"""Module for map plots of surfaces, using matplotlib."""
import numpy as np
import numpy.ma as ma
from xtgeo.common.log import null_logger
from .baseplot import BasePlot
logger = null_logger(__name__)
[docs]
class Map(BasePlot):
"""Class for plotting a map, using matplotlib."""
[docs]
def __init__(self):
"""The constructor method for a Map object."""
super().__init__()
clsname = f"{type(self).__module__}.{type(self).__name__}"
logger.info(clsname)
self._wells = None
self._surface = None
self._tight = False
self._wfence = None
self._showok = True # to indicate if plot is OK to show
self._legendtitle = "Map"
# =========================================================================
# Properties
# =========================================================================
@property
def pagesize(self):
"""Returns page size."""
return self._pagesize
# =========================================================================
# Functions methods (public)
# =========================================================================
[docs]
def plot_surface(
self,
surf,
minvalue=None,
maxvalue=None,
contourlevels=None,
xlabelrotation=None,
colormap=None,
logarithmic=False,
):
"""Input a surface and plot it."""
# need a deep copy to avoid changes in the original surf
logger.info("The key contourlevels %s is not in use", contourlevels)
usesurf = surf.copy()
if usesurf.yflip < 0:
usesurf.swapaxes()
if abs(surf.rotation) > 0.001:
usesurf.unrotate()
xi, yi, zi = usesurf.get_xyz_values()
zimask = ma.getmaskarray(zi).copy() # yes need a copy!
legendticks = None
if minvalue is not None and maxvalue is not None:
minv = float(minvalue)
maxv = float(maxvalue)
step = (maxv - minv) / 10.0
legendticks = []
for i in range(10 + 1):
llabel = float(f"{minv + step * i:9.4f}")
legendticks.append(llabel)
zi.unshare_mask()
zi[zi < minv] = minv
zi[zi > maxv] = maxv
# need to restore the mask:
zi.mask = zimask
# note use surf.min, not usesurf.min here ...
notetxt = (
"Note: map values are truncated from ["
+ str(surf.values.min())
+ ", "
+ str(surf.values.max())
+ "] "
+ "to interval ["
+ str(minvalue)
+ ", "
+ str(maxvalue)
+ "]"
)
self._fig.text(0.99, 0.02, notetxt, ha="right", va="center", fontsize=8)
logger.info("Legendticks: %s", legendticks)
if minvalue is None:
minvalue = usesurf.values.min()
if maxvalue is None:
maxvalue = usesurf.values.max()
# this will override current instance colormap locally, and is
# therefore reset afterwards
keepcolor = self.colormap
if colormap is not None:
self.colormap = colormap
levels = np.linspace(minvalue, maxvalue, self.contourlevels)
logger.debug("Number of contour levels: %s", levels)
import matplotlib.pyplot as plt
plt.setp(self._ax.xaxis.get_majorticklabels(), rotation=xlabelrotation)
# zi = ma.masked_where(zimask, zi)
# zi = ma.masked_greater(zi, xtgeo.UNDEF_LIMIT)
logger.info("Current colormap is %s, requested is %s", self.colormap, colormap)
logger.info("Current colormap name is %s", self.colormap.name)
uselevels = levels if ma.std(zi) > 1e-07 else 1
try:
if logarithmic is False:
locator = None
ticks = legendticks
im = self._ax.contourf(
xi, yi, zi, uselevels, locator=locator, cmap=self.colormap
)
else:
logger.info("use LogLocator")
import matplotlib as mpl
locator = mpl.ticker.LogLocator()
ticks = None
uselevels = None
im = self._ax.contourf(xi, yi, zi, locator=locator, cmap=self.colormap)
self._fig.colorbar(im, ticks=ticks)
except ValueError as err:
logger.warning("Could not make plot: %s", err)
plt.gca().set_aspect("equal", adjustable="box")
self.colormap = keepcolor
[docs]
def plot_faults(
self,
fpoly,
idname="POLY_ID",
color="k",
edgecolor="k",
alpha=0.7,
linewidth=0.8,
):
"""Plot the faults.
Args:
fpoly (object): A XTGeo Polygons object
idname (str): Name of column which has the faults ID
color (c): Fill color model c according to Matplotlib_
edgecolor (c): Edge color according to Matplotlib_
alpha (float): Degree of opacity
linewidth (float): Line width
.. _Matplotlib: http://matplotlib.org/api/colors_api.html
"""
import matplotlib as mpl
aff = fpoly.get_dataframe(copy=False).groupby(idname)
for name, _group in aff:
# make a dataframe sorted on faults (groupname)
myfault = aff.get_group(name)
# make a list [(X,Y) ...];
af = list(zip(myfault["X_UTME"].values, myfault["Y_UTMN"].values))
px = mpl.patches.Polygon(
af,
alpha=alpha,
color=color,
ec=edgecolor,
lw=linewidth,
)
if px.get_closed():
self._ax.add_artist(px)
else:
IOError(f"A polygon is not closed: {px}")
[docs]
def plot_polygons(self, fpoly, idname="POLY_ID", color="k", linewidth=0.8):
"""Plot a polygons instance.
Args:
fpoly (object): A XTGeo Polygons object
idname (str): Name of column which has the faults ID
color (c): Line color model c according to Matplotlib_
linewidth (float): Line width
.. _Matplotlib: http://matplotlib.org/api/colors_api.html
"""
aff = fpoly.get_dataframe(copy=False).groupby(idname)
for _name, group in aff:
# make a dataframe sorted on groupname
pname = fpoly.name
xarr = group[fpoly.xname].values
yarr = group[fpoly.yname].values
self._ax.plot(xarr, yarr, label=pname, lw=linewidth, color=color)
self._ax.legend()
[docs]
def plot_points(self, points):
"""Plot a points set on the map.
This can be be useful e.g. for plotting the underlying point set
that makes a gridded map.
Args:
points (Points): A XTGeo Points object X Y VALUE
"""
# This function is "in prep"
dataframe = points.get_dataframe(copy=False)
self._ax.scatter(
dataframe["X_UTME"].values, dataframe["Y_UTMN"].values, marker="x"
)
[docs]
def plot_wells(self, wells):
"""Plot wells on the map.
Args:
wells (Wells): A XTGeo Wells object (contains a number of Well
instances).
"""
for well in wells.wells:
dataframe = well.get_dataframe(copy=False)
xval = dataframe["X_UTME"].values
yval = dataframe["Y_UTMN"].values
self._ax.plot(xval, yval)
self._ax.annotate(well.name, xy=(xval[-1], yval[-1]))