COP quickstart

Two ways to compute COP in CEDAR: Climate & Energy Diagnostics for Applied Refrigeration:

  1. a fast, vectorized class for ambient temperature fields, and

  2. a minimal “single state” helper for one operating point.

Tip

For a longer, figure-heavy tutorial adapted from cedar.ipynb, see Cedar walkthrough.

1) Vectorized workflow — SingleFluidCOP

from cedar.metrics.cop import SingleFluidCOP

hp = SingleFluidCOP(
    "R134a",
    t_evap_k=273.15,
    delta_t_cond=10,
    eta_is=0.8,
    delta_t_min=10.0,
)

print(hp.cop(298.15))                # single value (K)
print(hp.cop([280, 290, 300]))       # vectorized over an array
hp.plot(show=True)                   # quick reference plot
# Or save instead of showing:
# hp.plot(show=False, save_path="outputs/r134a_cop.png", dpi=300)

Note

SingleFluidCOP builds a dense lookup table once (CoolProp sweep) and then returns fast interpolated values for arbitrary 1–3D arrays of ambient temperature.

2) Single state helper — cop_single

from cedar.physics.cop import cop_single

cop = cop_single("R134a", t_evap_k=273.15, t_cond_k=295.0, eta_is=0.8)
print(cop)  # returns NaN if the state is unphysical

Warning

cop_single is intentionally minimal: no input validation, plotting, or logging. Use it inside higher-level code that handles those concerns.

Notes & tips

  • Refrigerant names are validated against CoolProp (in the vectorized class).

  • Unphysical conditions (e.g., t_cond_k <= t_evap_k or too small lift) return NaN.

  • Temperatures are Kelvin. If you think in °C, use T[K] = T[°C] + 273.15.

SHR quickstart

Compute Sensible Heat Ratio (SHR) using temperature plus either relative humidity or dew point.

SHR vs temperature and relative humidity

Example SHR map for temperature (x) and relative humidity (y) with 0.1 contours.

from cedar.metrics.shr import SensibleHeatRatioModel

shr_model = SensibleHeatRatioModel(
    p_atm=101_325.0,
    t_evap_k=273.15,
    approach_temp=1.0,
    C_p=1020.05,
    H_fg=2.501e6,
    rh_out=1.0,
)

# Dew point path (dew point -> RH -> SHR)
temps_K = [295.0, 300.0]
dewpoint_K = [283.15, 288.15]
shr = shr_model.shr(temps_K, dewpoint_array=dewpoint_K)
print(shr)  # e.g., [0.704..., 0.62...]

# Or provide relative humidity directly
rh = [0.47, 0.65]
shr_direct = shr_model.shr(temps_K, rh_array=rh)

If you pass both rh_array and dewpoint_array, or neither, the model raises a ValueError to prevent ambiguous inputs.

See also the runnable scripts in examples/:

  • examples/cop_example.py for COP basics

  • examples/shr_example.py for SHR via RH or dew point

  • examples/effective_cop_example.py for ECOP (COP × SHR) using COP/SHR kwargs

ECOP quickstart (COP × SHR)

Compute effective COP by combining COP and SHR models.

from cedar.metrics.effective_cop import EffectiveCOP

ecop_model = EffectiveCOP(
    cop_kwargs=dict(
        fluid="R134a",
        t_evap_k=273.15,
        delta_t_cond=10,
        eta_is=0.8,
        delta_t_min=10.0,
    ),
    shr_kwargs=dict(
        p_atm=101_325.0,
        t_evap_k=273.15,
        approach_temp=1.0,
        C_p=1020.05,
        H_fg=2.501e6,
        rh_out=1.0,
    ),
)

temps_K = [295.0, 300.0]
dewpoint_K = [283.15, 288.15]
ecop_vals = ecop_model.ecop(temps_K, dewpoint_array=dewpoint_K)
print(ecop_vals)  # COP × SHR

Note

Keep COP and SHR assumptions aligned (e.g., same evaporator temperature, approach temperature, outlet RH) so ECOP and eCDD reflect one operating point.

CDD & eCDD quickstart

  • CDD (hourly exceedance):

from cedar.metrics.cdd import CoolingDegreeDays

cdd = CoolingDegreeDays(base_temperature_K=18.0 + 273.15)
temps_K = [290.0, 293.0, 296.0]
exceed = cdd.cdd(temps_K)
print(exceed)

  • eCDD (CDD / eCOP):

from cedar.metrics.effective_cdd import EffectiveCDD

ecdd_model = EffectiveCDD(
    cop_kwargs=dict(
        fluid="R134a",
        t_evap_k=273.15,
        delta_t_cond=10,
        eta_is=0.8,
        delta_t_min=10.0,
    ),
    shr_kwargs=dict(
        p_atm=101_325.0,
        t_evap_k=273.15,
        approach_temp=1.0,
        C_p=1020.05,
        H_fg=2.501e6,
        rh_out=1.0,
    ),
    cdd_kwargs=dict(base_temperature_K=18.0 + 273.15),
)

temps_K = [295.0, 300.0]
dewpoint_K = [283.15, 288.15]
ecdd_vals = ecdd_model.ecdd(temps_K, dewpoint_array=dewpoint_K)
print(ecdd_vals)