Customization

Customization

• A tick is a short line on an axis. For category axes, ticks separate each category. For value axes, ticks mark the major divisions and show the exact point on an axis that the axis label defines. Ticks are always the same color and line style as the axis.

• Ticks are the markers denoting data points on axes. Matplotlib's default tick locators and formatters are designed to be generally sufficient in many common situations. Position and labels of ticks can be explicitly mentioned to suit specific requirements.

• Fig. 5.9.1 shows ticks.

• Ticks come in two types: major and minor.

a) Major ticks separate the axis into major units. On category axes, major ticks are the only ticks available. On value axes, one major tick appears for every major axis division.

b) Minor ticks subdivide the major tick units. They can only appear on value axes. One minor tick appears for every minor axis division.

• By default, major ticks appear for value axes. xticks is a method, which can be used to get or to set the current tick locations and the labels.

• The following program creates a plot with both major and minor tick marks, customized to be thicker and wider than the default, with the major tick marks point into and out of the plot area.

importnumpyasnp

importmatplotlib.pyplotasplt

# A selection of functions on rnabcissa points for 0 <= x < 1

rn=100

rx=np.linspace(0,1,rn, endpoint=False)

deftophat(rx):

"""Top hat function: y = 1 for x < 0.5, y=0 for x >= 0.5"""

ry=np.ones(rn)

ry[rx>=0.5]=0

returnry

# A dictionary of functions to choose from

ry={half-sawtooth':lambdarx:rx.copy(),

'top-hat':tophat,

'sawtooth':lambdarx:2*np.abs(rx-0.5)}

# Repeat the chosen function nrep times

nrep=4

x=np.linspace (0,nrep,nrep*rn, endpoint=False)

y=np.tile(ry['top-hat'] (rx), nrep)

fig=plt.figure()

ax=fig.add_subplot(111)

ax.plot(x,y,'k',lw=2)

# Add a bit of padding around the plotted line to aid visualization

ax.set_ylim(-0.1,1.1)

ax.set_xlim(x[0]-0.5,x[-1]+0.5)

# Customize the tick marks and turn the grid on

ax.minorticks_on()

ax.tick_params (which='major',length=10, width=2,direction='inout')

ax.tick_params(which='minor',length=5,width=2, direction='in')

ax.grid(which='both')

plt.show()

Output: