Traceback (most recent call last): File "D:\Programming\envs\env_pytorch\Lib\site-packages\IPython\core\interactiveshell.py", line 3508, in run_code exec(code_obj, self.user_global_ns, self.user_ns) File "<ipython-input-2-f56814941387>", line 1, in <module> runfile('D:\\Programming\\PycharmProjects\\P02_PIVmix\\Segment\\Image_filter.py', wdir='D:\\Programming\\PycharmProjects\\P02_PIVmix\\Segment') File "D:\Program Files\JetBrains\PyCharm Community Edition 2022.3.3\plugins\python-ce\helpers\pydev\_pydev_bundle\pydev_umd.py", line 198, in runfile pydev_imports.execfile(filename, global_vars, local_vars) # execute the script ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\Program Files\JetBrains\PyCharm Community Edition 2022.3.3\plugins\python-ce\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile exec(compile(contents+"\n", file, 'exec'), glob, loc) File "D:\Programming\PycharmProjects\P02_PIVmix\Segment\Image_filter.py", line 70, in <module> gamma_params, _ = curve_fit(gamma_func, new_bin_centers, new_hist, p0=p2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\Programming\envs\env_pytorch\Lib\site-packages\scipy\optimize\_minpack_py.py", line 859, in curve_fit res = leastsq(func, p0, Dfun=jac, full_output=1, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\Programming\envs\env_pytorch\Lib\site-packages\scipy\optimize\_minpack_py.py", line 413, in leastsq shape, dtype = _check_func('leastsq', 'func', func, x0, args, n) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\Programming\envs\env_pytorch\Lib\site-packages\scipy\optimize\_minpack_py.py", line 26, in _check_func res = atleast_1d(thefunc(*((x0[:numinputs],) + args))) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\Programming\envs\env_pytorch\Lib\site-packages\scipy\optimize\_minpack_py.py", line 501, in func_wrapped return func(xdata, *params) - ydata ^^^^^^^^^^^^^^^^^^^^ File "D:\Programming\PycharmProjects\P02_PIVmix\Segment\Image_filter.py", line 63, in gamma_func assert isinstance(b, int) and b > 0, "b must be a positive integer" ^^^^^ AssertionError: b must be a positive integer
时间: 2023-07-21 20:46:05 浏览: 74
根据错误信息,可以看到程序出现了一个 AssertionError 异常,提示 "b must be a positive integer"。这个错误是由 gamma_func 函数中的 assert 语句触发的,说明输入参数 b 不满足要求。
根据代码,我们知道 gamma_func 函数要求输入参数 b 是正整数。因此,建议检查调用 gamma_func 函数时所传入的参数是否满足要求。如果不满足要求,可以进行相应的调整,确保输入参数 b 是正整数。
另外,如果需要捕获 AssertionError 异常并进行相应的处理,可以使用 try-except 语句来实现。例如:
```python
try:
gamma_params, _ = curve_fit(gamma_func, new_bin_centers, new_hist, p0=p2)
except AssertionError as e:
print("Error: ", e)
```
这里使用 try-except 语句捕获 AssertionError 异常,并输出相应的错误信息。
相关问题
traceback (most recent call last): file "d:\anaconda\lib\site-packages\conda
引用:已解决"Traceback (most recent call last): File “E:\Anaconda3\lib\site-packages\pip_vendor\urllib3\response.py”, line 360, in _error_catcher yield" 这是一个错误的追踪信息,通常出现在代码中发生了异常或错误时。它会显示出错的具体位置和引发异常的原因。
引用:网上给出了一些解决方法,比如关闭后台jupyter notebook,并根据提示使用命令"python -m pip install --upgrade pip"来升级pip工具。这个操作可以帮助更新pip并解决一些常见的问题。
引用:另外,还可以考虑更换镜像源来解决问题。可以使用命令"pip install tensorflow -i https://pypi.douban.com/simple"来安装TensorFlow,并指定使用豆瓣镜像源进行安装,这样可能可以避免一些下载或安装的问题。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* *3* [已解决Traceback (most recent call last): File “E:\Anaconda3\lib\site-packages\pip_vendor\urllib3\...](https://blog.csdn.net/weixin_50843918/article/details/129991452)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_1"}}] [.reference_item style="max-width: 50%"]
- *2* [python安装报错ERROR: Exception: Traceback (most recent call last): File “d:\anaconda3.5.2\lib\site-...](https://blog.csdn.net/qq_41387939/article/details/109828665)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_1"}}] [.reference_item style="max-width: 50%"]
[ .reference_list ]
Traceback (most recent call last): File D:\Programming\envs\env_pytorch\Lib\site-packages\spyder_kernels\py3compat.py:356 in compat_exec exec(code, globals, locals) File d:\programming\pycharmprojects\p02_pivmix\mix\main.py:287 plt.pcolormesh(pX, pY, M ,vmin=0, vmax=math.ceil(max(M)), cmap='inferno') ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
这个报错是因为 `vmax` 参数需要传入一个标量,但是你传入了一个数组 `math.ceil(max(M))`。
你可以将 `math.ceil(max(M))` 直接赋值给一个变量,然后将这个变量传给 `vmax` 参数。例如:
```python
import numpy as np
import math
import matplotlib.pyplot as plt
M = np.random.rand(10, 10) * 10
max_M = math.ceil(np.max(M))
pX, pY = np.meshgrid(np.arange(0, 10), np.arange(0, 10))
plt.pcolormesh(pX, pY, M ,vmin=0, vmax=max_M, cmap='inferno')
plt.colorbar()
plt.title('Displacement (pixels)')
plt.axis('scaled')
plt.savefig(result_path +'/2-D Velocity Field Displacement.png', dpi=300, bbox_inches='tight')
plt.show()
```
在这个例子中,我们首先使用NumPy库生成了一个10x10的随机二维数组M。然后,我们使用`np.max()`函数找到了数组M中的最大值,并使用`math.ceil()`函数对其进行向上取整,并将结果赋值给`max_M`变量。在调用`plt.pcolormesh()`函数时,我们将`max_M`作为`vmax`参数的值。最后,我们添加了一些其他的绘图设置,并将图像保存到指定的路径中。