python - 如何从 TA-lib 结果中列出一个列表？
问题描述
这是关于如何从 TA-lib 移动平均线的最后六个结果中制作一个有用的列表。
这是我的平均代码：
closes_TREND = []
MOVING_AVERAGES = []
klines_TREND = client.get_historical_klines(TRADE_SYMBOL, Client.KLINE_INTERVAL_1HOUR, "20 hours ago UTC")
for data in klines_TREND:
closes = data[4]
closes_TREND.append(float(closes))
np_closes_TREND = np.array(closes_TREND)
moving_average = talib.MA(np_closes_TREND, SMA_PERIOD)
给出这个结果：
[nan]
[nan nan]
[nan nan nan]
[nan nan nan nan]
[nan nan nan nan nan]
[nan nan nan nan nan nan]
[ nan nan nan nan
nan nan 49083.85571429]
[ nan nan nan nan
nan nan 49083.85571429 49056.04857143]
[ nan nan nan nan
nan nan 49083.85571429 49056.04857143
49062.34142857]
[ nan nan nan nan
nan nan 49083.85571429 49056.04857143
49062.34142857 49103.36142857]
[ nan nan nan nan
nan nan 49083.85571429 49056.04857143
49062.34142857 49103.36142857 49182.70857143]
[ nan nan nan nan
nan nan 49083.85571429 49056.04857143
49062.34142857 49103.36142857 49182.70857143 49406.18142857]
[ nan nan nan nan
nan nan 49083.85571429 49056.04857143
49062.34142857 49103.36142857 49182.70857143 49406.18142857
49649.40285714]
[ nan nan nan nan
nan nan 49083.85571429 49056.04857143
49062.34142857 49103.36142857 49182.70857143 49406.18142857
49649.40285714 49842.8 ]
[ nan nan nan nan
nan nan 49083.85571429 49056.04857143
49062.34142857 49103.36142857 49182.70857143 49406.18142857
49649.40285714 49842.8 50040.02142857]
[ nan nan nan nan
nan nan 49083.85571429 49056.04857143
49062.34142857 49103.36142857 49182.70857143 49406.18142857
49649.40285714 49842.8 50040.02142857 50210.48285714]
[ nan nan nan nan
nan nan 49083.85571429 49056.04857143
49062.34142857 49103.36142857 49182.70857143 49406.18142857
49649.40285714 49842.8 50040.02142857 50210.48285714
50386.27285714]
[ nan nan nan nan
nan nan 49083.85571429 49056.04857143
49062.34142857 49103.36142857 49182.70857143 49406.18142857
49649.40285714 49842.8 50040.02142857 50210.48285714
50386.27285714 50509.12285714]
[ nan nan nan nan
nan nan 49083.85571429 49056.04857143
49062.34142857 49103.36142857 49182.70857143 49406.18142857
49649.40285714 49842.8 50040.02142857 50210.48285714
50386.27285714 50509.12285714 50483.18714286]
[ nan nan nan nan
nan nan 49083.85571429 49056.04857143
49062.34142857 49103.36142857 49182.70857143 49406.18142857
49649.40285714 49842.8 50040.02142857 50210.48285714
50386.27285714 50509.12285714 50483.18714286 50467.02571429]
我需要的是列表中的最后六个值，如下所示：
[50040.02, 50210.48, 50386.27, 50509.12, 50483.18, 50467.02]
我已经尝试了很多，这是最接近的：
test = [round(num, 2) for num in moving_average]
y = test[14:]
它给了我这个：
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[50040.02]
[50040.02, 50210.48]
[50040.02, 50210.48, 50386.27]
[50040.02, 50210.48, 50386.27, 50509.12]
[50040.02, 50210.48, 50386.27, 50509.12, 50483.19]
[50040.02, 50210.48, 50386.27, 50509.12, 50483.19, 50467.02]
我需要多项式拟合的列表，现在我遇到了在 x 和 y 中具有相同长度的问题，这可能是因为列表 y 的构建方式。
在 de 多项式拟合中，x = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] 尝试得到 y = [50040.02, 50210.48, 50386.27, 50509.12, 50483.19, 50467.02]
有什么建议么？
PS编辑了我的问题以回答评论。
12-4-21 第二次编辑：
y = test[-6:], 给了我这个：它即将接近，但仍然不适合多项式拟合。
[nan]
[nan, nan]
[nan, nan, nan]
[nan, nan, nan, nan]
[nan, nan, nan, nan, nan]
[nan, nan, nan, nan, nan, nan]
[nan, nan, nan, nan, nan, 50058.15]
[nan, nan, nan, nan, 50058.15, 50115.52]
[nan, nan, nan, 50058.15, 50115.52, 50134.18]
[nan, nan, 50058.15, 50115.52, 50134.18, 50205.48]
[nan, 50058.15, 50115.52, 50134.18, 50205.48, 50262.16]
[50058.15, 50115.52, 50134.18, 50205.48, 50262.16, 50257.04]
[50115.52, 50134.18, 50205.48, 50262.16, 50257.04, 50262.79]
[50134.18, 50205.48, 50262.16, 50257.04, 50262.79, 50258.97]
