本文整理汇总了Python中matplotlib.ticker.ScalarFormatter.set_useOffset方法的典型用法代码示例。如果您正苦于以下问题：Python ScalarFormatter.set_useOffset方法的具体用法？Python ScalarFormatter.set_useOffset怎么用？Python ScalarFormatter.set_useOffset使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类matplotlib.ticker.ScalarFormatter的用法示例。
在下文中一共展示了ScalarFormatter.set_useOffset方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: ra_plot
# 需要导入模块: from matplotlib.ticker import ScalarFormatter [as 别名]
# 或者: from matplotlib.ticker.ScalarFormatter import set_useOffset [as 别名]
def ra_plot(array_dict, tcas_ra_array, tcas_ctl_array, tcas_up_array, tcas_down_array,
vert_ctl_array, sens_array, filename, orig, dest, tstart, tend):
'''plot tcas: vertical speed + controls '''
import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter
formatter = ScalarFormatter(useOffset=False)
formatter.set_powerlimits((-8,8))
formatter.set_scientific(False)
formatter.set_useOffset(0.0)
plt.figure(figsize=(15,15)) #set size in inches
plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=None, hspace=0.5)
# top time series plot
axts = plt.subplot2grid((8, 1), (0, 0), rowspan=2) #time series
axts.xaxis.set_major_formatter(formatter)
series_names = array_dict.keys() #only first 4
series_formats = ['k','r','g','b'] #color codes
for i,nm in enumerate(series_names):
ln=axts.plot(array_dict[nm], series_formats[i], alpha=0.45)
plt.setp(ln, linewidth=2)
leg = axts.legend(series_names, 'upper left', fancybox=True)
leg.get_frame().set_alpha(0.5)
axts.grid(True, color='gray')
plt.title('Vertical Speed (fpm)')
axts.autoscale(enable=False)
# tcas ra
ax_ra = plt.subplot2grid((8, 1), (2, 0), sharex=axts) #
ra_states = tcas_ra_array.values_mapping.values()
ra_states = [s.replace('Most Dangerous','') for s in ra_states]
ra_array = tcas_ra_array.data
plot_mapped_array(plt, ax_ra, ra_states, ra_array, title="TCAS RA")
# combined control
ax_ctl = plt.subplot2grid((8, 1), (3, 0), sharex=axts) #
ctl_states = tcas_ctl_array.values_mapping.values()
ctl_states = [s.replace('Advisory','Advzy').replace('Corrective', 'Corr.') for s in ctl_states]
ctl_array = tcas_ctl_array.data
plot_mapped_array(plt, ax_ctl, ctl_states, ctl_array, title="TCAS Combined Control")
# up and down advisory
ax_updown = plt.subplot2grid((8, 1), (4, 0), sharex=axts, rowspan=2)
up_states = [' ']+tcas_up_array.values_mapping.values()
down_states = [' ']+tcas_down_array.values_mapping.values()
ud_states = up_states + down_states
def disp_state(st):
st = st.replace('Descent Corrective','Desc Corr.')
st = st.replace('Descend ','Desc>')
st = st.replace('Advisory','Advzy').replace('advisory','Advzy')
st = st.replace("Don't Climb ","Don't Climb>")
return st
ud_states = [ disp_state(s) for s in ud_states]
plt.yticks( np.arange(len(ud_states)), ud_states )
up_array = tcas_up_array.data + 1 # adjust for display
ax_updown.plot(up_array, 'g')
down_array = tcas_down_array.data + len(up_states)+1 # adjust for display
ax_updown.plot(down_array, 'r')
ax_updown.grid(True, color='gray')
plt.ylim(0, len(up_states) + len(down_states))
plt.title('TCAS Up/Down Advisory')
# vertical control
ax_vert = plt.subplot2grid((8, 1), (6, 0), sharex=axts)
vert_states = vert_ctl_array.values_mapping.values()
vert_states = [' ']+[s.replace("Advisory is not one of the following types",'NA') for s in vert_states]
vert_array = vert_ctl_array.data + 1
plot_mapped_array(plt, ax_vert, vert_states, vert_array, title="TCAS Vertical Control")
#sensitivity mode
ax_sens = plt.subplot2grid((8, 1), (7, 0), sharex=axts)
sens_states = sens_array.values_mapping.values()
sens_states = [' ']+[s.replace("SL = ",'') for s in sens_states]
sens_arr = sens_array.data + 1 # adjust for display
plot_mapped_array(plt, ax_sens, sens_states, sens_arr, title="TCAS Sensitivity Mode")
plt.xlabel('time index')
plt.xlim(tstart, tend)
plt.suptitle('TCAS RA: '+filename.value + '\n '+orig.value['code']['icao']+'-'+dest.value['code']['icao']+ ' '+str(tstart)+':'+str(tend))
return plt