Getting started

CEDAR: Climate & Energy Diagnostics for Applied Refrigeration links climate data to refrigeration physics and energy performance. Core metrics include:

• COP (vectorized, single-stage vapor-compression)

• SHR (dew point → RH or direct RH)

• ECOP = COP × SHR

• CDD and eCDD = CDD / (COP × SHR)

TL;DR (three lines)

from cedar.metrics.cop import SingleFluidCOP
from cedar.metrics.shr import SensibleHeatRatioModel
from cedar.metrics.effective_cop import EffectiveCOP

hp = SingleFluidCOP(
    "R134a",
    t_evap_k=273.15,
    delta_t_cond=10,
    eta_is=0.8,
    delta_t_min=10.0,
)
shr_model = SensibleHeatRatioModel()
ecop = EffectiveCOP(cop_model=hp, shr_model=shr_model)

hp.cop([280.0, 290.0, 300.0])             # COP array
shr_model.shr([295.0, 300.0], dewpoint_array=[283.0, 288.0])  # SHR
ecop.ecop([295.0, 300.0], dewpoint_array=[283.0, 288.0])      # ECOP

For a reference curve:

hp.plot(show=True)
# or: hp.plot(show=False, save_path="outputs/cop_chart.png")

Tip

Working with gridded climate fields? Pass a NumPy array of shape (lat, lon) or (time, lat, lon) directly to hp.cop(...).

What’s inside

src/
└── cedar/
    ├── metrics/            # High-level interfaces
    │   ├── cop.py          # COP models
    │   ├── shr.py          # SHR models
    │   ├── effective_cop.py# ECOP = COP × SHR
    │   ├── cdd.py          # Cooling Degree Days
    │   └── effective_cdd.py# eCDD = CDD / (COP × SHR)
    ├── physics/            # Core thermodynamic equations
    │   ├── cop.py
    │   └── shr.py
    ├── utils/              # Helpers
    │   ├── validation.py
    │   ├── interpolation.py
    │   └── plotting.py
    └── tests/
        ├── test_cop.py
        └── test_shr.py

Next steps

• Install the package (see Installation).

• Run tests to verify your environment:

  pytest --cov=cedar --cov-report=term-missing -v
  

• Browse examples in your README or tutorials to wire this into your pipeline.