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format all functions and methods according to pep8
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@martinvonk
martinvonk committed Jan 9, 2023
1 parent d04bd68 commit fdae4a0
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Showing 21 changed files with 1,058 additions and 371 deletions.
8 changes: 6 additions & 2 deletions pastas/io/men.py
View file
Expand Up @@ -19,8 +19,12 @@ def load(fname: str) -> NotImplementedError:
"reads-section for a Menyanthes-read")


def dump(fname: str, data: dict, version: int = 3, verbose: bool = True) -> None:
# version can also be a specific version, like '2.x.g.t (beta)', or an integer (see below)
def dump(fname: str,
data: dict,
version: int = 3,
verbose: bool = True) -> None:
# version can also be a specific version,
# like '2.x.g.t (beta)', or an integer (see below)
if version == 3:
version = '3.x.b.c (gamma)'
elif version == 2:
Expand Down
184 changes: 132 additions & 52 deletions pastas/model.py
View file
Expand Up @@ -145,7 +145,9 @@ def __repr__(self):
const=not self.constant is None,
noise=not self.noisemodel is None)

def add_stressmodel(self, stressmodel: StressModel, replace: bool = False) -> None:
def add_stressmodel(self,
stressmodel: StressModel,
replace: bool = False) -> None:
"""Add a stressmodel to the main model.
Parameters
Expand Down Expand Up @@ -304,8 +306,12 @@ def del_noisemodel(self) -> None:
self.noisemodel = None
self.parameters = self.get_init_parameters(initial=False)

def simulate(self, p: Optional[ArrayLike] = None, tmin: Optional[TimestampType] = None,
tmax: Optional[TimestampType] = None, freq: Optional[str] = None, warmup: Optional[float] = None,
def simulate(self,
p: Optional[ArrayLike] = None,
tmin: Optional[TimestampType] = None,
tmax: Optional[TimestampType] = None,
freq: Optional[str] = None,
warmup: Optional[float] = None,
return_warmup: bool = False) -> Series:
"""Method to simulate the time series model.
Expand Down Expand Up @@ -396,9 +402,12 @@ def simulate(self, p: Optional[ArrayLike] = None, tmin: Optional[TimestampType]
sim.name = 'Simulation'
return sim

def residuals(
self, p: Optional[ArrayLike] = None, tmin: Optional[TimestampType] = None, tmax: Optional[TimestampType] = None,
freq: Optional[str] = None, warmup: Optional[float] = None) -> Series:
def residuals(self,
p: Optional[ArrayLike] = None,
tmin: Optional[TimestampType] = None,
tmax: Optional[TimestampType] = None,
freq: Optional[str] = None,
warmup: Optional[float] = None) -> Series:
"""Method to calculate the residual series.
Parameters
Expand Down Expand Up @@ -467,9 +476,12 @@ def residuals(
res.name = "Residuals"
return res

def noise(
self, p: Optional[ArrayLike] = None, tmin: Optional[TimestampType] = None, tmax: Optional[TimestampType] = None,
freq: Optional[str] = None, warmup: Optional[float] = None) -> Series:
def noise(self,
p: Optional[ArrayLike] = None,
tmin: Optional[TimestampType] = None,
tmax: Optional[TimestampType] = None,
freq: Optional[str] = None,
warmup: Optional[float] = None) -> Series:
"""Method to simulate the noise when a noisemodel is present.
Parameters
Expand Down Expand Up @@ -526,9 +538,12 @@ def noise(
noise = self.noisemodel.simulate(res, p)
return noise

def noise_weights(
self, p: Optional[list] = None, tmin: Optional[TimestampType] = None, tmax: Optional[TimestampType] = None,
freq: Optional[str] = None, warmup: Optional[float] = None) -> ArrayLike:
def noise_weights(self,
p: Optional[list] = None,
tmin: Optional[TimestampType] = None,
tmax: Optional[TimestampType] = None,
freq: Optional[str] = None,
warmup: Optional[float] = None) -> ArrayLike:
"""Internal method to calculate the noise weights."""
# Get parameters if none are provided
if p is None:
Expand All @@ -542,9 +557,11 @@ def noise_weights(

return weights

def observations(
self, tmin: Optional[TimestampType] = None, tmax: Optional[TimestampType] = None, freq: Optional[str] = None,
update_observations: bool = False) -> Series:
def observations(self,
tmin: Optional[TimestampType] = None,
tmax: Optional[TimestampType] = None,
freq: Optional[str] = None,
update_observations: bool = False) -> Series:
"""Method that returns the observations series used for calibration.
Parameters
Expand Down Expand Up @@ -605,10 +622,15 @@ def observations(
oseries_calib = self.oseries_calib
return oseries_calib

