Source code for imod.visualize.waterbalance

import itertools
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np


def _draw_bars(ax, x, df, labels, barwidth, colors):
    ndates, _ = df.shape
    bottoms = np.hstack([np.zeros((ndates, 1)), df.cumsum(axis=1).values]).T[:-1]
    heights = df.values.T
    if colors is None:
        for label, bottom, height in zip(labels, bottoms, heights):
            ax.bar(
                x,
                bottom=bottom,
                height=height,
                width=barwidth,
                edgecolor="k",
                label=label,
            )
    else:
        for label, bottom, height, color in zip(labels, bottoms, heights, colors):
            ax.bar(
                x,
                bottom=bottom,
                height=height,
                width=barwidth,
                edgecolor="k",
                label=label,
                color=color,
            )


[docs]def waterbalance_barchart( df, inflows, outflows, datecolumn=None, format="%Y-%m-%d", ax=None, unit=None, colors=None, ): """ Parameters ---------- df : pandas.DataFrame The dataframe containing the water balance data. inflows : listlike of str outflows : listlike of str datecolumn : str, optional format : str, optional, ax : matplotlib.Axes, optional unit : str, optional colors : listlike of strings or tuples Returns ------- ax : matplotlib.Axes Examples -------- >>> fig, ax = plt.subplots() >>> imod.visualize.waterbalance_barchart( >>> ax=ax, >>> df=df, >>> inflows=["Rainfall", "River upstream"], >>> outflows=["Evapotranspiration", "Discharge to Sea"], >>> datecolumn="Time", >>> format="%Y-%m-%d", >>> unit="m3/d", >>> colors=["#ca0020", "#f4a582", "#92c5de", "#0571b0"], >>> ) >>> fig.savefig("Waterbalance.png", dpi=300, bbox_inches="tight") """ # Do some checks if not isinstance(df, pd.DataFrame): raise TypeError("df should be a pandas.DataFrame") if datecolumn is not None: if datecolumn not in df.columns: raise ValueError(f"datecolumn {datecolumn} not in df") for column in itertools.chain(inflows, outflows): if column not in df: raise ValueError(f"{column} not in df") if colors is not None: ncolors = len(colors) nflows = len(inflows + outflows) if ncolors < nflows: raise ValueError( f"Not enough colors: Number of flows is {nflows}, while number of colors is {ncolors}" ) # Deal with colors, takes both dict and list if isinstance(colors, dict): incolors = [colors[k] for k in inflows] outcolors = [colors[k] for k in outflows] elif isinstance(colors, (tuple, list)): incolors = colors[: len(inflows)] outcolors = colors[len(inflows) :] else: incolors = None outcolors = None # Determine x position ndates, _ = df.shape barwidth = 1.0 r1 = np.arange(0.0, ndates * barwidth * 3, barwidth * 3) r2 = np.array([x + barwidth for x in r1]) r_between = 0.5 * (r1 + r2) # Grab ax if not provided directly if ax is None: ax = plt.gca() # Draw inflows _draw_bars( ax=ax, x=r1, df=df[inflows], labels=inflows, barwidth=barwidth, colors=incolors ) _draw_bars( ax=ax, x=r2, df=df[outflows], labels=inflows, barwidth=barwidth, colors=outcolors, ) # Place xticks xticks_location = list(itertools.chain(*zip(r1, r_between, r2))) # Collect the labels, and format them as desired # TODO: might not work for all dateformats? xticks_labels = [] if datecolumn is None: dates = df.index else: dates = df[datecolumn] for date in dates: # Place the date labels two lines (two \n) below the minor labels ("in", "out") xticks_labels.extend(["in", f"\n\n{date.strftime(format)}", "out"]) # Adjust the ticks. Lengthen the major ticks, so they extend down to the dates ax.tick_params(axis="x", which="major", bottom=False, top=False, labelbottom=True) ax.tick_params( axis="x", which="minor", bottom=True, top=False, labelbottom=False, length=barwidth * 45, ) ax.set_xticks(xticks_location) ax.set_xticklabels(xticks_labels) xticks_location_minor = r1[1:] - barwidth ax.set_xticks(xticks_location_minor, minor=True) # Create a legend on the right side of the chart ax.legend( loc="upper left", bbox_to_anchor=(1.03, 1.0), ncol=2, borderaxespad=0, frameon=True, ) # Set a unit on the y-axis if unit is not None: ax.set_ylabel(unit) return ax