flopy.plot.plotutil module

Module containing helper functions for plotting model data using ModelMap and ModelCrossSection. Functions for plotting shapefiles are also included.

exception PlotException(message)[source]

Bases: Exception

class PlotUtilities[source]

Bases: object

Class which groups a collection of plotting utilities which Flopy and Flopy6 can use to generate map based plots

static centered_specific_discharge(Qx, Qy, Qz, delr, delc, sat_thk)[source]

DEPRECATED. Use postprocessing.get_specific_discharge() instead.

Using the MODFLOW discharge, calculate the cell centered specific discharge by dividing by the flow width and then averaging to the cell center.

Parameters:
  • Qx (numpy.ndarray) – MODFLOW ‘flow right face’
  • Qy (numpy.ndarray) – MODFLOW ‘flow front face’. The sign on this array will be flipped by this function so that the y axis is positive to north.
  • Qz (numpy.ndarray) – MODFLOW ‘flow lower face’. The sign on this array will be flipped by this function so that the z axis is positive in the upward direction.
  • delr (numpy.ndarray) – MODFLOW delr array
  • delc (numpy.ndarray) – MODFLOW delc array
  • sat_thk (numpy.ndarray) – Saturated thickness for each cell
Returns:

(qx, qy, qz) – Specific discharge arrays that have been interpolated to cell centers.
Return type:

tuple of numpy.ndarrays
static saturated_thickness(head, top, botm, laytyp, mask_values=None)[source]

Calculate the saturated thickness.

Parameters:
  • head (numpy.ndarray) – head array
  • top (numpy.ndarray) – top array of shape (nrow, ncol)
  • botm (numpy.ndarray) – botm array of shape (nlay, nrow, ncol)
  • laytyp (numpy.ndarray) – confined (0) or convertible (1) of shape (nlay)
  • mask_values (list of floats) – If head is one of these values, then set sat to top - bot
Returns:

sat_thk – Saturated thickness of shape (nlay, nrow, ncol).
Return type:

numpy.ndarray
class SwiConcentration(model=None, botm=None, istrat=1, nu=None)[source]

Bases: object

The binary_header class is a class to create headers for MODFLOW binary files

calc_conc(zeta, layer=None)[source]

Calculate concentrations for a given time step using passed zeta.

Parameters:
  • zeta (dictionary of numpy arrays) – Dictionary of zeta results. zeta keys are zero-based zeta surfaces.
  • layer (int) – Concentration will be calculated for the specified layer. If layer is None, then the concentration will be calculated for all layers. (default is None).
Returns:

conc – Calculated concentration.
Return type:

numpy array

Examples

>>> import flopy
>>> m = flopy.modflow.Modflow.load('test')
>>> c = flopy.plot.SwiConcentration(model=m)
>>> conc = c.calc_conc(z, layer=0)
class UnstructuredPlotUtilities[source]

Bases: object

Collection of unstructured grid and vertex grid compatible plotting helper functions

static arctan2(verts)[source]

Reads 2 dimensional set of verts and orders them using the arctan 2 method

Parameters:verts (np.array of floats) – Nx2 array of verts
Returns:verts – Nx2 array of verts
Return type:np.array of float
static irregular_shape_patch(xverts, yverts)[source]

Patch for vertex cross section plotting when we have an irregular shape type throughout the model grid or multiple shape types.

Parameters:
  • xverts (list) – xvertices
  • yverts (list) – yvertices
Returns:
Return type:

xverts, yverts as np.ndarray
static line_intersect_grid(ptsin, xgrid, ygrid)[source]

Uses cross product method to find which cells intersect with the line and then uses the parameterized line equation to caluculate intersection x, y vertex points. Should be quite fast for large model grids!

