回答此问题可获得 20 贡献值,回答如果被采纳可获得 50 分。
<p>我想从NumPy数组中形成大约60行11列的矩阵。我研究了几种方法,但没能奏效。我尝试了以下代码并得到了这个错误</p>
<pre><code>stats_features_full = np.empty((0, 11))
for ls in range(60):
current_list = ls
print('Entering list {0} for feature extraction'.format(current_list))
stats_features = get_selected_statistics_features(list_values=list[ls])
stats_features_np_shape = np.array(stats_features).shape
print('Statistical Features Extracted from list: ', stats_features)
print('Statistical Features Shape Extracted from list: ', stats_features_np_shape)
stats_features_full = np.concatenate([stats_features_full, np.array(stats_features)], axis=0)
# stats_features_full = np.append(arr=stats_features_full, values=np.array(stats_features), axis=0)
stats_features_full_np_shape = np.array(stats_features_full).shape
print('Statistical Features Extracted from all lists: ', stats_features_full)
print('Statistical Features Shape Extracted from all lists: ', stats_features_full_np_shape)
</code></pre>
<p>错误消息:</p>
<p>(一)</p>
<pre><code>stats_features_full = np.concatenate([stats_features_full, np.array(stats_features)], axis=0)
File "<__array_function__ internals>", line 6, in concatenate
ValueError: all the input arrays must have same number of dimensions, but the array at index 0 has 2 dimension(s) and the array at index 1 has 1 dimension(s)
</code></pre>
<p>(二)</p>
<pre><code>print('Entering list {0} for feature extraction'.format(current_list))
File "<__array_function__ internals>", line 6, in append
return concatenate((arr, values), axis=axis)
File "<__array_function__ internals>", line 6, in concatenate
ValueError: all the input arrays must have same number of dimensions, but the array at index 0 has 2 dimension(s) and the array at index 1 has 1 dimension(s)
</code></pre>
<p>有没有办法创建一个60x11阵列</p>
<p><strong>编辑1:</strong></p>
<p>多亏了@Krish,它似乎工作得很好。我还有一个问题,我想将<code>stats_features_full</code>变量转换成一个pandas数据帧,以便将结果保存为文本文件。我如何处理这个问题?见下面我的方法:</p>
<pre><code> ########################################################################################################################
########################################################################################################################
############################################### Feature Datasets #######################################################
########################################################################################################################
########################################################################################################################
Stats_DataFrame_Feature = stats_features_full
Stats_DataFrame_Feature_Data_list = list(Stats_DataFrame_Feature)
# print('Statistical DataFrame Featureset list: ', Stats_DataFrame_Feature_Data_list)
Stats_DataFrame_Feature_Data_list_shape = np.array(Stats_DataFrame_Feature_Data_list).shape
Stats_DataFrame_Feature_Data_list_shape_1 = np.array(Stats_DataFrame_Feature_Data_list).shape
print('Statistical DataFrame Featureset list shape: ', Stats_DataFrame_Feature_Data_list_shape)
print('Statistical DataFrame Featureset list shape: ', Stats_DataFrame_Feature_Data_list_shape_1[0])
for Stat_row in range(60):
StatsData.append(Stats_DataFrame_Feature[0:Stats_DataFrame_Feature_Data_list_shape[0]])
StatsData_np = np.array(StatsData)
with open('filepath\dataset.txt', 'w') as out_file:
for i in range(60):
print('Opened file number: {0}'.format(i))
out_string = ""
out_string += pd.DataFrame(data=StatsData_np).to_string()
out_file.write(out_string)
break
# break
# break
Stats_DataFrame_Feature_Matrix = StatsData
print('Final Saved Statistical Feature Dataset file: ', Stats_DataFrame_Feature_Matrix)
print('Shape Final Saved Statistical Feature Dataset file: ', np.array(Stats_DataFrame_Feature_Matrix).shape)
</code></pre>
<p>我的错误消息:</p>
<pre><code>out_string += pd.DataFrame(data=StatsData_np).to_string()
mgr = init_ndarray(data, index, columns, dtype=dtype, copy=copy)
values = prep_ndarray(values, copy=copy)
raise ValueError("Must pass 2-d input")
ValueError: Must pass 2-d input
</code></pre>
<p><strong>编辑2:</strong></p>
<p>我改变了以下几行,成功地让它工作了</p>
<pre><code>StatsData.append(Stats_DataFrame_Feature[0:Stats_DataFrame_Feature_Data_list_shape[1]])
StatsData_np = np.array(StatsData[Stat_row])
</code></pre>
<p>但是,我将保存的文件设置为以下维度(60,11,11)。为什么呢</p>
<p><strong>编辑3:</strong></p>
<p>假设我创建了6个字典键,每个键有10个列表。我想实现同样的东西,但我不断得到索引错误</p>
<pre><code>for key in range(0, 6, 1):
list_key = np.array(dict_list[key])
print('Key value: {0}'.format(key))
arr_list = []
for list_num in range(0, 10, 1):
list_val_num = np.array(list(list_key[:, list_num][0]))
# stats_features = get_statistics_features_final(list_values=list_val_num)
stats_features = get_selected_statistics_features(list_values=list_val_num)
stats_features_np_shape = np.array(stats_features).shape
print('Statistical Features Extracted from list: ', stats_features)
print('Statistical Features Shape Extracted from list: ', stats_features_np_shape)
arr_list += [stats_features]
f_arr_list += arr_list
stats_features_full = np.vstack(f_arr_list)
stats_features_full_np_shape = np.array(stats_features_full).shape
print('Statistical Features Shape Extracted from all lists: ', stats_features_full_np_shape)
</code></pre>
<p>错误消息:</p>
<pre><code>IndexError: index 1 is out of bounds for axis 1 with size 1
</code></pre>