def initialize(
self, tmin: Optional[TimestampType] = None, tmax: Optional[TimestampType] = None, freq: Optional[str] = None,
warmup: Optional[float] = None, noise: Optional[bool] = None, weights: Optional[Series] = None, initial:
bool = True, fit_constant: bool = True) -> None:
def initialize(self,
tmin: Optional[TimestampType] = None,
tmax: Optional[TimestampType] = None,
freq: Optional[str] = None,
warmup: Optional[float] = None,
noise: Optional[bool] = None,
weights: Optional[Series] = None,
initial: bool = True,
fit_constant: bool = True) -> None:
"""Method to initialize the model.
This method is called by the solve-method, but can also be
Expand Down Expand Up @@ -662,10 +684,18 @@ def initialize(
self.parameters.loc["constant_d", "initial"] = 0.0
self.normalize_residuals = True

def solve(
self, tmin: Optional[TimestampType] = None, tmax: Optional[TimestampType] = None, freq: Optional[str] = None,
warmup: Optional[float] = None, noise: bool = True, solver: Optional[Solver] = None, report: bool = True,
initial: bool = True, weights: Optional[Series] = None, fit_constant: bool = True, **kwargs) -> None:
def solve(self,
tmin: Optional[TimestampType] = None,
tmax: Optional[TimestampType] = None,
freq: Optional[str] = None,
warmup: Optional[float] = None,
noise: bool = True,
solver: Optional[Solver] = None,
report: bool = True,
initial: bool = True,
weights: Optional[Series] = None,
fit_constant: bool = True,
**kwargs) -> None:
"""Method to solve the time series model.
Parameters
Expand Down Expand Up @@ -766,9 +796,14 @@ def solve(
output = None
print(self.fit_report(output=output))

def set_parameter(
self, name: str, initial: Optional[float] = None, vary: Optional[bool] = None, pmin: Optional[float] = None,
pmax: Optional[float] = None, optimal: Optional[float] = None, move_bounds: bool = False) -> None:
def set_parameter(self,
name: str,
initial: Optional[float] = None,
vary: Optional[bool] = None,
pmin: Optional[float] = None,
pmax: Optional[float] = None,
optimal: Optional[float] = None,
move_bounds: bool = False) -> None:
"""Method to change the parameter properties.
Parameters
Expand Down Expand Up @@ -881,7 +916,12 @@ def _get_time_offset(self, freq: str) -> Timedelta:
else:
return Timedelta(0)

def _get_sim_index(self, tmin: Timestamp, tmax: Timestamp, freq: str, warmup: Timedelta, update_sim_index: bool = False) -> DatetimeIndex:
def _get_sim_index(self,
tmin: Timestamp,
tmax: Timestamp,
freq: str,
warmup: Timedelta,
update_sim_index: bool = False) -> DatetimeIndex:
"""Internal method to get the simulation index, including the warmup.
Parameters
Expand Down Expand Up @@ -923,8 +963,10 @@ def _get_sim_index(self, tmin: Timestamp, tmax: Timestamp, freq: str, warmup: Ti
sim_index = self.sim_index
return sim_index

def get_tmin(
self, tmin: Optional[TimestampType] = None, use_oseries: bool = True, use_stresses: bool = False) -> Timestamp:
def get_tmin(self,
tmin: Optional[TimestampType] = None,
use_oseries: bool = True,
use_stresses: bool = False) -> Timestamp:
"""Method that checks and returns valid values for tmin.
Parameters
Expand Down Expand Up @@ -982,8 +1024,10 @@ def get_tmin(

return tmin

def get_tmax(
self, tmax: Optional[TimestampType] = None, use_oseries: bool = True, use_stresses: bool = False) -> Timestamp:
def get_tmax(self,
tmax: Optional[TimestampType] = None,
use_oseries: bool = True,
use_stresses: bool = False) -> Timestamp:
"""Method that checks and returns valid values for tmax.
Parameters
Expand Down Expand Up @@ -1044,7 +1088,9 @@ def get_tmax(

return tmax

def get_init_parameters(self, noise: Optional[bool] = None, initial: bool = True) -> DataFrame:
def get_init_parameters(self,
noise: Optional[bool] = None,
initial: bool = True) -> DataFrame:
"""Method to get all initial parameters from the individual objects.
Parameters
Expand Down Expand Up @@ -1141,10 +1187,15 @@ def get_stressmodel_settings(self, name: str) -> Union[dict, None]:
return settings