Parameters:
  • pts (list) – list of tuple line vertex pairs (ex. [(1, 0), (10, 0)]
  • xgrid (np.array) – model grid x vertices
  • ygrid (np.array) – model grid y vertices
Returns:

vdict
Return type:

dict of cell vertices
advanced_package_bc_helper(pkg, modelgrid, kper)[source]

Helper function for plotting boundary conditions from “advanced” packages

Parameters:
  • pkg (flopy Package objects) –
  • modelgrid (flopy.discretization.Grid object) –
cell_value_points(pts, xedge, yedge, vdata)[source]

Intersect a list of polyline vertices with a rectilinear MODFLOW grid. Vertices at the intersection of the polyline with the grid cell edges is returned. Optionally the original polyline vertices are returned.

Parameters:
  • pts (list) – A list of x, y points and polyline length to extract defining the vertices of a polyline that
  • xedge (numpy.ndarray) – x-coordinate of the edge of each MODFLOW column. The shape of xedge is (NCOL + 1). If xedge is not a numpy.ndarray it is converted to a numpy.ndarray.
  • yedge (numpy.ndarray) – y-coordinate of the edge of each MODFLOW row. The shape of yedge is (NROW + 1). If yedge is not a numpy.ndarray it is converted to a numpy.ndarray.
  • vdata (numpy.ndarray) – Data (i.e., head, hk, etc.) for a rectilinear MODFLOW model grid. The shape of vdata is (NROW, NCOL). If vdata is not a numpy.ndarray it is converted to a numpy.ndarray.
Returns:

vcell – numpy.ndarray of of data values from the vdata numpy.ndarray at x- and y-coordinate locations in pts.
Return type:

numpy.ndarray

Examples

>>> import flopy
>>> vcell = flopy.plotutil.cell_value_points(xpts, xedge, yedge, head[0, :, :])
cvfd_to_patch_collection(verts, iverts)[source]

Create a patch collection from control volume vertices and incidence list

Parameters:
  • verts (ndarray) – 2d array of x and y points.
  • iverts (list of lists) – should be of len(ncells) with a list of vertex numbers for each cell
findrowcolumn(pt, xedge, yedge)[source]

Find the MODFLOW cell containing the x- and y- point provided.

Parameters:
  • pt (list or tuple) – A list or tuple containing a x- and y- coordinate
  • xedge (numpy.ndarray) – x-coordinate of the edge of each MODFLOW column. xedge is dimensioned to NCOL + 1. If xedge is not a numpy.ndarray it is converted to a numpy.ndarray.
  • yedge (numpy.ndarray) – y-coordinate of the edge of each MODFLOW row. yedge is dimensioned to NROW + 1. If yedge is not a numpy.ndarray it is converted to a numpy.ndarray.
Returns:

irow, jcol – Row and column location containing x- and y- point passed to function.
Return type:

int

Examples

>>> import flopy
>>> irow, jcol = flopy.plotutil.findrowcolumn(pt, xedge, yedge)
line_intersect_grid(ptsin, xedge, yedge, returnvertices=False)[source]

Intersect a list of polyline vertices with a rectilinear MODFLOW grid. Vertices at the intersection of the polyline with the grid cell edges is returned. Optionally the original polyline vertices are returned.

Parameters:
  • ptsin (list) – A list of x, y points defining the vertices of a polyline that will be intersected with the rectilinear MODFLOW grid
  • xedge (numpy.ndarray) – x-coordinate of the edge of each MODFLOW column. xedge is dimensioned to NCOL + 1. If xedge is not a numpy.ndarray it is converted to a numpy.ndarray.
  • yedge (numpy.ndarray) – y-coordinate of the edge of each MODFLOW row. yedge is dimensioned to NROW + 1. If yedge is not a numpy.ndarray it is converted to a numpy.ndarray.
  • returnvertices (bool) – Return the original polyline vertices in the list of numpy.ndarray containing vertices resulting from intersection of the provided polygon and the MODFLOW model grid if returnvertices=True. (default is False).
Returns:

(x, y, dlen) – numpy.ndarray of tuples containing the x, y, and segment length of the intersection of the provided polyline with the rectilinear MODFLOW grid.
Return type:

numpy.ndarray of tuples

Examples

>>> import flopy
>>> ptsout = flopy.plotutil.line_intersect_grid(ptsin, xedge, yedge)
plot_cvfd(verts, iverts, ax=None, layer=0, cmap='Dark2', edgecolor='scaled', facecolor='scaled', a=None, masked_values=None, **kwargs)[source]

Generic function for plotting a control volume finite difference grid of information.

