Remove unused functions in utils.py

- Fix mypy errors

e3sm_diags/derivations/formulas_cosp.py

@@ -117,14 +117,14 @@ def cosp_histogram_standardize(
 
     # Align the dataset dimensions with the standardized variabe. `xr.align`
     # returns both objects and element 0 is the xr.Dataset that is needed.
-    ds_final: xr.Dataset = xr.align(ds_new, var_std)[0]  # type: ignore
+    ds_final = xr.align(ds_new, var_std)[0]
     ds_final[target_var_key] = var_std
     ds_final = ds_final.drop_vars(str(var.name))
 
     # TODO: These functions don't actually add missing cloud bounds yet
     # because it is based on the logic from the legacy code, which does not
     # correctly add bounds if they are missing.
-    ds_final = _add_missing_cloud_bnds(ds_final, prs, "prs")
+    ds_final = _add_missing_cloud_bnds(ds_final, prs, "prs")  # type: ignore
     ds_final = _add_missing_cloud_bnds(ds_final, tau, "tau")
 
     return ds_final

e3sm_diags/derivations/utils.py

@@ -2,16 +2,9 @@
 This module defines general utilities for deriving variables, including unit
 conversion functions, renaming variables, etc.
 """
-from typing import TYPE_CHECKING, Optional, Tuple
-
-import MV2
 import xarray as xr
 from genutil import udunits
 
-if TYPE_CHECKING:
-    from cdms2.axis import FileAxis
-    from cdms2.fvariable import FileVariable
-
 
 def rename(new_name: str):
     """Given the new name, just return it."""
@@ -87,6 +80,7 @@ def convert_units(var: xr.DataArray, target_units: str):  # noqa: C901
     elif var.attrs["units"] in ["gN/m^2/day", "gP/m^2/day", "gC/m^2/day"]:
         pass
     else:
+        # FIXME: Replace genutil.udunits module.
         temp = udunits(1.0, var.attrs["units"])
         coeff, offset = temp.how(target_units)
 
@@ -123,121 +117,3 @@ def _apply_land_sea_mask(
     masked_var = var.where(cond=cond, drop=False)
 
