Define, update, and validate your model's parameters.
Install using pip:
pip install paramtools
Install using conda:
conda install -c conda-forge paramtools
Subclass paramtools.Parameters
and define your model's parameters:
import paramtools
class Params(paramtools.Parameters):
defaults = {
"schema": {
"labels": {
"date": {
"type": "date",
"validators": {
"range": {
"min": "2020-01-01",
"max": "2021-01-01",
"step": {"months": 1}
}
}
}
},
},
"a": {
"title": "A",
"type": "int",
"value": [
{"date": "2020-01-01", "value": 2},
{"date": "2020-10-01", "value": 8},
],
"validators": {
"range" : {
"min": 0, "max": "b"
}
}
},
"b": {
"title": "B",
"type": "float",
"value": [{"date": "2020-01-01", "value": 10.5}]
}
}
Access values using .sel
:
params = Params()
params.sel["a"]
Values([ {'date': datetime.date(2020, 1, 1), 'value': 2}, {'date': datetime.date(2020, 10, 1), 'value': 8}, ])
Look up parameter values using a pandas-like api:
from datetime import date
result = params.sel["a"]["date"] == date(2020, 1, 1)
result
QueryResult([ {'date': datetime.date(2020, 1, 1), 'value': 2} ])
result.isel[0]["value"]
2
Add a new value:
params.adjust({"a": [{"date": "2020-11-01", "value": 22}]})
params.sel["a"]
Values([ {'date': datetime.date(2020, 1, 1), 'value': 2}, {'date': datetime.date(2020, 10, 1), 'value': 8}, {'date': datetime.date(2020, 11, 1), 'value': 22}, ])
Update an existing value:
params.adjust({"a": [{"date": "2020-01-01", "value": 3}]})
params.sel["a"]
Values([ {'date': datetime.date(2020, 1, 1), 'value': 3}, {'date': datetime.date(2020, 10, 1), 'value': 8}, {'date': datetime.date(2020, 11, 1), 'value': 22}, ])
Update all values:
params.adjust({"a": 7})
params.sel["a"]
Values([ {'date': datetime.date(2020, 1, 1), 'value': 7}, {'date': datetime.date(2020, 10, 1), 'value': 7}, {'date': datetime.date(2020, 11, 1), 'value': 7}, ])
Errors on values that are out of range:
params.adjust({"a": -1})
--------------------------------------------------------------------------- ValidationError Traceback (most recent call last) <ipython-input-9-f8f1b7f6cd9a> in <module> ----> 1 params.adjust({"a": -1}) ~/Paramtools/paramtools/parameters.py in adjust(self, params_or_path, ignore_warnings, raise_errors, extend_adj, clobber) 253 least one existing value item's corresponding label values. 254 """ --> 255 return self._adjust( 256 params_or_path, 257 ignore_warnings=ignore_warnings, ~/Paramtools/paramtools/parameters.py in _adjust(self, params_or_path, ignore_warnings, raise_errors, extend_adj, is_deserialized, clobber) 371 not ignore_warnings and has_warnings 372 ): --> 373 raise self.validation_error 374 375 # Update attrs for params that were adjusted. ValidationError: { "errors": { "a": [ "a -1 < min 0 " ] } }
params = Params()
params.adjust({"a": [{"date": "2020-01-01", "value": 11}]})
--------------------------------------------------------------------------- ValidationError Traceback (most recent call last) <ipython-input-10-cc8a21f044d8> in <module> 1 params = Params() 2 ----> 3 params.adjust({"a": [{"date": "2020-01-01", "value": 11}]}) ~/Paramtools/paramtools/parameters.py in adjust(self, params_or_path, ignore_warnings, raise_errors, extend_adj, clobber) 253 least one existing value item's corresponding label values. 254 """ --> 255 return self._adjust( 256 params_or_path, 257 ignore_warnings=ignore_warnings, ~/Paramtools/paramtools/parameters.py in _adjust(self, params_or_path, ignore_warnings, raise_errors, extend_adj, is_deserialized, clobber) 371 not ignore_warnings and has_warnings 372 ): --> 373 raise self.validation_error 374 375 # Update attrs for params that were adjusted. ValidationError: { "errors": { "a": [ "a[date=2020-01-01] 11 > max 10.5 b[date=2020-01-01]" ] } }
Errors on invalid values:
params = Params()
params.adjust({"b": "abc"})
--------------------------------------------------------------------------- ValidationError Traceback (most recent call last) <ipython-input-11-8373a2715e38> in <module> 1 params = Params() 2 ----> 3 params.adjust({"b": "abc"}) ~/Paramtools/paramtools/parameters.py in adjust(self, params_or_path, ignore_warnings, raise_errors, extend_adj, clobber) 253 least one existing value item's corresponding label values. 254 """ --> 255 return self._adjust( 256 params_or_path, 257 ignore_warnings=ignore_warnings, ~/Paramtools/paramtools/parameters.py in _adjust(self, params_or_path, ignore_warnings, raise_errors, extend_adj, is_deserialized, clobber) 371 not ignore_warnings and has_warnings 372 ): --> 373 raise self.validation_error 374 375 # Update attrs for params that were adjusted. ValidationError: { "errors": { "b": [ "Not a valid number: abc." ] } }
