flopy.plot.crosssection module

class DeprecatedCrossSection(ax=None, model=None, modelgrid=None, line=None, extent=None)[source]

Bases: flopy.plot.crosssection.PlotCrossSection

Deprecation handler for the PlotCrossSection class

Parameters:
  • ax (matplotlib.pyplot.axes object) –
  • model (flopy.modflow.Modflow object) –
  • modelgrid (flopy.discretization.Grid object) –
  • line (dict) – Dictionary with either “row”, “column”, or “line” key. If key is “row” or “column” key value should be the zero-based row or column index for cross-section. If key is “line” value should be an array of (x, y) tuples with vertices of cross-section. Vertices should be in map coordinates consistent with xul, yul, and rotation.
  • extent (tuple of floats) – (xmin, xmax, ymin, ymax) will be used to specify axes limits. If None then these will be calculated based on grid, coordinates, and rotation.
class ModelCrossSection[source]

Bases: object

DEPRECATED. Class to create a cross section of the model.

Parameters:
  • ax (matplotlib.pyplot axis) – The plot axis. If not provided it, plt.gca() will be used.
  • model (flopy.modflow object) – flopy model object. (Default is None)
  • dis (flopy.modflow.ModflowDis object) – flopy discretization object. (Default is None)
  • line (dict) – Dictionary with either “row”, “column”, or “line” key. If key is “row” or “column” key value should be the zero-based row or column index for cross-section. If key is “line” value should be an array of (x, y) tuples with vertices of cross-section. Vertices should be in map coordinates consistent with xul, yul, and rotation.
  • xul (float) – x coordinate for upper left corner
  • yul (float) – y coordinate for upper left corner. The default is the sum of the delc array.
  • rotation (float) – Angle of grid rotation around the upper left corner. A positive value indicates clockwise rotation. Angles are in degrees. Default is None
  • extent (tuple of floats) – (xmin, xmax, ymin, ymax) will be used to specify axes limits. If None then these will be calculated based on grid, coordinates, and rotation.
class PlotCrossSection(model=None, modelgrid=None, ax=None, line=None, extent=None, geographic_coords=False)[source]

Bases: object

Class to create a cross sectional plot of a model.

Parameters:
  • ax (matplotlib.pyplot axis) – The plot axis. If not provided it, plt.gca() will be used.
  • model (flopy.modflow object) – flopy model object. (Default is None)
  • modelgrid (flopy.discretization.Grid object) – can be a StructuredGrid, VertexGrid, or UnstructuredGrid object
  • line (dict) – Dictionary with either “row”, “column”, or “line” key. If key is “row” or “column” key value should be the zero-based row or column index for cross-section. If key is “line” value should be an array of (x, y) tuples with vertices of cross-section. Vertices should be in map coordinates consistent with xul, yul, and rotation.
  • extent (tuple of floats) – (xmin, xmax, ymin, ymax) will be used to specify axes limits. If None then these will be calculated based on grid, coordinates, and rotation.
  • geographic_coords (bool) – boolean flag to allow the user to plot cross section lines in geographic coordinates. If False (default), cross section is plotted as the distance along the cross section line.
contour_array(a, masked_values=None, head=None, **kwargs)[source]

Contour a two-dimensional array.

Parameters:
  • a (numpy.ndarray) – Three-dimensional array to plot.
  • masked_values (iterable of floats, ints) – Values to mask.
  • head (numpy.ndarray) – Three-dimensional array to set top of patches to the minimum of the top of a layer or the head value. Used to create patches that conform to water-level elevations.
  • **kwargs (dictionary) – keyword arguments passed to matplotlib.pyplot.contour
Returns:

contour_set
Return type:

matplotlib.pyplot.contour
get_extent()[source]

Get the extent of the rotated and offset grid

Returns:tuple
Return type:(xmin, xmax, ymin, ymax)
get_grid_line_collection(**kwargs)[source]

Get a PatchCollection of the grid

Parameters:**kwargs (dictionary) – keyword arguments passed to matplotlib.collections.LineCollection
Returns:PatchCollection
Return type:matplotlib.collections.LineCollection
get_grid_patch_collection(plotarray, projpts=None, fill_between=False, **kwargs)[source]

Get a PatchCollection of plotarray in unmasked cells

Parameters:
  • plotarray (numpy.ndarray) – One-dimensional array to attach to the Patch Collection.
  • projpts (dict) – dictionary defined by node number which contains model patch vertices.
  • fill_between (bool) – flag to create polygons that mimick the matplotlib fill between method. Only used by the plot_fill_between method.
  • **kwargs (dictionary) – keyword arguments passed to matplotlib.collections.PatchCollection
Returns:

patches
Return type:

matplotlib.collections.PatchCollection
plot_array(a, masked_values=None, head=None, **kwargs)[source]

Plot a three-dimensional array as a patch collection.

