Line plots i.e. graphs

Example 27: Basic line plot

Making a basic line plot

f = cf.read(f"cfplot_data/ggap.nc")[1]

g = f.collapse("X: mean")

cfp.gopen()
cfp.lineplot(
    g.subspace(pressure=100),
    marker="o",
    color="blue",
    title="Zonal mean zonal wind at 100mb",
)
cfp.gclose()

Note other valid markers are:

'.' point

',' pixel

'o' circle

'v' triangle_down

'^' triangle_up

'<' triangle_left

'>' triangle_right

'1' tri_down

'2' tri_up

'3' tri_left

'4' tri_right

'8' octagon

's' square

'p' pentagon

'*' star

'h' hexagon1

'H' hexagon2

'+' plus

'x' x

'D' diamond

'd' thin_diamond

Example 28: Line plot with a legend

Adding a legend to annotate a line plot with multiple plotted lines

f = cf.read(f"cfplot_data/ggap.nc")[1]

g = f.collapse("X: mean")

xticks = [-90, -75, -60, -45, -30, -15, 0, 15, 30, 45, 60, 75, 90]
xticklabels = [
    "90S",
    "75S",
    "60S",
    "45S",
    "30S",
    "15S",
    "0",
    "15N",
    "30N",
    "45N",
    "60N",
    "75N",
    "90N",
]
xpts = [-30, 30, 30, -30, -30]
ypts = [-8, -8, 5, 5, -8]

cfp.gset(xmin=-90, xmax=90, ymin=-10, ymax=50)

cfp.gopen()
cfp.lineplot(
    g.subspace(pressure=100),
    marker="o",
    color="blue",
    title="Zonal mean zonal wind",
    label="100mb",
)
cfp.lineplot(
    g.subspace(pressure=200),
    marker="D",
    color="red",
    label="200mb",
    xticks=xticks,
    xticklabels=xticklabels,
    legend_location="upper right",
)
cfp.plotvars.plot.plot(xpts, ypts, linewidth=3.0, color="green")
cfp.plotvars.plot.text(
    35, -2, "Region of interest", horizontalalignment="left"
)
cfp.gclose()

When making a multiple line plot:

a) Set the axis limits if required with cfp.gset before plotting the lines.

Using cfp.gset after the last line has been plotted may give unexpected

axis limits and / or labelling. This is a feature of matplotlib.

b) The last call to lineplot is the one that any of the above

axis overrides should be placed in.

c) All calls to lineplot with the label attribute will appear in the legend.

The cfp.plotvars.plot object contains the matplotlib plot and will accept normal Matplotlib plotting commands. As an example of this the following code within a cfp.gopen() and cfp.gclose() construct will make a legend that is independent of any previously made lines and attached labels.

import matplotlib.lines as mlines

green_line = mlines.Line2D([], [], color='green', label='green')

black_line = mlines.Line2D([], [], color='black', ls='--' , label='black dashed')

cfp.plotvars.plot.legend(handles=[green_line, black_line])

Valid locations for the legend_location keyword are:

'right'

'center left'

'upper right'

'lower right'

'best'

'center'

'lower left'

'center right'

'upper left'

'upper center'

'lower center'

When making a call to lineplot the following parameters overide any predefined CF defaults:

title=None - plot title

xunits=None - x units

yunits=None - y units

xname=None - x name

yname=None - y name

xticks=None - x ticks

xticklabels=None - x tick labels

yticks=None - y ticks

yticklabels - y tick labels

Example 29: Time series line plot

Making a basic line plot for a time series where the data shown is global average annual temperature

f = cf.read(f"cfplot_data/tas_A1.nc")[0]

temp = f.subspace(time=cf.wi(cf.dt("1900-01-01"), cf.dt("1980-01-01")))
temp_annual = temp.collapse("T: mean", group=cf.Y())
temp_annual_global = temp_annual.collapse("area: mean", weights="area")
temp_annual_global.Units -= 273.15

cfp.lineplot(
    temp_annual_global,
    title="Global average annual temperature",
    color="blue",
)

In this example we subset a time data series of global temperature, area mean the data, convert to Celsius and plot a linegraph.

When using gset to set the limits on the plotting axes and a time axis pass time strings to give the limits i.e. cfp.gset(xmin='1980-1-1', xmax='1990-1-1', ymin=285, ymax=295)

The correct date format is YYYY-MM-DD or YYYY-MM-DD HH:MM:SS. Anything else will give unexpected results.

Example 30: Line plot with two x axes

Adding an extra x axis to a line plot

tol = cf.RTOL(1e-5)

fl = cf.read(f"cfplot_data/ggap.nc")
f = fl[1]

u = f.collapse("X: mean")
u1 = u.subspace(Y=cf.isclose(-61.12099075))
u2 = u.subspace(Y=cf.isclose(0.56074494))

g = fl[0]
t = g.collapse("X: mean")
t1 = t.subspace(Y=cf.isclose(-61.12099075))
t2 = t.subspace(Y=cf.isclose(0.56074494))

cfp.gopen()
cfp.gset(-30, 30, 1000, 0)
cfp.lineplot(u1, color="r")
cfp.lineplot(u2, color="r")
cfp.gset(190, 300, 1000, 0, twiny=True)
cfp.lineplot(t1, color="b")
cfp.lineplot(t2, color="b")
cfp.gclose()

In this example we plot two x-axes, one with zonal mean zonal wind data and one with temperature data. The option for a twin x-axis is twiny=True. This is a matplotlib keyword which has been adopted within the cf-plot code.