Timeseries
Utilities for time series
GravityTimeSeries
Bases: TimeSeries
A time series of gravity values
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
obj
|
Series | DataFrame
|
Input data, see :class: |
required |
height
|
float
|
Measurement height, in meters. |
None
|
vgg
|
float
|
Vertical gravity gradient, in nm/s² per meter. |
None
|
has_error
property
True, if column of error values exists
meta
property
Dict of meta attibutes
y
property
Main value column
y_err
property
Error value column
adev(taus='auto', mrate=None)
chunks(freq='1D')
Itervate over time series by intervals
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
freq
|
str
|
Duration of time intervals, e. g. "1D" for day intervals. |
'1D'
|
Yields:
| Type | Description |
|---|---|
TimeSeries
|
Segment of this time series |
mask(*args, **kwargs)
Mask samples by a condition and return as new TimeSeries
mean()
Mean, standard deviation and standard error of the mean
Mean, standard deviation and SEM are weighted, if the time series has an error column. See weighted_mean.
Returns:
| Name | Type | Description |
|---|---|---|
mean |
float
|
Mean value. |
std |
float
|
Standard deviation. |
sem |
float
|
Standard error of the mean. |
mean_std()
Mean gravity value with standard deviation as error
Returns:
| Type | Description |
|---|---|
AbsGValue
|
Absolute gravity value. |
plot(fmt=None, ax=None, y0=None, **kwargs)
Plot gravity time series
plot_adev(mrate=None, ax=None, **kwargs)
Plot the Allan deviation
plot_chunks(freq='1D', ylim=None, **kwargs)
Plot time series in chunks
plot_mean(sem=False, std=False, y0=None, ax=None, **kwargs)
Plot mean, standard deviation and standard error of the mean (SEM)
resample(interval, min_count=None, err='sem', **kwargs)
Resample time series to new interval duration
See interval_means().
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
interval
|
str
|
Resampling interval, e.g. "1h". |
required |
min_count
|
int | float
|
Minimum number of samples required in interval. Intervals with fewer samples are evaluated as NaN. |
None
|
err
|
str
|
Statistical function to use for error column. Options are "sem" (standard error of the mean) and "std" (standard deviation). |
'sem'
|
kwargs
|
dict
|
Keyword arguments to be updated on resulting TimeSeries. Unspecified keywords are inherited. |
{}
|
Returns:
| Type | Description |
|---|---|
TimeSeries
|
Time series of resampled data. |
std()
Standard deviation
to_csv(path, float_format='%.2f', **kwargs)
Save to a CSV file
transfer(h)
Transfer to another height using VGG
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
h
|
float
|
New height, in meters. |
required |
Returns:
| Type | Description |
|---|---|
GravityTimeSeries
|
Height transferred gravity data. |
TimeSeries
A wrapper of pandas.Series for time series
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
obj
|
(Series, DataFrame)
|
Input data object with a time index. When passing a
pandas.DataFrame, it is expected to have a data column |
required |
**kwargs
|
dict
|
Optional keyword arguments to be used for plotting. |
{}
|
has_error
property
True, if column of error values exists
meta
property
Dict of meta attibutes
y
property
Main value column
y0
property
Plot y-axis offset
y_err
property
Error value column
adev(taus='auto', mrate=None)
chunks(freq='1D')
Itervate over time series by intervals
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
freq
|
str
|
Duration of time intervals, e. g. "1D" for day intervals. |
'1D'
|
Yields:
| Type | Description |
|---|---|
TimeSeries
|
Segment of this time series |
mask(*args, **kwargs)
Mask samples by a condition and return as new TimeSeries
mean()
Mean, standard deviation and standard error of the mean
Mean, standard deviation and SEM are weighted, if the time series has an error column. See weighted_mean.
Returns:
| Name | Type | Description |
|---|---|---|
mean |
float
|
Mean value. |
std |
float
|
Standard deviation. |
sem |
float
|
Standard error of the mean. |
plot(fmt=None, ax=None, y0=None, errorbars=True, min_count=None, **kwargs)
Plot
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
fmt
|
str
|
Plot style |
None
|
ax
|
Axes
|
Plot axes |
None
|
y0
|
float
|
Y-axis offset to be applied to data. Acquired from |
None
|
errorbars
|
bool
|
Plot errorbars, if possible. |
True
|
min_count
|
int | float
|
Minimum number of samples in an interval, given by column
|
None
|
kwargs
|
dict
|
Arguments to be passed to Matplotlib. |
{}
|
plot_adev(mrate=None, ax=None, **kwargs)
Plot the Allan deviation
plot_chunks(freq='1D', ylim=None, **kwargs)
Plot time series in chunks
plot_mean(sem=False, std=False, y0=None, ax=None, **kwargs)
Plot mean, standard deviation and standard error of the mean (SEM)
resample(interval, min_count=None, err='sem', **kwargs)
Resample time series to new interval duration
See interval_means().
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
interval
|
str
|
Resampling interval, e.g. "1h". |
required |
min_count
|
int | float
|
Minimum number of samples required in interval. Intervals with fewer samples are evaluated as NaN. |
None
|
err
|
str
|
Statistical function to use for error column. Options are "sem" (standard error of the mean) and "std" (standard deviation). |
'sem'
|
kwargs
|
dict
|
Keyword arguments to be updated on resulting TimeSeries. Unspecified keywords are inherited. |
{}
|
Returns:
| Type | Description |
|---|---|
TimeSeries
|
Time series of resampled data. |
std()
Standard deviation