Parameters:
  • a (numpy.ndarray) – Three-dimensional array to plot.
  • masked_values (iterable of floats, ints) – Values to mask.
  • head (numpy.ndarray) – Three-dimensional array to set top of patches to the minimum of the top of a layer or the head value. Used to create patches that conform to water-level elevations.
  • **kwargs (dictionary) – keyword arguments passed to matplotlib.collections.PatchCollection
Returns:

patches
Return type:

matplotlib.collections.PatchCollection
plot_bc(name=None, package=None, kper=0, color=None, head=None, **kwargs)[source]

Plot boundary conditions locations for a specific boundary type from a flopy model

Parameters:
  • name (string) – Package name string (‘WEL’, ‘GHB’, etc.). (Default is None)
  • package (flopy.modflow.Modflow package class instance) – flopy package class instance. (Default is None)
  • kper (int) – Stress period to plot
  • color (string) – matplotlib color string. (Default is None)
  • head (numpy.ndarray) – Three-dimensional array (structured grid) or Two-dimensional array (vertex grid) to set top of patches to the minimum of the top of a layer or the head value. Used to create patches that conform to water-level elevations.
  • **kwargs (dictionary) – keyword arguments passed to matplotlib.collections.PatchCollection
Returns:

patches
Return type:

matplotlib.collections.PatchCollection
plot_discharge(frf, fff, flf=None, head=None, kstep=1, hstep=1, normalize=False, **kwargs)[source]

DEPRECATED. Use plot_vector() instead, which should follow after postprocessing.get_specific_discharge().

Use quiver to plot vectors.

Parameters:
  • frf (numpy.ndarray) – MODFLOW’s ‘flow right face’
  • fff (numpy.ndarray) – MODFLOW’s ‘flow front face’
  • flf (numpy.ndarray) – MODFLOW’s ‘flow lower face’ (Default is None.)
  • head (numpy.ndarray) – MODFLOW’s head array. If not provided, then will assume confined conditions in order to calculated saturated thickness.
  • kstep (int) – layer frequency to plot. (Default is 1.)
  • hstep (int) – horizontal frequency to plot. (Default is 1.)
  • normalize (bool) – boolean flag used to determine if discharge vectors should be normalized using the magnitude of the specific discharge in each cell. (default is False)
  • kwargs (dictionary) – Keyword arguments passed to plt.quiver()
Returns:

quiver – Vectors
Return type:

matplotlib.pyplot.quiver
plot_endpoint(ep, direction='ending', selection=None, selection_direction=None, method='cell', head=None, **kwargs)[source]
plot_fill_between(a, colors=('blue', 'red'), masked_values=None, head=None, **kwargs)[source]

Plot a three-dimensional array as lines.

Parameters:
  • a (numpy.ndarray) – Three-dimensional array to plot.
  • colors (list) – matplotlib fill colors, two required
  • masked_values (iterable of floats, ints) – Values to mask.
  • head (numpy.ndarray) – Three-dimensional array to set top of patches to the minimum of the top of a layer or the head value. Used to create patches that conform to water-level elevations.
  • **kwargs (dictionary) – keyword arguments passed to matplotlib.pyplot.plot
Returns:

plot
Return type:

list containing matplotlib.fillbetween objects
plot_grid(**kwargs)[source]

Plot the grid lines.

Parameters:kwargs (ax, colors. The remaining kwargs are passed into the) – the LineCollection constructor.
Returns:lc
Return type:matplotlib.collections.LineCollection
plot_ibound(ibound=None, color_noflow='black', color_ch='blue', color_vpt='red', head=None, **kwargs)[source]

Make a plot of ibound. If not specified, then pull ibound from the self.model

Parameters:
  • ibound (numpy.ndarray) – ibound array to plot. (Default is ibound in ‘BAS6’ package.)
  • color_noflow (string) – (Default is ‘black’)
  • color_ch (string) – Color for constant heads (Default is ‘blue’.)
  • head (numpy.ndarray) – Three-dimensional array to set top of patches to the minimum of the top of a layer or the head value. Used to create patches that conform to water-level elevations.
  • **kwargs (dictionary) – keyword arguments passed to matplotlib.collections.PatchCollection
Returns:

patches
Return type:

matplotlib.collections.PatchCollection
plot_inactive(ibound=None, color_noflow='black', **kwargs)[source]

Make a plot of inactive cells. If not specified, then pull ibound from the self.ml

Parameters:
  • ibound (numpy.ndarray) – ibound array to plot. (Default is ibound in ‘BAS6’ package.)
  • color_noflow (string) – (Default is ‘black’)
Returns:

quadmesh
Return type:

matplotlib.collections.QuadMesh
plot_pathline(pl, travel_time=None, method='cell', head=None, **kwargs)[source]

Plot the MODPATH pathlines

Parameters:
  • pl (list of rec arrays or a single rec array) – rec array or list of rec arrays is data returned from modpathfile PathlineFile get_data() or get_alldata() methods. Data in rec array is ‘x’, ‘y’, ‘z’, ‘time’, ‘k’, and ‘particleid’.
  • travel_time (float or str) – travel_time is a travel time selection for the displayed pathlines. If a float is passed then pathlines with times less than or equal to the passed time are plotted. If a string is passed a variety logical constraints can be added in front of a time value to select pathlines for a select period of time. Valid logical constraints are <=, <, >=, and >. For example, to select all pathlines less than 10000 days travel_time=’< 10000’ would be passed to plot_pathline. (default is None)
  • method (str) –
    “cell” shows only pathlines that intersect with a cell
    ”all” projects all pathlines onto the cross section regardless
    of whether they intersect with a given cell
  • head (np.ndarray) – optional adjustment to only show pathlines that are <= to the top of the water table given a user supplied head array
  • kwargs (layer, ax, colors. The remaining kwargs are passed) – into the LineCollection constructor.
Returns:

lc
Return type:

matplotlib.collections.LineCollection
plot_specific_discharge(spdis, head=None, kstep=1, hstep=1, normalize=False, **kwargs)[source]

DEPRECATED. Use plot_vector() instead, which should follow after postprocessing.get_specific_discharge().

