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Merged
pnorton-usgs merged 7 commits into from
May 11, 2026
Merged

Clean up and modernize parameters directory #53

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acecdda
Remove ParameterSet.py (entirely commented-out dead code)
pnorton-usgs May 11, 2026
0f5511a
Modernize type hints across parameters directory
pnorton-usgs May 11, 2026
ab26b42
Replace __getattr__ with explicit collection interface in Parameters
pnorton-usgs May 11, 2026
418c29f
Rename __parameters_to_dict to _parameters_to_dict in MetaData
pnorton-usgs May 11, 2026
0033687
Remove commented-out dead code from parameter files
pnorton-usgs May 11, 2026
1819096
Minor improvements to Parameter.py
pnorton-usgs May 11, 2026
2e6c91c
Protect parameters property with MappingProxyType
pnorton-usgs May 11, 2026
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8 changes: 4 additions & 4 deletions pyPRMS/metadata/metadata.py
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Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ def __init__(self, version: str | Version = PRMS_VERSION,

fcn_map = {'control': self.__control_to_dict,
'dimensions': self.__dimensions_to_dict,
'parameters': self.__parameters_to_dict,
'parameters': self._parameters_to_dict,
'variables': self.__variables_to_dict,
'data_file': self.__data_file_to_dict,
'cbh': self.__cbh_to_dict}
Expand Down Expand Up @@ -250,9 +250,9 @@ def __control_to_dict(self, xml_root: xmlET.Element,

return meta_dict

def __parameters_to_dict(self, xml_root: xmlET.Element,
meta_type: str,
req_version: Version) -> dict:
def _parameters_to_dict(self, xml_root: xmlET.Element,
meta_type: str,
req_version: Version) -> dict:
"""Convert parameter metadata to dictionary.

:param xml_root: XML root element
Expand Down
13 changes: 7 additions & 6 deletions pyPRMS/parameters/ParamDb.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,8 @@
from __future__ import annotations

import os
import pandas as pd # type: ignore
from typing import cast, Optional
from typing import cast

from ..constants import PRMS_VERSION
from ..Exceptions_custom import ParameterNotValidError
Expand All @@ -17,7 +18,7 @@
class ParamDb(Parameters):
def __init__(self, paramdb_dir: str,
metadata,
verbose: Optional[bool] = False):
verbose: bool = False):
"""Initialize ParamDb object.

This object handles the monolithic parameter database.
Expand All @@ -26,7 +27,7 @@ def __init__(self, paramdb_dir: str,
:param verbose: Output additional debug information
"""

super(ParamDb, self).__init__(metadata=metadata, verbose=verbose)
super().__init__(metadata=metadata, verbose=verbose)

global con
con = get_console_instance()
Expand Down Expand Up @@ -59,9 +60,9 @@ def _read(self):

# Create a MetaData object to use its parameter parsing function
mobj = MetaData()
pvt_meta = mobj._MetaData__parameters_to_dict(xml_root=params_root,
meta_type='parameters',
req_version=PRMS_VERSION)
pvt_meta = mobj._parameters_to_dict(xml_root=params_root,
meta_type='parameters',
req_version=PRMS_VERSION)

# Populate parameterSet with all available parameter names
for param in params_root.findall('parameter'):
Expand Down
116 changes: 31 additions & 85 deletions pyPRMS/parameters/Parameter.py
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Original file line number Diff line number Diff line change
@@ -1,24 +1,22 @@
from __future__ import annotations

import functools
import numpy as np
import numpy.typing as npt
import pandas as pd # type: ignore
from typing import Any, cast, Dict, List, NamedTuple, Optional, Union
from collections.abc import ValuesView
from typing import Any, cast, NamedTuple
import xml.etree.ElementTree as xmlET

from ..base.console import get_console_instance
from ..constants import NEW_PTYPE_TO_DTYPE
from ..dimensions.Dimensions import ParamDimensions
from ..Exceptions_custom import FixedDimensionError

# from rich.console import Console
# from rich import pretty
#
# pretty.install()
# con = Console(force_jupyter=False)
con = None

