Python：专门为子图中的条设置x tick？

Question

我想分析四个工具在运行多个程序时的性能。一个子图是一个工具在所有程序上的结果。结果应该是这样的：

我用for循环遍历程序列表中的每一次绘制一个部分如下：

但情节看起来像一个一个和我不能通过使用axis.set_xticks()来分开它们的x标记。看来这个功能没有效果。

我是否使用正确的功能来设置x刻度？或者我应该如何制作这个情节？

draw_hist_query()可能是最重要的功能对于我的问题

数据样本：

boolector,ppbv,stp,z3 
0.05349588394165039,0.015434503555297852,0.028127193450927734,0.11303281784057617 
0.0027561187744140625,0.004331827163696289,0.007134914398193359,0.016040563583374023 
0.003190755844116211,0.005587577819824219,0.002897500991821289,0.013916015625 
0.009758472442626953,0.02006363868713379,0.0031282901763916016,0.011539697647094727 
0.057138681411743164,0.012826681137084961,0.030836820602416992,0.0217435359954834 

代码：

index = range(len(solvers)) 
fig, axes = plt.subplots(nrows=4) 
solvers = ['z3', 'stp', 'boolector', 'ppbv'] 
colors = ['g', 'c', 'b', 'r', 'y', 'orange', 'grey'] 
ticks = [0.1, 0.5, 1.0, 2.0] 
width=0.2 

# program entry 
def all_time_query(path): 
    csv = xxx.csv # the array of data to be analyzed, one csv for one program 
    for axis in axes: 
     axis.set_xticks(range(len(csv))) 
    for c in csv: 
     multi_time_query(c) # draw the bar pair for c, which shows the upper image for one program on four tools 


def multi_time_query(csv): 
    data = pd.read_csv(csv) 
    for solver in solvers: # the four tools 
     bin = index[solvers.index(solver)] 
     hist_t_query(data, solver, ax=axes[bin]) # details to draw the bar pair, uses dataframe.plot.bar 



def hist_t_query(data, solver, ax): 
    solver_data = pd.DataFrame(data).as_matrix(columns=[solver]) 
    # draw one bar for demo 
    draw_hist_query(pd.DataFrame(solver_data), ax) 


# left of bar pair, the right one is similar 
def draw_hist_query(df, ax): 
    count = [] 
    for i in range(len(ticks)): 
     count.append(df[df < ticks[i]].count()) 
     color = stat.colors[i] 
     if i == 0: 
      count[i].plot.bar(ax=ax, color=color, width=width, position=0) 
     else: 
      (count[i] - count[i - 1]).plot.bar(bottom=count[i - 1], 
               ax=ax, color=color, width=width, position=0) 

Answer 1

最后我解决了这个问题：

我的想法错之前大约是次要情节。我想在一对子已经在那里之后在另一个子图中添加另一个子对。 但是，一个小区应该一起绘制（一次），不应该分开。在我的情况下，一个子图的条应该一起出现，并且只需要四次来绘制所有的子图。

这里是我的代码新版本：

def time_query_project(path): 
    fig, axis = plt.subplots(nrows=4) 
    csv = sio.find_csv(path) 
    data = {} 

    for solver in solvers: 
     for c in csv: 
      df = pd.DataFrame(pd.read_csv(c), columns=[solver]) 
      data.update({get_name(c): df.to_dict()[solver]}) 
     df = pd.DataFrame.from_dict(data, orient='columns') 
     ax = axis[solvers.index(solver)] 
     ax.set_ylabel(solver) 
     hist_t_query(df, ax) 


def hist_t_query(data, solver, ax): 
    solver_data = pd.DataFrame(data).as_matrix(columns=[solver]) 
    # draw one bar for demo 
    draw_hist_query(pd.DataFrame(solver_data), ax) 


# left of bar pair, the right one is similar 
def draw_hist_query(df, ax): 
    count = [] 
    for i in range(len(ticks)): 
     count.append(df[df < ticks[i]].count()) 
     color = stat.colors[i] 
     if i == 0: 
      count[i].plot.bar(ax=ax, color=color, width=width, position=0) 
     else: 
      (count[i] - count[i - 1]).plot.bar(bottom=count[i - 1], 
               ax=ax, color=color, width=width, position=0) 

Answer 2

一般来说，你有几种选择。您可以使用plt.tight_layout()，它会自动执行所有操作，或者您可以使用plt.subplot_adjust()并自行指定每个参数。 正如你可以在文档中看到，签名是这样的：

subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=None, hspace=None) 

而且，如果你会去交互式窗口，你必须有调整参数的选项，你可以看到你的图形将每个参数

更改，然后就可以调用subplot_adjust与任何最适合你。

我希望它有帮助。