atiim package

Submodules

atiim.dem module

atiim.dem.create_basin_dem(basin_shp: str, dem_file: str, run_name: str, output_directory: Optional[str] = None) → str[source]

Mask the input DEM using a basin geometry representative of the contributing area.

Parameters

  • basin_shp (str) – Full path with file name and extension to the target basin shapefile

  • dem_file (str) – Full path with file name and extension to the input DEM raster file.

  • run_name (str) – Name of run, all lowercase and only underscore separated.

  • output_directory (Union[str, None]) – Full path to a write-enabled directory to write output files to

Returns

Full path with file name and extension to the masked DEM raster file

atiim.gage module

atiim.gage.import_gage_data(gage_data_file: str, date_field_name: str = 'DATE', time_field_name: str = 'TIME')[source]

Process gage data tabular file.

Parameters

  • gage_data_file (str) – Full path with file name and extension to the gage data file.

  • date_field_name (str) – Name of date field in file

  • time_field_name (str) – Name of time field in file

Returns

DataFrame of time series gage data sorted by date_time

atiim.gage.process_gage_data(gage_data_file: str, date_field_name: str = 'DATE', time_field_name: str = 'TIME', elevation_field_name: str = 'WL_ELEV_M', verbose: bool = False)[source]

Process gage data tabular file.

Parameters

  • gage_data_file (str) – Full path with file name and extension to the gage data file.

  • date_field_name (str) – Name of date field in file

  • time_field_name (str) – Name of time field in file

  • elevation_field_name (str) – Name of elevation field in file

  • verbose (bool) – Choice to log verbose description of file

Returns

[0] minumum water elevation in file [1] maximum water elevation in file [2] dictionary of water elevation frequency {elev: frequency}

atiim.hypsometric module

atiim.hypsometric.hypsometric_curve(dem_file: str, elevation_interval: float = 0.1, min_elevation: Optional[float] = None, max_elevation: Optional[float] = None) → pandas.core.frame.DataFrame[source]

Calculate a hypsometric curve as an elevation-area relationship assessment metric of the landform shape at a site. Provides basic metric of opportunity for inundation and habitat opportunity.

Parameters

  • dem_file (str) – Full path with file name and extension to the input digital elevation model raster

  • elevation_interval (float) – Elevation sample spacing in the units of the input DEM

  • min_elevation (float) – Optional. Minimum elevation to sample from. Default is to use the minimum elevation of the raster as a starting point.

  • max_elevation (float) – Optional. Maximum elevation to sample from. Default is to use the maximum elevation of the raster as a starting point.

Returns

Pandas DataFrame of elevation, area at or above the target elevation, and percent area at or above the target elevation for each elevation interval

atiim.inflection module

atiim.inflection.calculate_bankfull_elevation(df: pandas.core.frame.DataFrame, smooth_data: bool = False, smooth_sigma: int = 100, area_field_name: str = 'area', elevation_field_name: str = 'elevation') → Tuple[float][source]

Calculate the bankfull elevation point, or the first point of inflection, using the index of the change in sign of the second derivatives of the accumulating area with increasing elevation. If the input data is noisy, you may choose to smooth the data using a Gaussian filter.

Parameters

  • df (pd.DataFrame) – Desingned for output from the atiim.simulate_inundation() function. Though can be used with any data frame having an area and elevation field with data.

  • smooth_data (bool) – Optional. Smooth noisy data using a Gaussian filter. Use in combination with the smooth_sigma setting.

  • smooth_sigma (int) – Optional. Standard deviation for Gaussian kernel. Use when smooth_data is set to True.

