如何修复'ValueError：零尺寸数组到没有身份的归约运算fmin'
[英]How to fix 'ValueError: zero-size array to reduction operation fmin which has no identity'
问题描述
I'm trying to plot some simple time Series and usually it works fine, but this special case does not get the results as expected: 
我正在尝试绘制一些简单的时间序列，通常可以正常工作，但是这种特殊情况无法获得预期的结果：
I run the code in Visual Studio and CLI where I got the same Error Message. 我在获得相同错误消息的Visual Studio和CLI中运行代码。 But when I tried to run the same code in a jupyter notebook where I got three cells (CELL1, CELL2 and CELL3 separated), the whole code works fine. 但是，当我尝试在jupyter笔记本中运行相同的代码时，我得到了三个单元格（CELL1，CELL2和CELL3分开），整个代码可以正常工作。 Only when I put CELL2 and CELL3 in one single CELL, it produced the typical error again. 仅当我将CELL2和CELL3放在一个单独的CELL中时，它才再次产生典型错误。
# CELL 1
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import datetime
from pandas import Series
import sys
input_array = np.array([[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.]])
date_list = [datetime.date(2019, 1, 2), datetime.date(2019, 1, 9), datetime.date(2019, 1, 16), datetime.date(2019, 1, 23), datetime.date(2019, 1, 30), datetime.date(2019, 2, 6), datetime.date(2019, 2, 13), datetime.date(2019, 2, 20), datetime.date(2019, 2, 27), datetime.date(2019, 3, 6), datetime.date(2019, 3, 13), datetime.date(2019, 3, 20), datetime.date(2019, 3, 27), datetime.date(2019, 4, 3), datetime.date(2019, 4, 10)]
def get_indiv_series(table, index):
out_series = []
for i in table:
out_series.append(i[index])
return out_series
def make_indiv_category_plot(times, table, index, axis):
print(get_indiv_series(table, index))
series = Series(get_indiv_series(table, index), index=times)
try:
series.plot(style='-', ax=axis)
except ValueError as err:
print(' A value Error ocurred')
print(index)
print(series)
print(get_indiv_series(table, index))
print(sys.exc_info())
raise err
line_i, = plt.plot([])
return line_i
# CELL 2
fig = plt.figure(figsize=(10, 10))
ax = plt.gca()
# CELL 3
line_0 = make_indiv_category_plot(date_list, input_array, 0, ax)
line_1 = make_indiv_category_plot(date_list, input_array, 1, ax)
line_2 = make_indiv_category_plot(date_list, input_array, 2, ax)
line_3 = make_indiv_category_plot(date_list, input_array, 3, ax)
line_4 = make_indiv_category_plot(date_list, input_array, 4, ax)
RESULTS (merging CELL2 & CELL 3): 结果（合并单元2和单元3）：
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
2019-01-02 0.0
2019-01-09 0.0
2019-01-16 0.0
2019-01-23 0.0
2019-01-30 0.0
2019-02-06 0.0
2019-02-13 0.0
2019-02-20 0.0
2019-02-27 0.0
2019-03-06 0.0
2019-03-13 0.0
2019-03-20 0.0
2019-03-27 0.0
2019-04-03 0.0
2019-04-10 0.0
dtype: float64
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
2019-01-02 0.0
2019-01-09 0.0
2019-01-16 0.0
2019-01-23 0.0
2019-01-30 0.0
2019-02-06 0.0
2019-02-13 0.0
2019-02-20 0.0
2019-02-27 0.0
2019-03-06 0.0
2019-03-13 0.0
2019-03-20 0.0
2019-03-27 0.0
2019-04-03 0.0
2019-04-10 0.0
dtype: float64
A value Error ocurred
1
2019-01-02 0.0
2019-01-09 0.0
2019-01-16 0.0
2019-01-23 0.0
2019-01-30 0.0
2019-02-06 0.0
2019-02-13 0.0
2019-02-20 0.0
2019-02-27 0.0
2019-03-06 0.0
2019-03-13 0.0
2019-03-20 0.0
2019-03-27 0.0
2019-04-03 0.0
2019-04-10 0.0
dtype: float64
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
(<class 'ValueError'>, ValueError('zero-size array to reduction operation fmin which has no identity',), <traceback object at 0x000001DB4550C208>)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-4-814d54a9ca4b> in <module>()
5 line_0 = make_indiv_category_plot(date_list, input_array, 0, ax)
6
----> 7 line_1 = make_indiv_category_plot(date_list, input_array, 1, ax)
8
9 line_2 = make_indiv_category_plot(date_list, input_array, 2, ax)
<ipython-input-3-ddbd896b3735> in make_indiv_category_plot(times, table, index, axis)
57 print(get_indiv_series(table, index))
58 print(sys.exc_info())
---> 59 raise err
60 # create a empty line with the same properties as the time series for legends
61 line_i, = plt.plot([])#, color='%s'%db_fplive.Get_color_table()[index+1], label=db_fplive.Get_label_table()[index+1])
<ipython-input-3-ddbd896b3735> in make_indiv_category_plot(times, table, index, axis)
48 # plot the series with the color and label from the category dictionaries
49 try:
---> 50 series.plot()#style='-', ax=axis, color='%s'%db_fplive.Get_color_table()[index+1], label=db_fplive.Get_label_table()[index+1])
51 except ValueError as err:
52 print(' A value Error ocurred')