[50205.48, 50262.16, 50257.04, 50262.79, 50258.97, 50317.7]
[50262.16, 50257.04, 50262.79, 50258.97, 50317.7, 50361.69]
[50257.04, 50262.79, 50258.97, 50317.7, 50361.69, 50371.85]
[50262.79, 50258.97, 50317.7, 50361.69, 50371.85, 50463.78]
[50258.97, 50317.7, 50361.69, 50371.85, 50463.78, 50585.92]
[50317.7, 50361.69, 50371.85, 50463.78, 50585.92, 50704.61]
print(type(y[0]))
给了我这个：
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
<class 'numpy.float64'>
编辑 23-4
这就是它为 x、y 和 polyn 打印的内容。适合，我只需要最后一个
x = :
[0.0, 1.0, 2.0, 3.0, 4.0, 5.0]
y = :
[41676.59, 41223.05, 40937.1, 40708.92, 40627.29, 40770.61]
polyn. fit = :
[ -187.01028571 41458.11904762]
x = :
[0.0, 1.0, 2.0, 3.0, 4.0, 5.0]
y = :
[41223.05, 40937.1, 40708.92, 40627.29, 40770.61, 40747.72]
polyn. fit = :
[ -84.50714286 41047.04952381]
x = :
[0.0, 1.0, 2.0, 3.0, 4.0, 5.0]
y = :
[40937.1, 40708.92, 40627.29, 40770.61, 40747.72, 40770.06]
polyn. fit = :
[-1.64422857e+01 4.08013890e+04]
x = :
[0.0, 1.0, 2.0, 3.0, 4.0, 5.0]
y = :
[40708.92, 40627.29, 40770.61, 40747.72, 40770.06, 41008.3]
polyn. fit = :
[ 54.352 40636.27 ]
x = :
[0.0, 1.0, 2.0, 3.0, 4.0, 5.0]
y = :
[40627.29, 40770.61, 40747.72, 40770.06, 41008.3, 41136.19]
polyn. fit = :
[ 93.71171429 40609.08238095]
x = :
[0.0, 1.0, 2.0, 3.0, 4.0, 5.0]
y = :
[40770.61, 40747.72, 40770.06, 41008.3, 41136.19, 41329.56]
polyn. fit = :
[ 119.95428571 40660.52095238]
x = :
[0.0, 1.0, 2.0, 3.0, 4.0, 5.0]
y = :
[40747.72, 40770.06, 41008.3, 41136.19, 41329.56, 41339.63]
polyn. fit = :
[ 136.16971429 40714.81904762]
x = :
[0.0, 1.0, 2.0, 3.0, 4.0, 5.0]
y = :
[40770.06, 41008.3, 41136.19, 41329.56, 41339.63, 41358.35]
polyn. fit = :
[ 117.966 40862.1 ]
x = :
[0.0, 1.0, 2.0, 3.0, 4.0, 5.0]
y = :
[41008.3, 41136.19, 41329.56, 41339.63, 41358.35, 41526.3]
polyn. fit = :
[ 93.33 41049.73] #>> this is the correct value!
每次它执行时，我都会一遍又一遍地得到这些值......
解决方案
回复较晚，抱歉。我认为由于moving_average并不总是返回长度为 6 的 numpy 数组，因此y在继续之前，您需要有一个 if 语句来检查长度何时等于 6。您还应该考虑添加行moving_average = moving_average[~np.isnan(moving_average)]以删除其中的nan值，moving_average以便y其列表中没有任何 nan 值。
closes_TREND = []
MOVING_AVERAGES = []
klines_TREND = client.get_historical_klines("BTCUSDT", Client.KLINE_INTERVAL_1HOUR, "20 hours ago UTC")
for data in klines_TREND:
closes = data[4]
closes_TREND.append(float(closes))
np_closes_TREND = np.array(closes_TREND)
SMA_PERIOD = 3
moving_average = talib.MA(np_closes_TREND, SMA_PERIOD)
# Filter out nan values in bumpy array
moving_average = moving_average[~np.isnan(moving_average)]
test = [round(num, 2) for num in moving_average]
y = test[-6:]
if len(y) == 6:
print(y)
# Perform de polynomial fit here
编辑：如果您只需要获取最后一个列表，您可以将if语句移到for循环之外，以便它只对最后一个y列表执行多项式拟合
closes_TREND = []
MOVING_AVERAGES = []
klines_TREND = client.get_historical_klines("BTCUSDT", Client.KLINE_INTERVAL_1HOUR, "20 hours ago UTC")
for data in klines_TREND:
closes = data[4]
closes_TREND.append(float(closes))
np_closes_TREND = np.array(closes_TREND)
SMA_PERIOD = 3
moving_average = talib.MA(np_closes_TREND, SMA_PERIOD)
# Filter out nan values in bumpy array
moving_average = moving_average[~np.isnan(moving_average)]
test = [round(num, 2) for num in moving_average]
y = test[-6:]
if len(y) == 6:
print(y)
# Perform de polynomial fit here
推荐阅读
- html - 是否可以删除html5输入类型周中的“周”？
- reactjs - 如果在 reactjs 功能组件中没有找到记录，则显示无数据消息
- spring-batch - Spring Batch：使用多个实体并将它们合并
- android - Android Room 获取今天插入的所有时间
- python - Python 代码返回空白图。我该如何纠正这个错误？
- encryption - 使用 SHA-256 的 RSA OAEP 加密失败，而使用 SHA-1 则正常
- database - 如何使用 docker 部署和配置远程 clickhouse db 实例
- css - 使用滚动 CSS 在一行中显示项目
- mysql - 将计算的 AVG 集成到同一查询中
- javascript - 如何根据用户输入动态计算和绘制画布边框