Question

我编写了一个代码，用python的matplotlib库绘制水平条形图。

我的目标是调整条形图的宽度，但与原点的距离必须保持不变，即5.6。简而言之，我的目的是根据宽度修剪尺寸，保持长度相同。我无法弄清楚使用子图给出的例子。

以下是代码：

import matplotlib.pyplot as plt;plt.rcdefaults()
from numpy.random import rand
from numpy import arange
import numpy as np

data = np.genfromtxt('C:\\programming\\Python27\\libra_graphs\\File\\histogram.csv',delimiter=',')
diff = 0
time_lst = []
for row in data:
    if not np.isnan(row[7]):
        diff = row[7]-diff
time_lst.append(diff)

print time_lst,len(time_lst)
y_pos = np.arange(len(time_lst))
print y_pos
val = np.array(diff)
print val

plt.barh(y_pos, val,align='center',height = 0.5 ,color='r',alpha=0.5)
plt.yticks(y_pos)

plt.xlabel('Time(seconds)')
plt.title('Job Execution LIBRA')

plt.show()

Answer 1

我绘制了3个条形图，问题已解决。

import matplotlib.pyplot as plt;plt.rcdefaults()
from numpy.random import rand
from numpy import arange
import numpy as np

def libra_execution_time():
    data = np.genfromtxt('C:\\programming\\Python27\\libra_graphs\\File\\histogram.csv',delimiter=',')

    hash_diff,key_diff,binary_diff = 0,0,0

    hash_time_lst,key_time_lst,binary_time_lst = [],[],[]

    for row in data:
        if not np.isnan(row[7]):
            hash_diff = row[7]-hash_diff
    hash_time_lst.append(hash_diff)

    for row in data:
        if not np.isnan(row[8]):
            key_diff = row[8]-key_diff
    key_time_lst.append(key_diff)

    for row in data:
        if not np.isnan(row[9]):
            binary_diff = row[9]-binary_diff
    binary_time_lst.append(binary_diff)

    print "#Hash Partitioner--->" ,hash_time_lst,len(hash_time_lst)
    print "#Key Field Partitioenr--->", key_time_lst,len(key_time_lst)
    print "#Binary Partitioner--->",binary_time_lst,len(binary_time_lst)


    #x_lst = (hash_time_lst + key_time_lst + binary_time_lst)
    #print x_lst
    job_time = {"Hash Time":hash_time_lst,"Key_Time":key_time_lst,"Binary Time":binary_time_lst}
    print job_time
    print job_time.keys(),job_time.values()

    y_pos = np.arange(len(job_time.values()))
    print "Y position",y_pos
    val = np.array(job_time.values())
    print val


    plt.barh(y_pos,val ,align='center',height = 0.5 ,color=('r','y','g'))
    plt.yticks(y_pos,job_time.keys())

    plt.xlabel('Time(seconds)')
    plt.ylabel('Performance--->')
    plt.title('Job Execution LIBRA')

    plt.show()

libra_execution_time()

Python MatPlotlib条形图 - 调整宽度

1 个答案: