welltest_pta.DeconvolutionResult

class welltest_pta.DeconvolutionResult[source]

Bases: object

Output of deconvolve().

Parameters:
__init__(t, pu, dpu_dlnt, z, p_initial, nu, converged, iterations, residual_norm, fit_pressure, obs_pressure, obs_time, rate_history, metadata=<factory>)
Parameters:
Return type:

None

Methods

__init__(t, pu, dpu_dlnt, z, p_initial, nu, ...)

export(path[, format])

Save the response to CSV / Excel / JSON.

plot([ax, show_obs_fit])

Log-log plot of the recovered \(p_u\) and its derivative.

to_dataframe()

Long-form DataFrame of the recovered response.

Attributes

t

pu

dpu_dlnt

z

p_initial

nu

converged

iterations

residual_norm

fit_pressure

obs_pressure

obs_time

rate_history

metadata

t: ndarray
pu: ndarray
dpu_dlnt: ndarray
z: ndarray
p_initial: float
nu: float
converged: bool
iterations: int
residual_norm: float
fit_pressure: ndarray
obs_pressure: ndarray
obs_time: ndarray
rate_history: DataFrame
metadata: dict
to_dataframe()[source]

Long-form DataFrame of the recovered response.

Return type:

DataFrame

export(path, format='csv')[source]

Save the response to CSV / Excel / JSON.

Parameters:
Return type:

None

plot(ax=None, show_obs_fit=False)[source]

Log-log plot of the recovered \(p_u\) and its derivative.

Parameters:
__init__(t, pu, dpu_dlnt, z, p_initial, nu, converged, iterations, residual_norm, fit_pressure, obs_pressure, obs_time, rate_history, metadata=<factory>)
Parameters:
Return type:

None