Extend values using label_to_extend
:
params = Params(label_to_extend="date")
params.sel["a"]
Values([ {'date': datetime.date(2020, 1, 1), 'value': 2}, {'date': datetime.date(2020, 2, 1), 'value': 2, '_auto': True}, {'date': datetime.date(2020, 3, 1), 'value': 2, '_auto': True}, {'date': datetime.date(2020, 4, 1), 'value': 2, '_auto': True}, {'date': datetime.date(2020, 5, 1), 'value': 2, '_auto': True}, {'date': datetime.date(2020, 6, 1), 'value': 2, '_auto': True}, {'date': datetime.date(2020, 7, 1), 'value': 2, '_auto': True}, {'date': datetime.date(2020, 8, 1), 'value': 2, '_auto': True}, {'date': datetime.date(2020, 9, 1), 'value': 2, '_auto': True}, {'date': datetime.date(2020, 10, 1), 'value': 8}, {'date': datetime.date(2020, 11, 1), 'value': 8, '_auto': True}, {'date': datetime.date(2020, 12, 1), 'value': 8, '_auto': True}, {'date': datetime.date(2021, 1, 1), 'value': 8, '_auto': True}, ])
Updates to values are carried through to future dates:
params.adjust({"a": [{"date": "2020-4-01", "value": 9}]})
params.sel["a"]
Values([ {'date': datetime.date(2020, 1, 1), 'value': 2}, {'date': datetime.date(2020, 2, 1), 'value': 2, '_auto': True}, {'date': datetime.date(2020, 3, 1), 'value': 2, '_auto': True}, {'date': datetime.date(2020, 4, 1), 'value': 9}, {'date': datetime.date(2020, 5, 1), 'value': 9, '_auto': True}, {'date': datetime.date(2020, 6, 1), 'value': 9, '_auto': True}, {'date': datetime.date(2020, 7, 1), 'value': 9, '_auto': True}, {'date': datetime.date(2020, 8, 1), 'value': 9, '_auto': True}, {'date': datetime.date(2020, 9, 1), 'value': 9, '_auto': True}, {'date': datetime.date(2020, 10, 1), 'value': 9, '_auto': True}, {'date': datetime.date(2020, 11, 1), 'value': 9, '_auto': True}, {'date': datetime.date(2020, 12, 1), 'value': 9, '_auto': True}, {'date': datetime.date(2021, 1, 1), 'value': 9, '_auto': True}, ])
Use clobber
to only update values that were set automatically:
params = Params(label_to_extend="date")
params.adjust(
{"a": [{"date": "2020-4-01", "value": 9}]},
clobber=False,
)
# Sort parameter values by date for nicer output
params.sort_values()
params.sel["a"]
Values([ {'date': datetime.date(2020, 1, 1), 'value': 2}, {'date': datetime.date(2020, 2, 1), 'value': 2, '_auto': True}, {'date': datetime.date(2020, 3, 1), 'value': 2, '_auto': True}, {'date': datetime.date(2020, 4, 1), 'value': 9}, {'date': datetime.date(2020, 5, 1), 'value': 9, '_auto': True}, {'date': datetime.date(2020, 6, 1), 'value': 9, '_auto': True}, {'date': datetime.date(2020, 7, 1), 'value': 9, '_auto': True}, {'date': datetime.date(2020, 8, 1), 'value': 9, '_auto': True}, {'date': datetime.date(2020, 9, 1), 'value': 9, '_auto': True}, {'date': datetime.date(2020, 10, 1), 'value': 8}, {'date': datetime.date(2020, 11, 1), 'value': 8, '_auto': True}, {'date': datetime.date(2020, 12, 1), 'value': 8, '_auto': True}, {'date': datetime.date(2021, 1, 1), 'value': 8, '_auto': True}, ])
Access values as NumPy arrays with array_first
:
params = Params(label_to_extend="date", array_first=True)
params.a
array([2, 2, 2, 2, 2, 2, 2, 2, 2, 8, 8, 8, 8])
params.a * params.b
array([21., 21., 21., 21., 21., 21., 21., 21., 21., 84., 84., 84., 84.])
Only get the values that you want:
arr = params.to_array("a", date=["2020-01-01", "2020-11-01"])
arr
array([2, 8])
Go back to a list of dictionaries:
params.from_array("a", arr, date=["2020-01-01", "2020-11-01"])
[{'date': datetime.date(2020, 1, 1), 'value': 2}, {'date': datetime.date(2020, 11, 1), 'value': 8}]
Full documentation available at paramtools.dev.
Contributions are welcome! Checkout CONTRIBUTING.md to get started.
ParamTools is built on top of the excellent marshmallow JSON schema and validation framework. I encourage everyone to check out their repo and documentation. ParamTools was modeled off of Tax-Calculator's parameter processing and validation engine due to its maturity and sophisticated capabilities.