  • area_field_name (str) – Optional. Name of area field in data frame. Default: ‘area’

  • elevation_field_name (str) – Optional. Name of elevation field in data frame. Default ‘elevation’

Returns

[0] Bankfull elevation value. First inflection point. [1] Bankfull area value

atiim.inundation module

atiim.inundation.process_slice(arr: numpy.ndarray, upper_elev: float, gage_gdf: geopandas.geodataframe.GeoDataFrame, water_elev_freq: dict, run_name: str, hour_interval: float, transform: affine.Affine, target_crs: rasterio.crs.CRS, write_shapefile: bool = True, output_directory: Optional[str] = None) → geopandas.geodataframe.GeoDataFrame[source]

Create a water level polygon shapefile containing a single feature that represents the grid cells of an input DEM that are less than or equal to an upper elevation level.

Parameters

  • arr (np.ndarray) – 2D array from raster band read

  • upper_elev (float) – Elevation value for the upper bound of the elevation interval

  • gage_gdf (gpd.GeoDataFrame) – GeoDataFrame of the gage location point

  • water_elev_freq (dict) – Dictionary of water elevation frequency {elev: frequency}

  • run_name (str) – Name of run, all lowercase and only underscore separated.

  • hour_interval (float) – Time step of inundation extent. Either 1.0 or 0.5.

  • transform (Affine) – Trasformation object from the rasterio source raster

  • target_crs (CRS) – Coordinate reference system (CRS) object from the rasterio source raster to be used in projecting the water level polygons.

  • write_shapefile (bool) – Optional. Choice to write the GeoDataFrame water level polygon as a shapefile. Set output directory if True. Default is True.

  • output_directory (str) – Full path to a write-enabled directory to write output files to if write_shapefile is set to True

Returns

A geopandas data frame of a polygon intersecting the gage point location for the target elevation interval.

atiim.inundation.simulate_inundation(dem_file: str, basin_shp: str, gage_shp: str, gage_data_file: str, run_name: str, output_directory: Optional[str] = None, write_csv: bool = True, elevation_interval: float = 0.1, hour_interval: float = 1.0, n_jobs: int = 1, verbose: bool = False)[source]

Worker function to simulate inundation over a DEM using a stable gage location and accompanying water level time series data.

Parameters

  • dem_file (str) – Full path with file name and extension to the input DEM raster file.

  • basin_shp (str) – Full path with file name and extension to the target basin shapefile

  • gage_shp (str) – Full path with file name and extension to the target gage shapefile

  • gage_data_file (str) – Full path with file name and extension to the gage data file.

  • output_directory (str) – Full path to a write-enabled directory to write output files to

  • run_name (str) – Name of run, all lowercase and only underscore separated.

  • write_csv (bool) – Choice to write a CSV file of inundation metric outputs

  • elevation_interval (float) – Step for elevation to be processed.

  • hour_interval (float) – Time step of inundation extent. Either 1.0 or 0.5.

  • n_jobs (int) – The maximum number of concurrently running jobs, such as the number of Python worker processes when backend=”multiprocessing” or the size of the thread-pool when backend=”threading”. If -1 all CPUs are used. If 1 is given, no parallel computing code is used at all, which is useful for debugging. For n_jobs below -1, (n_cpus + 1 + n_jobs) are used. Thus for n_jobs = -2, all CPUs but one are used. None is a marker for ‘unset’ that will be interpreted as n_jobs=1 (sequential execution) unless the call is performed under a parallel_backend context manager that sets another value for n_jobs.

  • verbose (bool) – Choice to log verbosely

atiim.plots module

class atiim.plots.PlotDem(data: Union[str, pandas.core.frame.DataFrame], elevation_interval: float, min_elevation: Optional[float] = None, max_elevation: Optional[float] = None, style: str = 'whitegrid', font_scale: float = 1.2, figsize: Tuple[int] = (12, 8), show_plot: bool = True, save_plot: bool = False, output_file: Optional[str] = None, dpi: int = 150)[source]

Bases: atiim.plots.PlotGeneral

Prepare elevation data from an input DEM raster for plotting.

Parameters

  • data (Union[str, pd.Dataframe]) – Either a full path with file name and extension to the input DEM raster or a data frame processed using atiim.hypsometric_curve()

  • elevation_interval (float) – Optional. Elevation sample spacing in the units of the input DEM. Set when using a DEM raster file input.