Parameters:
  • verts (ndarray) – 2d array of x and y points.
  • iverts (list of lists) – should be of len(ncells) with a list of vertex number for each cell
  • ax (matplotlib.pylot axis) – matplotlib.pyplot axis instance. Default is None
  • layer (int) – layer to extract. Used in combination to the optional ncpl parameter. Default is 0
  • cmap (string) – Name of colormap to use for polygon shading (default is ‘Dark2’)
  • edgecolor (string) – Color name. (Default is ‘scaled’ to scale the edge colors.)
  • facecolor (string) – Color name. (Default is ‘scaled’ to scale the face colors.)
  • a (numpy.ndarray) – Array to plot.
  • masked_values (iterable of floats, ints) – Values to mask.
  • kwargs (dictionary) – Keyword arguments that are passed to PatchCollection.set(**kwargs). Some common kwargs would be ‘linewidths’, ‘linestyles’, ‘alpha’, etc.
Returns:

pc
Return type:

matplotlib.collections.PatchCollection

Examples

plot_shapefile(shp, ax=None, radius=500.0, cmap='Dark2', edgecolor='scaled', facecolor='scaled', a=None, masked_values=None, idx=None, **kwargs)[source]

Generic function for plotting a shapefile.

Parameters:
  • shp (string) – Name of the shapefile to plot.
  • ax (matplolib.pyplot.axes object) –
  • radius (float) – Radius of circle for points. (Default is 500.)
  • cmap (string) – Name of colormap to use for polygon shading (default is ‘Dark2’)
  • edgecolor (string) – Color name. (Default is ‘scaled’ to scale the edge colors.)
  • facecolor (string) – Color name. (Default is ‘scaled’ to scale the face colors.)
  • a (numpy.ndarray) – Array to plot.
  • masked_values (iterable of floats, ints) – Values to mask.
  • idx (iterable int) – A list or array that contains shape numbers to include in the patch collection. Return all shapes if not specified.
  • kwargs (dictionary) – Keyword arguments that are passed to PatchCollection.set(**kwargs). Some common kwargs would be ‘linewidths’, ‘linestyles’, ‘alpha’, etc.
Returns:

pc
Return type:

matplotlib.collections.PatchCollection

Examples

shapefile_extents(shp)[source]

Determine the extents of a shapefile

Parameters:shp (string) – Name of the shapefile to convert to a PatchCollection.
Returns:extents – tuple with xmin, xmax, ymin, ymax from shapefile.
Return type:tuple

Examples

>>> import flopy
>>> fshp = 'myshapefile'
>>> extent = flopy.plot.plotutil.shapefile_extents(fshp)
shapefile_get_vertices(shp)[source]

Get vertices for the features in a shapefile

Parameters:shp (string) – Name of the shapefile to extract shapefile feature vertices.
Returns:vertices – Vertices is a list with vertices for each feature in the shapefile. Individual feature vertices are x, y tuples and contained in a list. A list with a single x, y tuple is returned for point shapefiles. A list with multiple x, y tuples is returned for polyline and polygon shapefiles.
Return type:list

Examples

>>> import flopy
>>> fshp = 'myshapefile'
>>> lines = flopy.plot.plotutil.shapefile_get_vertices(fshp)
shapefile_to_patch_collection(shp, radius=500.0, idx=None)[source]

Create a patch collection from the shapes in a shapefile

Parameters:
  • shp (string) – Name of the shapefile to convert to a PatchCollection.
  • radius (float) – Radius of circle for points in the shapefile. (Default is 500.)
  • idx (iterable int) – A list or array that contains shape numbers to include in the patch collection. Return all shapes if not specified.
Returns:

pc – Patch collection of shapes in the shapefile
Return type:

matplotlib.collections.PatchCollection