ParamDataRawType = Union[npt.NDArray, np.int32, np.float32, np.float64, np.str_]
ParamDataType = Union[npt.NDArray, np.int32, np.float32, np.float64, np.str_, int, float, str]
ParamDataRawType = npt.NDArray | np.int32 | np.float32 | np.float64 | np.str_
ParamDataType = npt.NDArray | np.int32 | np.float32 | np.float64 | np.str_ | int | float | str


class Outliers(NamedTuple):
Expand All @@ -29,10 +27,10 @@ class Outliers(NamedTuple):

class Stats(NamedTuple):
name: str
min: Optional[npt.DTypeLike]
max: Optional[npt.DTypeLike]
mean: Optional[npt.DTypeLike]
median: Optional[npt.DTypeLike]
min: npt.DTypeLike | None
max: npt.DTypeLike | None
mean: npt.DTypeLike | None
median: npt.DTypeLike | None


class Parameter(object):
Expand All @@ -44,10 +42,10 @@ class Parameter(object):

# Container for a single parameter
def __init__(self, name: str,
meta: Optional[Dict] = None,
meta: dict | None = None,
global_dims=None,
strict: Optional[bool] = True,
verbose: Optional[bool] = False):
strict: bool = True,
verbose: bool = False):
"""
Initialize a parameter object.

Expand Down Expand Up @@ -86,9 +84,16 @@ def __init__(self, name: str,
# The meta must be supplied as an adhoc dictionary
self.meta = meta

self.__data: Optional[ParamDataRawType] = None
self.__data: ParamDataRawType | None = None
self.__modified = False

def __repr__(self) -> str:
"""String representation of the Parameter object.

:return: string with parameter name and dimensions
"""
return f"Parameter(name='{self.name}')"

def __str__(self) -> str:
"""Pretty-print string representation of the parameter information.

Expand Down Expand Up @@ -245,7 +250,7 @@ def dimensions(self) -> ParamDimensions:
return self.__dimensions

@property
def index_map(self) -> Union[Dict[Any, int], None]:
def index_map(self) -> dict[Any, int] | None:
"""Returns an ordered dictionary which maps data values of a 1D array
to index positions.

Expand All @@ -260,7 +265,7 @@ def index_map(self) -> Union[Dict[Any, int], None]:
return None

@property
def is_scalar(self):
def is_scalar(self) -> bool:
try:
return 'one' in self.meta['dimensions']
except KeyError:
Expand All @@ -275,7 +280,7 @@ def modified(self) -> bool:
return self.__modified

@property
def modules(self) -> List[str]:
def modules(self) -> list[str]:
"""Returns the names of the PRMS modules that require the parameter.

:returns: names of PRMS modules that require the parameter
Expand All @@ -301,16 +306,6 @@ def ndim(self) -> int:
else:
return self.__dimensions.ndim

# @property
# def size(self) -> int:
# """Return the total size of the parameter for the defined dimensions.
#
# :returns total size of parameter dimensions"""
# arr_shp = [dd.size for dd in self.dimensions.dimensions.values()]
#
# # Compute the total size of the parameter
# return functools.reduce(lambda x, y: x * y, arr_shp)

@property
def xml(self) -> xmlET.Element:
"""Return the xml metadata for the parameter as an xml Element.
Expand Down Expand Up @@ -355,7 +350,6 @@ def check_values(self) -> bool:

:returns: true when all values are within the valid min/max range for the parameter
"""
# if self.__data is not None:
minval = self.meta.get('minimum', None)
maxval = self.meta.get('maximum', None)

Expand Down Expand Up @@ -409,7 +403,6 @@ def outliers(self) -> Outliers:

:returns: NamedTuple containing count of values less than and values greater than valid range
"""
# Outliers = namedtuple('Outliers', ['name', 'under', 'over'])

values_under = 0
values_over = 0
Expand All @@ -422,13 +415,13 @@ def outliers(self) -> Outliers:

return Outliers(self.__name, values_under, values_over)

def remove_by_index(self, dim_name: str, indices: List[int]):
def remove_by_index(self, dim_name: str, indices: list[int]):
"""Remove columns (nhru or nsegment) from data array given a list of indices.