Use quiver to plot vectors.

Parameters:
  • spdis (np.recarray) – numpy recarray of specific discharge information. This can be grabbed directly from the CBC file if SAVE_SPECIFIC_DISCHARGE is used in the MF6 NPF file.
  • head (numpy.ndarray) –
    MODFLOW’s head array. If not provided, then the quivers will be
    plotted in the cell center.
  • kstep (int) – layer frequency to plot. (Default is 1.)
  • hstep (int) – horizontal frequency to plot. (Default is 1.)
  • normalize (bool) – boolean flag used to determine if discharge vectors should be normalized using the magnitude of the specific discharge in each cell. (default is False)
  • kwargs (dictionary) – Keyword arguments passed to plt.quiver()
Returns:

quiver – Vectors
Return type:

matplotlib.pyplot.quiver
plot_surface(a, masked_values=None, **kwargs)[source]

Plot a two- or three-dimensional array as line(s).

Parameters:
  • a (numpy.ndarray) – Two- or three-dimensional array to plot.
  • masked_values (iterable of floats, ints) – Values to mask.
  • **kwargs (dictionary) – keyword arguments passed to matplotlib.pyplot.plot
Returns:

plot
Return type:

list containing matplotlib.plot objects
plot_timeseries(ts, travel_time=None, method='cell', head=None, **kwargs)[source]

Plot the MODPATH timeseries.

Parameters:
  • ts (list of rec arrays or a single rec array) – rec array or list of rec arrays is data returned from modpathfile TimeseriesFile get_data() or get_alldata() methods. Data in rec array is ‘x’, ‘y’, ‘z’, ‘time’, ‘k’, and ‘particleid’.
  • travel_time (float or str) – travel_time is a travel time selection for the displayed pathlines. If a float is passed then pathlines with times less than or equal to the passed time are plotted. If a string is passed a variety logical constraints can be added in front of a time value to select pathlines for a select period of time. Valid logical constraints are <=, <, >=, and >. For example, to select all pathlines less than 10000 days travel_time=’< 10000’ would be passed to plot_pathline. (default is None)
  • kwargs (layer, ax, colors. The remaining kwargs are passed) – into the LineCollection constructor. If layer=’all’, pathlines are output for all layers
Returns:

lo
Return type:

list of Line2D objects
plot_vector(vx, vy, vz, head=None, kstep=1, hstep=1, normalize=False, masked_values=None, **kwargs)[source]

Plot a vector.

Parameters:
  • vx (np.ndarray) – x component of the vector to be plotted (non-rotated) array shape must be (nlay, nrow, ncol) for a structured grid array shape must be (nlay, ncpl) for a unstructured grid
  • vy (np.ndarray) – y component of the vector to be plotted (non-rotated) array shape must be (nlay, nrow, ncol) for a structured grid array shape must be (nlay, ncpl) for a unstructured grid
  • vz (np.ndarray) – y component of the vector to be plotted (non-rotated) array shape must be (nlay, nrow, ncol) for a structured grid array shape must be (nlay, ncpl) for a unstructured grid
  • head (numpy.ndarray) – MODFLOW’s head array. If not provided, then the quivers will be plotted in the cell center.
  • kstep (int) – layer frequency to plot (default is 1)
  • hstep (int) – horizontal frequency to plot (default is 1)
  • normalize (bool) – boolean flag used to determine if vectors should be normalized using the vector magnitude in each cell (default is False)
  • masked_values (iterable of floats) – values to mask
  • kwargs (matplotlib.pyplot keyword arguments for the) – plt.quiver method
Returns:

quiver – result of the quiver function
Return type:

matplotlib.pyplot.quiver
polygons

Method to return cached matplotlib polygons for a cross section

Returns:dict
Return type:[matplotlib.patches.Polygon]
set_zcentergrid(vs, kstep=1)[source]

Get an array of z elevations at the center of a cell that is based on minimum of cell top elevation (self.elev) or passed vs numpy.ndarray

Parameters:
  • vs (numpy.ndarray) – Three-dimensional array to plot.
  • kstep (int) – plotting layer interval
Returns:

zcentergrid
Return type:

numpy.ndarray
set_zpts(vs)[source]

Get an array of projected vertices corrected with corrected elevations based on minimum of cell elevation (self.elev) or passed vs numpy.ndarray

Parameters:vs (numpy.ndarray) – Two-dimensional array to plot.
Returns:zpts
Return type:dict