@get_stressmodel
def get_contribution(
self, name: str, tmin: Optional[TimestampType] = None, tmax: Optional[TimestampType] = None,
freq: Optional[str] = None, warmup: Optional[float] = None, istress: Optional[int] = None,
return_warmup: bool = False, p: Optional[ArrayLike] = None) -> Series:
def get_contribution(self,
name: str,
tmin: Optional[TimestampType] = None,
tmax: Optional[TimestampType] = None,
freq: Optional[str] = None,
warmup: Optional[float] = None,
istress: Optional[int] = None,
return_warmup: bool = False,
p: Optional[ArrayLike] = None) -> Series:
"""Method to get the contribution of a stressmodel.
Parameters
Expand Down Expand Up @@ -1247,7 +1298,9 @@ def get_contributions(self, split: bool = True, **kwargs) -> List[Series]:
return contribs

def get_transform_contribution(
self, tmin: Optional[TimestampType] = None, tmax: Optional[TimestampType] = None) -> Series:
self,
tmin: Optional[TimestampType] = None,
tmax: Optional[TimestampType] = None) -> Series:
"""Method to get the contribution of a transform.
Parameters
Expand All @@ -1271,9 +1324,11 @@ def get_transform_contribution(
sim_org = ml.simulate(tmin=tmin, tmax=tmax)
return sim - sim_org

def get_output_series(
self, tmin: Optional[TimestampType] = None, tmax: Optional[TimestampType] = None, add_contributions: bool = True,
split: bool = True) -> DataFrame:
def get_output_series(self,
tmin: Optional[TimestampType] = None,
tmax: Optional[TimestampType] = None,
add_contributions: bool = True,
split: bool = True) -> DataFrame:
"""Method to get all the modeled output time series from the Model.
Parameters
Expand Down Expand Up @@ -1324,9 +1379,13 @@ def get_output_series(
df = concat(df, axis=1)
return df

def _get_response(
self, block_or_step: str, name: str, p: Optional[ArrayLike] = None, dt: Optional[float] = None, add_0:
bool = False, **kwargs) -> Series:
def _get_response(self,
block_or_step: str,
name: str,
p: Optional[ArrayLike] = None,
dt: Optional[float] = None,
add_0: bool = False,
**kwargs) -> Series:
"""Internal method to compute the block and step response.
Parameters
Expand Down Expand Up @@ -1381,8 +1440,12 @@ def _get_response(
return response

@get_stressmodel
def get_block_response(self, name: str, p: Optional[ArrayLike] = None, add_0: bool = False, dt: Optional[float] = None, **
kwargs) -> Series:
def get_block_response(self,
name: str,
p: Optional[ArrayLike] = None,
add_0: bool = False,
dt: Optional[float] = None,
**kwargs) -> Series:
"""Method to obtain the block response for a stressmodel.
The optimal parameters are used when available, initial otherwise.
Expand Down Expand Up @@ -1411,8 +1474,12 @@ def get_block_response(self, name: str, p: Optional[ArrayLike] = None, add_0: bo
p=p, add_0=add_0, **kwargs)

@get_stressmodel
def get_step_response(
self, name, p: Optional[ArrayLike] = None, add_0: bool = False, dt: Optional[float] = None, **kwargs) -> Series:
def get_step_response(self,
name,
p: Optional[ArrayLike] = None,
add_0: bool = False,
dt: Optional[float] = None,
**kwargs) -> Series:
"""Method to obtain the step response for a stressmodel.
The optimal parameters are used when available, initial otherwise.
Expand Down Expand Up @@ -1440,7 +1507,10 @@ def get_step_response(
p=p, add_0=add_0, **kwargs)

@get_stressmodel
def get_response_tmax(self, name: str, p: ArrayLike = None, cutoff: float = 0.999) -> float:
def get_response_tmax(self,
name: str,
p: ArrayLike = None,
cutoff: float = 0.999) -> float:
"""Method to get the tmax used for the response function.
Parameters
Expand Down Expand Up @@ -1477,9 +1547,16 @@ def get_response_tmax(self, name: str, p: ArrayLike = None, cutoff: float = 0.99
return tmax

@get_stressmodel
def get_stress(self, name: str, tmin: Optional[TimestampType] = None, tmax: Optional[TimestampType] = None,
freq: Optional[str] = None, warmup: Optional[float] = None, istress: Optional[int] = None,
return_warmup: bool = False, p: Optional[ArrayLike] = None) -> Union[Series, List[Series]]:
def get_stress(
self,
name: str,
tmin: Optional[TimestampType] = None,
tmax: Optional[TimestampType] = None,
freq: Optional[str] = None,
warmup: Optional[float] = None,
istress: Optional[int] = None,
return_warmup: bool = False,
p: Optional[ArrayLike] = None) -> Union[Series, List[Series]]:
"""Method to obtain the stress(es) from the stressmodel.
Parameters
Expand Down Expand Up @@ -1569,7 +1646,10 @@ def _get_file_info(self) -> dict:

return file_info

def fit_report(self, output: str = "basic", warnings: bool = True, warnbounds: Optional[bool] = None) -> str:
def fit_report(self,
output: str = "basic",
warnings: bool = True,
warnbounds: Optional[bool] = None) -> str:
"""Method that reports on the fit after a model is optimized.
Parameters
Expand Down

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