在matplotlib中使用更多颜色进行绘图
我正在尝试使用matplotlib绘制散点图,但遇到了“IndexError: pop from empty list”的错误,我不知道该怎么解决。
import matplotlib.pyplot as plt
import matplotlib
import numpy as np
import time
import itertools
d = {'5000cca229d10d09': {374851: 1}, '5000cca229cf3f8f': {372496:3},'5000cca229d106f9': {372496: 3, 372455: 2}, '5000cca229d0b3e4': {380904: 2, 380905: 1, 380906: 1, 386569: 1}, '5000cca229d098f8': {379296: 2, 379297: 2, 379299: 2, 379303: 1, 379306: 1, 379469: 1, 379471: 1, 379459: 1, 379476: 1, 379456: 4, 379609: 4}, '5000cca229d03957': {380160: 3, 380736: 3, 380162: 1, 380174: 1, 381072: 2, 379608: 2, 380568: 3, 380569: 1, 380570: 1, 379296: 3, 379300: 1, 380328: 3, 379306: 1, 380331: 1, 379824: 2, 379825: 1, 379827: 1, 380344: 1, 379836: 1, 379456: 3, 380737: 1, 380739: 1, 379462: 1, 379476: 1, 379992: 3, 379609: 1, 379994: 1, 379611: 1, 379621: 1, 380006: 1, 380904: 3, 380905: 1, 380907: 1, 380535: 3, 380536: 1, 380538: 1}, '5000cca229cf6d0b': {372768: 10, 372550: 15, 372616: 14, 372617: 20, 372653: 3, 372505: 2}, '5000cca229cec4f1': {372510: 132}}
colors = list("rgbcmyk")
for data_dict in d.values():
x = data_dict.keys()
#print x
#X= time.asctime(time.localtime(x))
y = data_dict.values()
#plt.scatter(x,y,color=colors.pop(),s = 60)
plt.scatter(x,y,color=colors.pop(),s = 90, marker='^')
plt.ylabel("Errors" , fontsize=18, color="Green")
plt.xlabel("Occured on",fontsize=18, color="Green")
plt.title("DDN23b", fontsize=25, color="Blue")
plt.gca().get_xaxis().get_major_formatter().set_useOffset(False)
plt.xticks(rotation='vertical')
#plt.ylim(min(y),max(y))
#plt.grid()
#for x, y in dict(itertools.chain(*[item.items() for item in d.values()])).items():
# plt.text(x, y, time.strftime("%m/%d/%y, %H:%M:%S", time.localtime(x*3600)), ha='center', va='top', rotation='vertical', fontsize = '11', fontstyle = 'italic', color = '#844d4d')
plt.xticks(plt.xticks()[0], [time.strftime("%m/%d/%y, %H:%M:%S", time.localtime(item)) for item in plt.xticks()[0]*3600])
plt.legend(d.keys())
mng = plt.get_current_fig_manager()
mng.resize(*mng.window.maxsize())
plt.subplots_adjust(bottom=.24,right=.98,left=0.03,top=.89)
plt.grid()
plt.show()
我有几个数据集,d是一个字典。当数据集较小时,代码运行没有任何错误。但是当数据集变大时,就会出现颜色不够用的问题。我该如何为颜色列表添加更多颜色,以便“d”中的每个键都有自己独特的颜色呢?
欢迎对我的代码进行修改并提出建议。
1 个回答
4
颜色映射是可以调用的。当你给它一个0到1之间的小数时,它会返回一个RGBA颜色值:
In [73]: jet = plt.cm.jet
In [74]: jet(0.5)
Out[74]: (0.49019607843137247, 1.0, 0.47754585705249841, 1.0)
这样,你可以通过把NumPy数组 np.linspace(0, 1, len(d))
传给颜色映射,生成 len(d)
个颜色:
jet = plt.cm.jet
colors = jet(np.linspace(0, 1, len(d)))
这些选中的颜色会在颜色映射的渐变中均匀分布。
import matplotlib.pyplot as plt
import numpy as np
import time
d = {'5000cca229d10d09': {374851: 1}, '5000cca229cf3f8f': {372496:3},'5000cca229d106f9': {372496: 3, 372455: 2}, '5000cca229d0b3e4': {380904: 2, 380905: 1, 380906: 1, 386569: 1}, '5000cca229d098f8': {379296: 2, 379297: 2, 379299: 2, 379303: 1, 379306: 1, 379469: 1, 379471: 1, 379459: 1, 379476: 1, 379456: 4, 379609: 4}, '5000cca229d03957': {380160: 3, 380736: 3, 380162: 1, 380174: 1, 381072: 2, 379608: 2, 380568: 3, 380569: 1, 380570: 1, 379296: 3, 379300: 1, 380328: 3, 379306: 1, 380331: 1, 379824: 2, 379825: 1, 379827: 1, 380344: 1, 379836: 1, 379456: 3, 380737: 1, 380739: 1, 379462: 1, 379476: 1, 379992: 3, 379609: 1, 379994: 1, 379611: 1, 379621: 1, 380006: 1, 380904: 3, 380905: 1, 380907: 1, 380535: 3, 380536: 1, 380538: 1}, '5000cca229cf6d0b': {372768: 10, 372550: 15, 372616: 14, 372617: 20, 372653: 3, 372505: 2}, '5000cca229cec4f1': {372510: 132}}
jet = plt.cm.jet
colors = jet(np.linspace(0, 1, len(d)))
fig, ax = plt.subplots()
for color, data_dict in zip(colors, d.values()):
x = data_dict.keys()
y = data_dict.values()
ax.scatter(x,y,color=color, s = 90, marker='^')
plt.ylabel("Errors" , fontsize=18, color="Green")
plt.xlabel("Occured on",fontsize=18, color="Green")
plt.title("DDN23b", fontsize=25, color="Blue")
ax.get_xaxis().get_major_formatter().set_useOffset(False)
plt.xticks(rotation='vertical')
plt.xticks(plt.xticks()[0],
[time.strftime("%m/%d/%y, %H:%M:%S", time.localtime(item))
for item in plt.xticks()[0]*3600])
plt.legend(d.keys())
plt.subplots_adjust(bottom=.24,right=.98,left=0.03,top=.89)
plt.grid()
plt.show()