在地块右侧添加标签

我正在绘制时间序列数据。在这里，我想问如何在剧情的右侧添加标签。我的代码如下所示：在地块右侧添加标签

import pandas 
import os 
import datetime 
import numpy as np 
import glob 

data_path = os.getcwd() 


def convert_stamp_to_date(stamp): 
    try: 
     d = datetime.datetime.utcfromtimestamp(stamp) 
    except: 
     d = datetime.datetime.utcfromtimestamp(0) 
    d = datetime.datetime(d.year, d.month, d.day, d.hour, d.minute, d.second) 
    return d 

#get data of 25 minutes 
date1 = datetime.datetime(2014,7,20,7,0,0) 
date2 = datetime.datetime(2014,7,20,7,25,0) 

#load Activity data 
activity_df = pandas.read_csv('%s/ITRCProject/oneP/activity.csv'%data_path, index_col=0) 
activity_df['timestamp'] = activity_df['timestamp'].apply(convert_stamp_to_date) 
activity_df = activity_df.drop_duplicates('timestamp') 
condition1 = np.logical_and(activity_df['timestamp']>date1,activity_df['timestamp']<date2) 
activity_df = activity_df[condition1] 
activity_df.columns = ['timestamp', 'activity'] 

#load Call data 
call_df = pandas.read_csv('%s/ITRCProject/oneP/Call.csv'%data_path, index_col=0) 
call_df['timestamp'] = call_df['timestamp'].apply(convert_stamp_to_date) 
call_df = call_df.drop_duplicates('timestamp') 
condition2 = np.logical_and(call_df['timestamp']>date1,call_df['timestamp']<date2) 
call_df = call_df[condition2] 
call_df = call_df[call_df['types']==2] 
call_df['types'] = 'Call_O' 
call_df = call_df[['timestamp','types']] 
call_df.columns = ['timestamp', 'activity'] 

#load SMS data 
sms_df = pandas.read_csv('%s/ITRCProject/oneP/SMS.csv'%data_path, index_col=0) 
sms_df['timestamp'] = sms_df['timestamp'].apply(convert_stamp_to_date) 
sms_df = sms_df.drop_duplicates('timestamp') 
condition3 = np.logical_and(sms_df['timestamp']>date1,sms_df['timestamp']<date2) 
sms_df = sms_df[condition3] 
sms_df = sms_df[(sms_df['types']==1)] 
sms_df['types'] = 'SMS_Sent' 
sms_df = sms_df[['timestamp','types']] 
sms_df.columns = ['timestamp', 'activity'] 

#load Screen data 
screen_df = pandas.read_csv('%s/ITRCProject/oneP/Screen.csv'%data_path, index_col=0) 
screen_df['timestamp'] = screen_df['timestamp'].apply(convert_stamp_to_date) 
screen_df = screen_df.drop_duplicates('timestamp') 
condition4 = np.logical_and(screen_df['timestamp']>date1,screen_df['timestamp']<date2) 
screen_df = screen_df[condition4] 
screen_df = screen_df[screen_df['screenOn']==1] 
screen_df['screenOn'] = 'Screen_On' 
screen_df.columns = ['timestamp', 'activity'] 

#load Charger data 
charger_df = pandas.read_csv('%s/ITRCProject/oneP/BatteryProbe.csv'%data_path, index_col=0) 
charger_df['timestamp'] = charger_df['timestamp'].apply(convert_stamp_to_date) 
charger_df = charger_df.drop_duplicates('timestamp') 
condition5 = np.logical_and(charger_df ['timestamp']>date1,charger_df ['timestamp']<date2) 
charger_df = charger_df[condition5] 
charger_df = charger_df[(charger_df['status']==2)] 
charger_df['status'] = 'charging' 
charger_df = charger_df[['timestamp','status']] 
charger_df.columns = ['timestamp', 'activity'] 

frames = [activity_df, charger_df, screen_df,sms_df,call_df] 
result = pandas.concat(frames, ignore_index=True) 

from matplotlib.ticker import FixedLocator 
font = {'weight' : 'bold', 
     'size' : 35} 
import matplotlib 
matplotlib.rc('font', **font) 
matplotlib.use('Agg') 
import matplotlib.pyplot as plt 
import matplotlib.dates as dates 

%pylab inline 

def colour(x): 
    if 'none' in x: 
     return '#ffaa33' 
    elif 'high' in x: 
     return '#3bb200' 
    elif 'low' in x: 
     return 'yellow' 
    elif 'SMS_Sent' in x: 
     return '#800080' 
    elif 'Call_O' in x: 
     return 'cyan' 
    elif 'Screen_On' in x: 
     return 'magenta' 
    elif 'charging' in x: 
     return '#3388ff' 


def position(x): 
    if 'none' in x: 
     return 0 
    elif 'high' in x: 
     return 1 
    elif 'low' in x: 
     return 2 
    elif 'SMS_Sent' in x: 
     return 3 
    elif 'Call_O' in x: 
     return 4 
    elif 'Screen_On' in x: 
     return 5 
    elif 'charging' in x: 
     return 6 


result['colour'] = result['activity'].apply(colour) 
result['position'] = result['activity'].apply(position) 
result = result.set_index('timestamp') 
result.index.name = None 
result= result.sort_index() 
fig, ax = plt.subplots(figsize=(20,15)) 
ax.scatter(result.index, result.position, s=75, c=result.colour, marker='x') 
ax.set_xlim([date1,date2]) 
ax.spines['top'].set_color('none') 
ax.xaxis.set_ticks_position('bottom') 
ax.set_ylim(-1, 7) 
ax.spines['right'].set_color('none') 
ax.yaxis.set_ticks_position('left') 
labels = ['NONE', 'HIGH','LOW','SENT_SMS','CALL_OUT','SCREEN_ON','CHARGING'] 
tick_locations = [0,1,2,3,4,5,6,7,8,9] 
ax.yaxis.set_major_locator(FixedLocator(tick_locations)) 
ax.set_yticklabels(labels, minor=False) 
plt.grid() 
plt.show()

我的代码的测试结果如下如下：所需的输出如下如下：

来源

2015-10-14 markov zain

您可以创建一个文本框的任何地方，你想在数字。对于这样的情节标签，我将使用轴坐标来绘制与轴相关的文本。

这里是一个类似于上面的布局为例（因为你没有提供的数据，我不能完全复制的情节）：

fig, ax = plt.subplots(figsize=(8, 8)) 
ax.scatter(np.random.rand(100), np.random.rand(100), 
      marker='+', c=np.random.rand(100), 
      cmap='hsv') 
ax.text(1.05, 0.5, "20 July 2014 07:00:00 - 20 July 2014 07:25:00", 
     rotation=90, size=16, weight='bold', 
     bbox=dict(edgecolor='lightgreen', facecolor='none', pad=10, linewidth=3), 
     ha='left', va='center', transform=ax.transAxes)

结果看起来是这样的：

如果您实际上不想要绿色框，则可以删除bbox参数。

来源

2015-10-14 02:56:55 jakevdp

在地块右侧添加标签

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