  • min_elevation (float) – Optional. Minimum elevation to sample from. Default is to use the minimum elevation of the raster as a starting point. Set when using a DEM raster file input.

  • max_elevation (float) – Optional. Maximum elevation to sample from. Default is to use the maximum elevation of the raster as a starting point. Set when using a DEM raster file input.

  • style (str) – Seaborn style designation

  • font_scale (float) – Scaling factor for font size

  • figsize (Tuple[int]) – Tuple of figure size (x, y)

  • show_plot (bool) – If True, plot will be displayed

  • save_plot (bool) – If True, plot will be written to file and a value must be set for output_file

  • output_file (str) – Full path with file name and extension to an output file

  • dpi (int) – The resolution in dots per inch

prepare_data() → pandas.core.frame.DataFrame[source]

Assign input data to a data frame.

class atiim.plots.PlotGageData(data: Union[str, pandas.core.frame.DataFrame], date_field_name: str = 'DATE', time_field_name: str = 'TIME', elevation_field_name: str = 'WL_ELEV_M', style: str = 'whitegrid', font_scale: float = 1.2, figsize: Tuple[int] = (12, 8), show_plot: bool = True, save_plot: bool = False, output_file: Optional[str] = None, dpi: int = 150)[source]

Bases: atiim.plots.PlotGeneral

Prepare gage data for plotting.

Parameters

  • gage_data (Union[str, pd.Dataframe]) – Either a full path with file name and extension to the gage data file or a data frame processed using atiim.import_gage_data()

  • date_field_name (str) – Name of date field in file

  • time_field_name (str) – Name of time field in file

  • elevation_field_name (str) – Name of elevation field in file

  • style (str) – Seaborn style designation

  • font_scale (float) – Scaling factor for font size

  • figsize (Tuple[int]) – Tuple of figure size (x, y)

  • show_plot (bool) – If True, plot will be displayed

  • save_plot (bool) – If True, plot will be written to file and a value must be set for output_file

  • output_file (str) – Full path with file name and extension to an output file

  • dpi (int) – The resolution in dots per inch

calculate_cdf(data: numpy.ndarray) → numpy.ndarray[source]

Calculate the cumulative distribution.

Parameters

data (np.ndarray) – Input data for x-axis values

Returns

NumPy array of CDF outputs

calculate_exceedance_probability() → pandas.core.series.Series[source]

Calculate a y-axis series of exceedance probilites as a percentage.

calculate_lognorm_fit() → Tuple[float][source]

Calculate the lognormal continuous random variable and generate parameter estimates. Uses Maximum Likelihood Estimateion (MLE).

Returns

[0] shape parameter estimates [1] location parameters [2] scale parameters

calculate_pdf(data: numpy.ndarray) → numpy.ndarray[source]

Calculate the probability density.

Parameters

data (np.ndarray) – Input data for x-axis values

Returns

NumPy array of PDF outputs

generate_wse_interval(x_padding: float = 1.05, n_samples: int = 100) → numpy.ndarray[source]

Generate an evenly spaced interval of values encompassing water surface elevation for use in scaling the x-axis.

Parameters

  • x_padding (float) – Multiplier for maximum elevation to determine an ending interval for the x-axis. E.g., if max value is 100 and x_padding is 1.1 then the ending bound would be 110.

  • n_samples (int) – The number of samples to generate over the x-axis space

Returns

NumPy array of evenly spaced water surface elevation intervals

prepare_data() → pandas.core.frame.DataFrame[source]

Assign gage data to a data frame.

set_cumulative_series() → pandas.core.series.Series[source]

Generate axis series and intervals for the cumulative distribution y-axis.

sorted_elevation() → pandas.core.series.Series[source]

Sort elevation data in ascending order.

class atiim.plots.PlotGeneral(style: str = 'whitegrid', font_scale: float = 1.2, figsize: Tuple[int] = (12, 8), show_plot: bool = True, save_plot: bool = False, output_file: Optional[str] = None, dpi: int = 150)[source]

Bases: object

General plotting setup and option handling.