     return masked_var
-
-
-def adjust_prs_val_units(
-    prs: "FileAxis", prs_val: float, prs_val0: Optional[float]
-) -> float:
-    """Adjust the prs_val units based on the prs.id"""
-    # FIXME: Refactor this function to operate on xr.Dataset/xr.DataArray.
-    # COSP v2 cosp_pr in units Pa instead of hPa as in v1
-    # COSP v2 cosp_htmisr in units m instead of km as in v1
-    adjust_ids = {"cosp_prs": 100, "cosp_htmisr": 1000}
-
-    if prs_val0:
-        prs_val = prs_val0
-        if prs.id in adjust_ids.keys() and max(prs.getData()) > 1000:
-            prs_val = prs_val * adjust_ids[prs.id]
-
-    return prs_val
-
-
-def determine_cloud_level(
-    prs_low: float,
-    prs_high: float,
-    low_bnds: Tuple[int, int],
-    high_bnds: Tuple[int, int],
-) -> str:
-    """Determines the cloud type based on prs values and the specified boundaries"""
-    # Threshold for cloud top height: high cloud (<440hPa or > 7km), midlevel cloud (440-680hPa, 3-7 km) and low clouds (>680hPa, < 3km)
-    if prs_low in low_bnds and prs_high in high_bnds:
-        return "middle cloud fraction"
-    elif prs_low in low_bnds:
-        return "high cloud fraction"
-    elif prs_high in high_bnds:
-        return "low cloud fraction"
-    else:
-        return "total cloud fraction"
-
-
-def cosp_bin_sum(
-    cld: "FileVariable",
-    prs_low0: Optional[float],
-    prs_high0: Optional[float],
-    tau_low0: Optional[float],
-    tau_high0: Optional[float],
-):
-    # FIXME: Refactor this function to operate on xr.Dataset/xr.DataArray.
-    """sum of cosp bins to calculate cloud fraction in specified cloud top pressure / height and
-    cloud thickness bins, input variable has dimension (cosp_prs,cosp_tau,lat,lon)/(cosp_ht,cosp_tau,lat,lon)
-    """
-    prs: FileAxis = cld.getAxis(0)
-    tau: FileAxis = cld.getAxis(1)
-
-    prs_low: float = adjust_prs_val_units(prs, prs[0], prs_low0)
-    prs_high: float = adjust_prs_val_units(prs, prs[-1], prs_high0)
-
-    if prs_low0 is None and prs_high0 is None:
-        prs_lim = "total cloud fraction"
-
-    tau_high, tau_low, tau_lim = determine_tau(tau, tau_low0, tau_high0)
-
-    if cld.id == "FISCCP1_COSP":  # ISCCP model
-        cld_bin = cld(cosp_prs=(prs_low, prs_high), cosp_tau=(tau_low, tau_high))
-        simulator = "ISCCP"
-    if cld.id == "CLISCCP":  # ISCCP obs
-        cld_bin = cld(isccp_prs=(prs_low, prs_high), isccp_tau=(tau_low, tau_high))
-
-    if cld.id == "CLMODIS":  # MODIS
-        prs_lim = determine_cloud_level(prs_low, prs_high, (440, 44000), (680, 68000))
-        simulator = "MODIS"
-
-        if prs.id == "cosp_prs":  # Model
-            cld_bin = cld(
-                cosp_prs=(prs_low, prs_high), cosp_tau_modis=(tau_low, tau_high)
-            )
-        elif prs.id == "modis_prs":  # Obs
-            cld_bin = cld(modis_prs=(prs_low, prs_high), modis_tau=(tau_low, tau_high))
-
-    if cld.id == "CLD_MISR":  # MISR model
-        if max(prs) > 1000:  # COSP v2 cosp_htmisr in units m instead of km as in v1
-            cld = cld[
-                1:, :, :, :
-            ]  # COSP v2 cosp_htmisr[0] equals to 0 instead of -99 as in v1, therefore cld needs to be masked manually
-        cld_bin = cld(cosp_htmisr=(prs_low, prs_high), cosp_tau=(tau_low, tau_high))
-        prs_lim = determine_cloud_level(prs_low, prs_high, (7, 7000), (3, 3000))
-        simulator = "MISR"
-    if cld.id == "CLMISR":  # MISR obs
-        cld_bin = cld(misr_cth=(prs_low, prs_high), misr_tau=(tau_low, tau_high))
-
-    cld_bin_sum = MV2.sum(MV2.sum(cld_bin, axis=1), axis=0)
-
-    try:
-        cld_bin_sum.long_name = simulator + ": " + prs_lim + " with " + tau_lim
-        # cld_bin_sum.long_name = "{}: {} with {}".format(simulator, prs_lim, tau_lim)
-    except BaseException:
-        pass
-    return cld_bin_sum
-
-
-def determine_tau(
-    tau: "FileAxis", tau_low0: Optional[float], tau_high0: Optional[float]
-):
-    # FIXME: Refactor this function to operate on xr.Dataset/xr.DataArray.
-    tau_low = tau[0]
-    tau_high = tau[-1]
-
-    if tau_low0 is None and tau_high0:
-        tau_high = tau_high0
-        tau_lim = "tau <" + str(tau_high0)
-    elif tau_high0 is None and tau_low0:
-        tau_low = tau_low0
-        tau_lim = "tau >" + str(tau_low0)
-    elif tau_low0 is None and tau_high0 is None:
-        tau_lim = str(tau_low) + "< tau < " + str(tau_high)
-    else:
-        tau_low = tau_low0
-        tau_high = tau_high0
-        tau_lim = str(tau_low) + "< tau < " + str(tau_high)
-
-    return tau_high, tau_low, tau_lim