C:\Program Files (x86)\Microsoft Visual Studio\Shared\Anaconda3_64\lib\site-packages\pandas\plotting\_core.py in __call__(self, kind, ax, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, label, secondary_y, **kwds)
2740 colormap=colormap, table=table, yerr=yerr,
2741 xerr=xerr, label=label, secondary_y=secondary_y,
-> 2742 **kwds)
2743 __call__.__doc__ = plot_series.__doc__
2744
C:\Program Files (x86)\Microsoft Visual Studio\Shared\Anaconda3_64\lib\site-packages\pandas\plotting\_core.py in plot_series(data, kind, ax, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, label, secondary_y, **kwds)
1996 yerr=yerr, xerr=xerr,
1997 label=label, secondary_y=secondary_y,
-> 1998 **kwds)
1999
2000
C:\Program Files (x86)\Microsoft Visual Studio\Shared\Anaconda3_64\lib\site-packages\pandas\plotting\_core.py in _plot(data, x, y, subplots, ax, kind, **kwds)
1799 plot_obj = klass(data, subplots=subplots, ax=ax, kind=kind, **kwds)
1800
-> 1801 plot_obj.generate()
1802 plot_obj.draw()
1803 return plot_obj.result
C:\Program Files (x86)\Microsoft Visual Studio\Shared\Anaconda3_64\lib\site-packages\pandas\plotting\_core.py in generate(self)
249 self._compute_plot_data()
250 self._setup_subplots()
--> 251 self._make_plot()
252 self._add_table()
253 self._make_legend()
C:\Program Files (x86)\Microsoft Visual Studio\Shared\Anaconda3_64\lib\site-packages\pandas\plotting\_core.py in _make_plot(self)
998
999 lines = _get_all_lines(ax)
-> 1000 left, right = _get_xlim(lines)
1001 ax.set_xlim(left, right)
1002
C:\Program Files (x86)\Microsoft Visual Studio\Shared\Anaconda3_64\lib\site-packages\pandas\plotting\_tools.py in _get_xlim(lines)
362 for l in lines:
363 x = l.get_xdata(orig=False)
--> 364 left = min(np.nanmin(x), left)
365 right = max(np.nanmax(x), right)
366 return left, right
C:\Program Files (x86)\Microsoft Visual Studio\Shared\Anaconda3_64\lib\site-packages\numpy\lib\nanfunctions.py in nanmin(a, axis, out, keepdims)
278 # Fast, but not safe for subclasses of ndarray, or object arrays,
279 # which do not implement isnan (gh-9009), or fmin correctly (gh-8975)
--> 280 res = np.fmin.reduce(a, axis=axis, out=out, **kwargs)
281 if np.isnan(res).any():
282 warnings.warn("All-NaN slice encountered", RuntimeWarning, stacklevel=2)
ValueError: zero-size array to reduction operation fmin which has no identity
Does anyone know how to deal with the problem or is familiar with that error message? 有谁知道如何处理该问题或熟悉该错误消息？
1 个解决方案
解决方案1
0 2019-04-12 13:05:35
Okay, meanwhile I found a solution to get the code work: 好的，与此同时，我找到了使代码正常工作的解决方案：
turn the created Series object into a DataFrame object with one column(whose internal representation should still be a Series object) 将创建的Series对象转换为具有一列的DataFrame对象（其内部表示形式仍应为Series对象）
To summarize, the following code magically works: 总而言之，以下代码神奇地起作用：
# CELL 1
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import datetime
from pandas import Series
import sys
input_array = np.array([[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.]])
date_list = [datetime.date(2019, 1, 2), datetime.date(2019, 1, 9), datetime.date(2019, 1, 16), datetime.date(2019, 1, 23), datetime.date(2019, 1, 30), datetime.date(2019, 2, 6), datetime.date(2019, 2, 13), datetime.date(2019, 2, 20), datetime.date(2019, 2, 27), datetime.date(2019, 3, 6), datetime.date(2019, 3, 13), datetime.date(2019, 3, 20), datetime.date(2019, 3, 27), datetime.date(2019, 4, 3), datetime.date(2019, 4, 10)]
def get_indiv_series(table, index):
out_series = []
for i in table:
out_series.append(i[index])
return out_series
def make_indiv_category_plot(times, table, index, axis):
print(get_indiv_series(table, index))
series = pd.DataFrame(get_indiv_series(table, index), index=times)
try:
series.plot(style='-', use_index = True)
except ValueError as err:
print(' A value Error ocurred')
print(index)
print(series)
print(get_indiv_series(table, index))
print(sys.exc_info())
raise err
line_i, = plt.plot([])
return line_i
fig = plt.figure(figsize=(10, 10))
ax = plt.gca()
line_0 = make_indiv_category_plot(date_list, input_array, 0, ax)
line_1 = make_indiv_category_plot(date_list, input_array, 1, ax)
line_2 = make_indiv_category_plot(date_list, input_array, 2, ax)
line_3 = make_indiv_category_plot(date_list, input_array, 3, ax)
line_4 = make_indiv_category_plot(date_list, input_array, 4, ax)
Got anyone an explanation for that curious behavior ?? 得到任何人对这种奇怪行为的解释？
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