Parameters

  • style (str) – Seaborn style designation

  • font_scale (float) – Scaling factor for font size

  • figsize (Tuple[int]) – Tuple of figure size (x, y)

  • show_plot (bool) – If True, plot will be displayed

  • save_plot (bool) – If True, plot will be written to file and a value must be set for output_file

  • output_file (str) – Full path with file name and extension to an output file

  • dpi (int) – The resolution in dots per inch

output_handler()[source]

Handle plot display and output options.

set_xaxis_to_thousands()[source]

Format the x-axis to show thousands as K (e.g., 15,000 as 15K).

class atiim.plots.PlotInundationData(data: Union[str, pandas.core.frame.DataFrame], style: str = 'whitegrid', font_scale: float = 1.2, figsize: Tuple[int] = (12, 8), show_plot: bool = True, save_plot: bool = False, output_file: Optional[str] = None, dpi: int = 150)[source]

Bases: atiim.plots.PlotGeneral

Prepare inundation data for plotting.

Parameters

  • data (Union[str, pd.Dataframe]) – Either a full path with file name and extension to the inundation data file or a data frame processed using atiim.simulate_inundation()

  • style (str) – Seaborn style designation

  • font_scale (float) – Scaling factor for font size

  • figsize (Tuple[int]) – Tuple of figure size (x, y)

  • show_plot (bool) – If True, plot will be displayed

  • save_plot (bool) – If True, plot will be written to file and a value must be set for output_file

  • output_file (str) – Full path with file name and extension to an output file

  • dpi (int) – The resolution in dots per inch

FLD_AREA = 'area'
FLD_ELEVATION = 'elevation'
FLD_FREQUENCY = 'frequency'
FLD_HECTARES = 'hectares'
FLD_HECTARE_HOURS = 'hect_hours'
FLD_ID = 'id'
FLD_PERIMETER = 'perimeter'
prepare_data() → pandas.core.frame.DataFrame[source]

Assign input data to a data frame.

atiim.plots.plot_hypsometric_curve(data: Union[str, pandas.core.frame.DataFrame], elevation_interval: float = 0.1, min_elevation: Optional[float] = None, max_elevation: Optional[float] = None, show_plot: bool = True, save_plot: bool = False, output_file: Optional[str] = None, dpi: int = 150, x_field_name: str = 'dem_area_at_elevation', y_field_name: str = 'dem_elevation', x_label: str = 'Area (m$^2$)', y_label: str = 'Elevation (m)', title: Optional[str] = 'Hypsometric Curve', style: str = 'whitegrid', font_scale: float = 1.2, figsize: Tuple[int] = (12, 8), color: str = 'black')[source]

Plot a hypsometric curve as an elevation-area relationship assessment metric of the landform shape at a site. Provides basic metric of opportunity for inundation and habitat opportunity.

Parameters

  • data (Union[str, pd.Dataframe]) – Either a full path with file name and extension to the input DEM raster or a data frame processed using atiim.hypsometric_curve()

  • elevation_interval (float) – Optional. Elevation sample spacing in the units of the input DEM. Set when using a DEM raster file input.

  • min_elevation (float) – Optional. Minimum elevation to sample from. Default is to use the minimum elevation of the raster as a starting point. Set when using a DEM raster file input.

  • max_elevation (float) – Optional. Maximum elevation to sample from. Default is to use the maximum elevation of the raster as a starting point. Set when using a DEM raster file input.

  • show_plot (bool) – If True, plot will be displayed

  • save_plot (bool) – If True, plot will be written to file and a value must be set for output_file

  • output_file (str) – Full path with file name and extension to an output file

  • dpi (int) – The resolution in dots per inch

  • x_field_name (str) – Field name of data for the x-axis

  • y_field_name (str) – Field name of data for the y-axis

  • x_label (str) – Label for the x-axis

  • y_label (str) – Label for the y-axis

  • title (Union[str, None]) – Title for the plot if desired. Use None for no title.

