neptoon.visulisation

figures¶

Functions:

validate_columns_present
make_nmdb_data_figure
uncorr_and_corr_neutrons_figure
soil_moisture_figure_uncertainty
soil_moisture_coloured_figure
atmospheric_conditions_figure
correction_factors_figure

Here are basic figures for creating plots.

validate_columns_present ¶

validate_columns_present(data_frame, required_cols)

Utility function to validate column existence in data frame Raises ValueError if columns are missing

make_nmdb_data_figure ¶

make_nmdb_data_figure(data_frame, reference_value, incoming_neutron_col_name=str(INCOMING_NEUTRON_INTENSITY), resolution=60, show=False, backend='agg', save_location=None)

Makes the figure

Parameters:

Name	Type	Description	Default
`data_frame`	`DataFrame`	DataFrame containing data	required
`nmdb_station_name`	`str`	NMDB station name	required
`reference_value`	`int`	reference value	required
`resolution`	`int`	resolution in minutes, by default 60	`60`
`show`	`bool`	show interactively, by default False	`False`
`backend`	`str`	the backend to use in matplotlib, by default "agg	`'agg'`
`save`	`str`	The save path	required

Returns:

Type	Description
`BytesIO`	Figure object to be used for later display

soil_moisture_figure_uncertainty ¶

soil_moisture_figure_uncertainty(data_frame, station_name, soil_moisture_col=str(SOIL_MOISTURE_VOL_FINAL), upper_uncertainty_col=str(SOIL_MOISTURE_UNCERTAINTY_VOL_UPPER), lower_uncertainty_col=str(SOIL_MOISTURE_UNCERTAINTY_VOL_LOWER), sm_range=(0, 0.5), show=False, backend='agg', save_location=None)

Creates a two-panel figure showing soil moisture content and associated uncertainties.

The top panel displays the soil moisture time series. The bottom panel shows the uncertainty bounds as separate lines with filled regions to emphasize the error margins.

Parameters:

Name	Type	Description	Default
`data_frame`	`DataFrame`	DataFrame containing the soil moisture and uncertainty data	required
`station_name`	`str`	Name of the CRNS station for the title	required
`soil_moisture_col`	`str`	Column name for soil moisture data, defaults to SOIL_MOISTURE_FINAL	`str(SOIL_MOISTURE_VOL_FINAL)`
`upper_uncertainty_col`	`str`	Column name for upper uncertainty bound	`str(SOIL_MOISTURE_UNCERTAINTY_VOL_UPPER)`
`lower_uncertainty_col`	`str`	Column name for lower uncertainty bound	`str(SOIL_MOISTURE_UNCERTAINTY_VOL_LOWER)`
`sm_range`	`tuple`	Y-axis range for soil moisture plots as (min, max), defaults to (0, 0.5)	`(0, 0.5)`
`show`	`bool`	Whether to display the figure, defaults to False	`False`
`backend`	`str`	Matplotlib backend to use, defaults to "agg"	`'agg'`
`save_location`	`str`	Path to save the figure, if None the figure is not saved	`None`

Returns:

Type	Description
`None`	The figure is either displayed, saved, or both based on parameters

soil_moisture_coloured_figure ¶

soil_moisture_coloured_figure(data_frame, station_name, sm_column_name=str(SOIL_MOISTURE_VOL_FINAL), lower_bound=0, save_location=None)

Soil moisture plot which fills below the line colours between blue and brown to represent wet vs dry periods.

Parameters:

Name	Type	Description	Default
`data_frame`	`DataFrame`	time series data	required
`station_name`	`str`	name of the station	required
`sm_column_name`	`str`	column name containing soil moisture data, by default str(ColumnInfo.Name.SOIL_MOISTURE_FINAL)	`str(SOIL_MOISTURE_VOL_FINAL)`
`lower_bound`	`float`	lower bound of y-axis, by default 0	`0`
`save_location`	`str`	location to save data if desired, by default None	`None`

atmospheric_conditions_figure ¶

atmospheric_conditions_figure(data_frame, station_name, pressure_col=str(AIR_PRESSURE), temperature_col=str(AIR_TEMPERATURE), rel_humidity_col=str(AIR_RELATIVE_HUMIDITY), temperature_range=(-20.0, 40.0), show=False, backend='agg', save_location=None)

Creates a three-panel figure showing atmospheric conditions affecting CRNS measurements.

Parameters:

Name	Type	Description	Default
`data_frame`	`DataFrame`	DataFrame containing the atmospheric measurements	required
`station_name`	`str`	Name of the CRNS station for the title	required
`pressure_col`	`str`	Column name for air pressure data (hPa)	`str(AIR_PRESSURE)`
`temperature_col`	`str`	Column name for air temperature data (°C)	`str(AIR_TEMPERATURE)`
`rel_humidity_col`	`str`	Column name for relative humidity data (%)	`str(AIR_RELATIVE_HUMIDITY)`
`abs_humidity_col`	`str`	Column name for absolute humidity data (g/m³)	required
`temperature_range`	`Tuple[float, float]`	Temperature axis range (min, max) in °C	`(-20.0, 40.0)`
`show`	`bool`	Whether to display the figure	`False`
`backend`	`str`	Matplotlib backend to use	`'agg'`
`save_location`	`str`	Path to save the figure	`None`

Notes

The function handles missing data gracefully - panels with no data will be left blank with an appropriate message. This is particularly useful for stations that may not record all atmospheric variables.

correction_factors_figure ¶

correction_factors_figure(data_frame, station_name, pressure_corr_col=str(PRESSURE_CORRECTION), humidity_corr_col=str(HUMIDITY_CORRECTION), intensity_corr_col=str(INTENSITY_CORRECTION), biomass_corr_col=str(ABOVEGROUND_BIOMASS_CORRECTION), show=False, backend='agg', save_location=None)

Creates a figure showing correction factors applied to CRNS data.

Parameters:

Name	Type	Description	Default
`data_frame`	`DataFrame`	DataFrame containing the correction factors and soil properties	required
`station_name`	`str`	Name of the CRNS station for the title	required
`pressure_corr_col`	`str`	Column name for pressure correction factor	`str(PRESSURE_CORRECTION)`
`humidity_corr_col`	`str`	Column name for humidity correction factor	`str(HUMIDITY_CORRECTION)`
`intensity_corr_col`	`str`	Column name for incoming neutron intensity correction	`str(INTENSITY_CORRECTION)`
`show`	`bool`	Whether to display the figure	`False`
`backend`	`str`	Matplotlib backend to use	`'agg'`
`save_location`	`str`	Path to save the figure	`None`