打印减少语法错误：语法无效

Question

When I call this method patternFinder() I got a error like this

def patternFinder():
    avgaLine=((bid+ask)/2)
    x=len(avgaLine)-30
    y=11

    while y<x:
        outcomeRange=avgaLine[y+20:y+30]
        currentPoint=avgaLine[y]

        print reduce((lambda x,y:x+y,outcomeRange)/len(outcomeRange))
        print (currentPoint)
        print ('_________')

        time.sleep(5555)

I get this error:

File <ipython-input-66-a32566f8689e> , line 21
print reduce((lambda x,y:x+y,outcomeRange)/len(outcomeRange))
SyntaxError: invalid syntax

Answer 1

That's not the correct way to use reduce (the division should be done after the reduction), and besides you don't even need to use reduce in here. If you want to calculate an average, try this instead:

print( sum(outcomeRange) / len(outcomeRange) )

By the way, beware of integer division. Make sure that outcomeRange contains at least one decimal value, or that you imported the current division function:

from __future__ import division

Answer 2

reduce takes two separate arguments, function and iterable. So, you line should be

reduce(lambda x,y:x+y,  outcomeRange/len(outcomeRange))

However, also make sure that your outcomeRange is a numpy array, otherwise you'll get another syntax error for trying to divide it by a number. Otherwise, convert the division to [x/len(outcomeRange) for x in outcomeRange]

In that case, it would be better to divide by the lenght after the summation is done, so, you could write

reduce(lambda x, y: x+y, outcomeRange) / len(outcomeRange)

Answer 3

You are most likely using Python 3+, which means that the syntax of your print statement is incorrect. It needs to be in parentheses:

print(reduce((lambda x,y:x+y,outcomeRange)/len(outcomeRange)))

You've done it correctly in the other 2 print statements, I guess you've just missed it here.

Answer 4

For Python 3.8 (Jupyter Notebook Anaconda)

import matplotlib
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
import matplotlib.dates as mdates
import numpy as np
import time

def bytespdate2num(b):
    return mdates.datestr2num(b.decode('utf-8'))

date, bid, ask = np.loadtxt('GBPUSD1d.txt', unpack=True,
                            delimiter=',', converters={0:bytespdate2num})

def percentChange (startPoint, currentPoint):
    return ((float(currentPoint)-startPoint)/startPoint)*100.0

def patternFinder():
    avgLine = ((bid+ask)/2)
    x = len(avgLine) - 30

    y = 11
    while y < x:
        p1 = percentChange(avgLine[y-10], avgLine[y-9])
        p2 = percentChange(avgLine[y-10], avgLine[y-8])
        p3 = percentChange(avgLine[y-10], avgLine[y-7])
        p4 = percentChange(avgLine[y-10], avgLine[y-6])
        p5 = percentChange(avgLine[y-10], avgLine[y-5])
        p6 = percentChange(avgLine[y-10], avgLine[y-4])
        p7 = percentChange(avgLine[y-10], avgLine[y-3])
        p8 = percentChange(avgLine[y-10], avgLine[y-2])
        p9 = percentChange(avgLine[y-10], avgLine[y-1])
        p10 = percentChange(avgLine[y-10], avgLine[y])

        outcomeRange = avgLine[y+20:y+30]
        currentPoint = avgLine[y]

        print (sum(outcomeRange) / len(outcomeRange) )
        print (currentPoint)
        print (' ____')

        print (p1, p2, p3, p4, p5, p6, p7, p8, p9, p10)
        y += 1
        time.sleep(5555)

patternFinder()

Output

1.553601

1.553555

-0.001930961683282023 -0.0032182694721319405 -0.0032182694721319405 -0.0035400964193622853 -0.003861923366564046 -0.005471058102644308 -0.0061147119970621205 -0.00450557726099615 -0.00450557726099615 -0.004827404208212203