  • style (str) – Seaborn style designation

  • font_scale (float) – Scaling factor for font size

  • figsize (Tuple[int]) – Tuple of figure size (x, y)

  • color (str) – Color of line and markers in plot

atiim.plots.plot_inundation_area(data: Union[str, pandas.core.frame.DataFrame], show_plot: bool = True, save_plot: bool = False, output_file: Optional[str] = None, dpi: int = 150, style: str = 'whitegrid', font_scale: float = 1.2, figsize: Tuple[int] = (12, 8), title: Optional[str] = 'Inundation Area by Water Surface Elevation', inflection_pt_size: int = 14)[source]

Plot area of inundation through the water surface elevation time series.

Parameters

  • data (Union[str, pd.DataFrame]) – An data frame or CSV file containing inundation data as a result of atiim.simulate_inundation()

  • show_plot (bool) – If True, plot will be displayed

  • save_plot (bool) – If True, plot will be written to file and a value must be set for output_file

  • output_file (str) – Full path with file name and extension to an output file

  • dpi (int) – The resolution in dots per inch

  • style (str) – Seaborn style designation

  • font_scale (float) – Scaling factor for font size

  • figsize (Tuple[int]) – Tuple of figure size (x, y)

:param title Plot title. If None, then no title will be displayed. :type title Union[str, None]

Parameters

inflection_pt_size (int) – Size of the inflection point marker

atiim.plots.plot_inundation_hectare_hours(data: Union[str, pandas.core.frame.DataFrame], show_plot: bool = True, save_plot: bool = False, output_file: Optional[str] = None, dpi: int = 150, y_pad_fraction: float = 0.15, x_pad_fraction: float = 0.05, style: str = 'whitegrid', font_scale: float = 1.2, figsize: Tuple[int] = (12, 8), fill_color: str = '#005AB5', transparency: float = 0.7, title: Optional[str] = 'Hectare Hours of Inundation')[source]

Plot of the hectare hours of inundation over water surface elevations.

Parameters

  • data (Union[str, pd.DataFrame]) – An data frame or CSV file containing inundation data as a result of atiim.simulate_inundation()

  • show_plot (bool) – If True, plot will be displayed

  • save_plot (bool) – If True, plot will be written to file and a value must be set for output_file

  • output_file (str) – Full path with file name and extension to an output file

  • dpi (int) – The resolution in dots per inch

  • y_pad_fraction (float) – A decimal fraction of the maximum elevation value to use as a padding on the Y axis

  • x_pad_fraction (float) – A decimal fraction of the maximum hectare hour value to use as a padding on the X axis

  • style (str) – Seaborn style designation

  • font_scale (float) – Scaling factor for font size

  • figsize (Tuple[int]) – Tuple of figure size (x, y)

  • fill_color (str) – Color of filled area in plot

:param transparency Alpha value from 0 to 1 for transparency :type transparency float

:param title Plot title. If None, then no title will be displayed. :type title Union[str, None]

atiim.plots.plot_inundation_perimeter(data: Union[str, pandas.core.frame.DataFrame], show_plot: bool = True, save_plot: bool = False, output_file: Optional[str] = None, dpi: int = 150, x_pad_fraction: float = 0.05, style: str = 'whitegrid', font_scale: float = 1.2, figsize: Tuple[int] = (12, 8), title: Optional[str] = 'Inundation Perimeter by Water Surface Elevation')[source]

Plot perimeter of inundation through the water surface elevation time series.

