outlet
    {"p": 3.0, "via": "isenthalpic"},                   # 4 after the valve
])

What else it does:

• Isoline labels sit at the edges of the chart, as on printed charts, and keep clear of the cycles.
• Blends: the dome from CoolProp's phase envelope, the temperature glide inside it, a chart in seconds.
• Units: SI, kPa and kJ, deg C and bar, or inch-pound; a change of units costs no new calculation.
• Output: PNG and PDF through matplotlib (fonts embedded, texts kept as text, several charts per file), SVG with no dependencies, plotly figures and HTML pages, live charts in a web page.
• Interactive: zoom, hover and dragging of cycle states in matplotlib and in a web page; only what changed is recomputed and redrawn; lines can be computed in the background.

The documentation (getting started, tutorials, how-to pages, the API reference and a gallery of the examples) is built from docs/ and published on Read the Docs; make docs builds it locally.

The code was forked from the main CoolProp repository at v6.3.0 with its history preserved, hence the old commits. Version 0.2 replaced the legacy API (from CoolPlot.Plot import PropertyPlot); the upgrade guide in the documentation gives the equivalents, and pip install "coolplot<0.2" keeps the last legacy release. From 1.0 to 2.0 the public API is stable.

Pull requests are encouraged!

The project gets published on PyPi as coolplot and you can install it using pip

pip install coolplot                # core, includes the SVG backend
pip install "coolplot[matplotlib]"  # with the matplotlib backend

This Python package is released under the terms of the MIT license.