:param dim_name: Name of dimension to reduce
:param indices: List of indices to remove"""

if isinstance(indices, type(dict().values())):
if isinstance(indices, ValuesView):
indices = list(indices)

if self.__data is not None:
Expand All @@ -441,58 +434,11 @@ def remove_by_index(self, dim_name: str, indices: List[int]):
else:
raise TypeError('Parameter data is not initialized')

# def reshape(self, new_dims: Dict):
# """Reshape a parameter, broadcasting existing values as necessary.
#
# :param new_dims: Dimension names and sizes that will be used to reshape the parameter data
# """
#
# if self.__data is None:
# # Reshape has no meaning if there is no data to reshape
# return
#
# if self.dimensions.ndim == 1:
# if 'one' in self.dimensions.keys():
# # Reshaping from a scalar to a 1D or 2D array
# # print('Scalar to 1D or 2D')
# new_sizes = [vv.size for vv in new_dims.values()]
# tmp_data = np.broadcast_to(self.__data, new_sizes)
#
# # Remove the original dimension
# self.dimensions.remove('one')
#
# # Add the new ones
# for kk, vv in new_dims.items():
# self.dimensions.add(kk, vv.size)
#
# self.__data = tmp_data
# elif set(self.dimensions.keys()).issubset(set(new_dims.keys())):
# # Reschaping a 1D to a 2D
# if len(new_dims) == 1:
# print('ERROR: Cannot reshape from 1D array to 1D array')
# else:
# # print('1D array to 2D array')
# new_sizes = [vv.size for vv in new_dims.values()]
# try:
# tmp_data = np.broadcast_to(self.__data, new_sizes)
# except ValueError:
# # operands could not be broadcast together with remapped shapes
# tmp_data = np.broadcast_to(self.__data, new_sizes[::-1]).T
#
# old_dim = list(self.dimensions.keys())[0]
# self.dimensions.remove(old_dim)
#
# for kk, vv in new_dims.items():
# self.dimensions.add(kk, vv.size)
#
# self.__data = tmp_data

def stats(self) -> Stats:
"""Returns basic statistics on parameter values.

:returns: None (for strings or no data) or NamedTuple containing min, max, mean, and median of parameter values
"""
# Stats = namedtuple('Stats', ['name', 'min', 'max', 'mean', 'median'])

try:
return Stats(self.__name, np.min(self.data_raw), np.max(self.data_raw),
Expand All @@ -507,7 +453,7 @@ def subset_by_index(self, dim_name: str, indices):
:param dim_name: name of dimension
:param indices: local indices of HRUs or segments to extract"""

if isinstance(indices, type(dict().values())):
if isinstance(indices, ValuesView):
indices = list(indices)

if self.dimensions[dim_name].is_fixed:
Expand All @@ -522,7 +468,7 @@ def subset_by_index(self, dim_name: str, indices):
assert self.data_raw is not None # Needed so mypy doesn't fail on next line
self.dimensions[dim_name].size = self.data_raw.shape[dim_idx]

def tolist(self) -> List[Union[int, float, str]]:
def tolist(self) -> list[int | float | str]:
"""Returns the parameter data as a list.

:returns: Parameter data
Expand Down Expand Up @@ -572,14 +518,14 @@ def tostructure(self) -> dict:
'data': self.tolist()}
return param

def unique(self) -> Optional[npt.NDArray]:
def unique(self) -> npt.NDArray | None:
"""Create array of unique values from the parameter data.

:returns: Array of unique values
"""
return np.unique(self.data_raw)

def update_element(self, index: int, value: Union[int, float, List[int], List[float]]):
def update_element(self, index: int, value: int | float | list[int] | list[float]):
"""Update single value or row of values (e.g. nhru by nmonths) for a
given local zero-based index in the parameter data array.

Expand Down Expand Up @@ -634,7 +580,7 @@ def update_element(self, index: int, value: Union[int, float, List[int], List[fl
self.__data[index] = value # type: ignore
self.__modified = True

def _value_index_1d(self, value: Union[int, float, str]) -> npt.NDArray:
def _value_index_1d(self, value: int | float | str) -> npt.NDArray:
"""Given a scalar value return the indices where there is a match.

:param value: The value to find in the parameter data array
Expand Down
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