Parameters

  • data (Union[str, pd.DataFrame]) – An data frame or CSV file containing inundation data as a result of atiim.simulate_inundation()

  • show_plot (bool) – If True, plot will be displayed

  • save_plot (bool) – If True, plot will be written to file and a value must be set for output_file

  • output_file (str) – Full path with file name and extension to an output file

  • dpi (int) – The resolution in dots per inch

  • x_pad_fraction (float) – A decimal fraction of the maximum hectare hour value to use as a padding on the X axis

  • style (str) – Seaborn style designation

  • font_scale (float) – Scaling factor for font size

  • figsize (Tuple[int]) – Tuple of figure size (x, y)

:param title Plot title. If None, then no title will be displayed. :type title Union[str, None]

atiim.plots.plot_wse_cumulative_distribution(data: Union[str, pandas.core.frame.DataFrame], show_plot: bool = True, save_plot: bool = False, output_file: Optional[str] = None, dpi: int = 150, date_field_name: str = 'DATE', time_field_name: str = 'TIME', elevation_field_name: str = 'WL_ELEV_M', x_padding: float = 1.05, n_samples: int = 100, style: str = 'whitegrid', font_scale: float = 1.2, figsize: Tuple[int] = (12, 8), data_color: str = '#005AB5', lognorm_color: str = '#DC3220', title: Optional[str] = 'Cumulative Distribution of Water Surface Elevation')[source]

Plot the cumulative distribution function for water surface elevation from the gage data.

Parameters

  • data (Union[str, pd.Dataframe]) – Either a full path with file name and extension to the gage data file or a data frame processed using atiim.import_gage_data()

  • show_plot (bool) – If True, plot will be displayed

  • save_plot (bool) – If True, plot will be written to file and a value must be set for output_file

  • date_field_name (str) – Name of date field in file

  • time_field_name (str) – Name of time field in file

  • elevation_field_name (str) – Name of elevation field in file

  • x_padding (float) – Multiplier for maximum elevation to determine an ending interval for the x-axis. E.g., if max value is 100 and x_padding is 1.1 then the ending bound would be 110.

  • n_samples (int) – The number of samples to generate over the x-axis space

  • output_file (str) – Full path with file name and extension to an output file

  • dpi (int) – The resolution in dots per inch

  • style (str) – Seaborn style designation

  • font_scale (float) – Scaling factor for font size

  • figsize (Tuple[int]) – Tuple of figure size (x, y)

  • data_color (str) – Color of data line

  • lognorm_color (str) – Color of data line

:param title Plot title. If None, then no title will be displayed. :type title Union[str, None]

:param title Plot title. If None, then no title will be displayed. :type title Union[str, None]

atiim.plots.plot_wse_exceedance_probability(data: Union[str, pandas.core.frame.DataFrame], show_plot: bool = True, save_plot: bool = False, output_file: Optional[str] = None, dpi: int = 150, date_field_name: str = 'DATE', time_field_name: str = 'TIME', elevation_field_name: str = 'WL_ELEV_M', x_padding: float = 1.05, n_samples: int = 100, style: str = 'whitegrid', font_scale: float = 1.2, figsize: Tuple[int] = (12, 8), data_color: str = '#005AB5', lognorm_color: str = '#DC3220', title: Optional[str] = 'Exceedance Probability of Water Surface Elevation')[source]

Plot the probability of occurrence for individual water surface elevations based on the period-of-record.

Parameters

  • data (Union[str, pd.Dataframe]) – Either a full path with file name and extension to the gage data file or a data frame processed using atiim.import_gage_data()

  • show_plot (bool) – If True, plot will be displayed

  • save_plot (bool) – If True, plot will be written to file and a value must be set for output_file

  • date_field_name (str) – Name of date field in file

  • time_field_name (str) – Name of time field in file

  • elevation_field_name (str) – Name of elevation field in file

  • x_padding (float) – Multiplier for maximum elevation to determine an ending interval for the x-axis. E.g., if max value is 100 and x_padding is 1.1 then the ending bound would be 110.

