gfdlvitals.extensions module

Pandas class extension for gfdlvitals

class gfdlvitals.extensions.Timeseries(f, var, scale=1.0, multiply_by_area=False, legacy_land=False, start=None, end=None)

Bases: object

Timeseries class object

Parameters

  • f (str, path-like) – Input SQLite file

  • var (str) – Variable to extract

  • scale (float, optional) – Scale data by this factor, by default 1.0

  • multiply_by_area (bool, optional) – Multiply variable by cell area before returning, by default False

  • legacy_land (bool, optional) – Read legacy version of the land SQLite files, by default False

  • start (int, optional) – Specify start year, by default None

  • end (int, optional) – Specify end year, by default None

class gfdlvitals.extensions.VitalsDataFrame(data=None, index: Optional[Collection] = None, columns: Optional[Collection] = None, dtype: Optional[Union[ExtensionDtype, str, numpy.dtype, Type[Union[str, float, int, complex, bool, object]]]] = None, copy: bool = False)

Bases: pandas.core.frame.DataFrame

Pandas class extension for holding the Vitals data

Parameters

pd (pandas.DataFrame) – Input Pandas DataFrame object

Returns

Class extension object

Return type

gfdlvitals.VitalsDataFrame

detrend(reference=None, order=1, anomaly=True, return_coefs=False)

Detrend VitalsDataFrame object

Parameters

  • reference (gfdlvitals.DataFrame, optional) – Reference VitalsDataFrame, by default None

  • order (int, optional) – Polynomial order to use for fitting, by default 1

  • anomaly (bool, optional) – Results as anomalies from the fit, by default True

  • return_coefs (bool, optional) – Return polynomial fit coeffiecients, by default False

Returns

Extended dataset

Return type

self

extend(maxlen)

Extend VitalsDataFrame to a set length and pad with NaNs

Parameters

maxlen (int) – New length of the VitalsDataFrame

Returns

Extended dataset

Return type

self

smooth(window, extrap=False)

Apply a smoother to the dataset

Parameters

  • window (int) – Smoothing filter length

  • extrap (bool, optional) – Extrapolate data on the ends, by default False

Returns

Smoothed dataset

Return type

self

trend(order=1)

Fits a trend to the VitalsDataFrame object

Parameters

order (int, optional) – Polynomial order to use for fitting, by default 1

Returns

Fitted trend dataset

Return type

self

ttest(df2)

Performs t-test between two instances of VitalsDataFrame

Parameters

df2 (VitalsDataFrame) – Comparison data set

Returns

Contains p-values for variables common between the two VitalsDataFrames

Return type

pandas.DataFrame

gfdlvitals.extensions.open_db(dbfile, variables=None, yearshift=0.0, legacy_land=False, start=None, end=None)

Function to read sqlite dbfile

gfdlvitals.extensions.reformat_time_axis(ax=None)

Reformats x-axis labels to YYYY format

Parameters

ax (matplotlob.pyplot.figure.axis, optional) – axis object to be reformatted, by default None

gfdlvitals.extensions.ttest_ind_auto(arr1, arr2, axis=0)

Performs a t-test that adjusts the degrees of freedom based on the autocorrelation of the dataset. See Krasting et al. 2013 for more details DOI: 10.1175/JCLI-D-12-00832.1

Parameters

  • arr1 (numpy.ndarray) – First array of data points

  • arr2 (numpy.ndarray) – Second array of data points

  • axis (int, optional) – Axis to perform t-test, by default 0

Returns

t-statistic, probability, arr1 autocorrelation, arr2 autocorrelation

Return type

tuple