  • n_samples (int) – The number of samples to generate over the x-axis space

  • output_file (str) – Full path with file name and extension to an output file

  • dpi (int) – The resolution in dots per inch

  • style (str) – Seaborn style designation

  • font_scale (float) – Scaling factor for font size

  • figsize (Tuple[int]) – Tuple of figure size (x, y)

  • data_color (str) – Color of data line

  • lognorm_color (str) – Color of data line

:param transparency Alpha value from 0 to 1 for transparency of histogram :type transparency float

Parameters

n_bins (int) – The number of equal-width bins in the range.

:param title Plot title. If None, then no title will be displayed. :type title Union[str, None]

atiim.plots.plot_wse_probability_density(data: Union[str, pandas.core.frame.DataFrame], show_plot: bool = True, save_plot: bool = False, output_file: Optional[str] = None, dpi: int = 150, date_field_name: str = 'DATE', time_field_name: str = 'TIME', elevation_field_name: str = 'WL_ELEV_M', x_padding: float = 1.05, n_samples: int = 100, style: str = 'whitegrid', font_scale: float = 1.2, figsize: Tuple[int] = (12, 8), data_color: str = '#005AB5', lognorm_color: str = '#DC3220', transparency: float = 0.6, n_bins: int = 21, title: Optional[str] = 'Probability Density of Water Surface Elevation')[source]

Plot the probability density of water surface elevations based on the period-of-record.

Parameters

  • data (Union[str, pd.Dataframe]) – Either a full path with file name and extension to the gage data file or a data frame processed using atiim.import_gage_data()

  • show_plot (bool) – If True, plot will be displayed

  • save_plot (bool) – If True, plot will be written to file and a value must be set for output_file

  • date_field_name (str) – Name of date field in file

  • time_field_name (str) – Name of time field in file

  • elevation_field_name (str) – Name of elevation field in file

  • x_padding (float) – Multiplier for maximum elevation to determine an ending interval for the x-axis. E.g., if max value is 100 and x_padding is 1.1 then the ending bound would be 110.

  • n_samples (int) – The number of samples to generate over the x-axis space

  • output_file (str) – Full path with file name and extension to an output file

  • dpi (int) – The resolution in dots per inch

  • style (str) – Seaborn style designation

  • font_scale (float) – Scaling factor for font size

  • figsize (Tuple[int]) – Tuple of figure size (x, y)

  • data_color (str) – Color of data line

  • lognorm_color (str) – Color of data line

:param transparency Alpha value from 0 to 1 for transparency of histogram :type transparency float

Parameters

n_bins (int) – The number of equal-width bins in the range.

:param title Plot title. If None, then no title will be displayed. :type title Union[str, None]

atiim.plots.plot_wse_timeseries(data: Union[str, pandas.core.frame.DataFrame], show_plot: bool = True, save_plot: bool = False, output_file: Optional[str] = None, dpi: int = 150, date_field_name: str = 'DATE', time_field_name: str = 'TIME', elevation_field_name: str = 'WL_ELEV_M', style: str = 'whitegrid', font_scale: float = 1.2, figsize: Tuple[int] = (12, 8), color: str = '#005AB5', transparency: float = 0.7, title: Optional[str] = 'Water Surface Elevation Gage Measurements')[source]

Create plot for water surface elevation for the gage measurement period.

Parameters

  • data (Union[str, pd.Dataframe]) – Either a full path with file name and extension to the gage data file or a data frame processed using atiim.import_gage_data()

  • show_plot (bool) – If True, plot will be displayed

  • save_plot (bool) – If True, plot will be written to file and a value must be set for output_file

  • output_file (str) – Full path with file name and extension to an output file

  • dpi (int) – The resolution in dots per inch

  • date_field_name (str) – Name of date field in file

  • time_field_name (str) – Name of time field in file

  • elevation_field_name (str) – Name of elevation field in file

  • style (str) – Seaborn style designation

  • font_scale (float) – Scaling factor for font size

  • figsize (Tuple[int]) – Tuple of figure size (x, y)

  • color (str) – Color of line and markers in plot

:param transparency Alpha value from 0 to 1 for transparency :type transparency float

:param title Plot title. If None, then no title will be displayed. :type title Union[str, None]

Module contents