使用EZ-USB FX3优化USB 3.0高速传输

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"AN86947_Optimizing_USB_3.0_Throughput_with_EZ-USB_FX3_Chinese.pdf" 本文档详细介绍了如何利用Cypress的EZ-USB® FX3控制器来优化USB 3.0的吞吐量，确保在高速数据传输时达到最佳性能。EZ-USB FX3是一款高度集成的USB 3.0外围设备控制器，它为设计者提供了强大的灵活性，可以方便地将USB 3.0功能集成到各种系统中。USB 3.0的传输速度达到了5 Gbps，是USB 2.0的10倍，而FX3芯片能够接近这一理论上限，实现高效的数据传输。 文档首先概述了与USB 3.0性能相关的资源，包括EZ-USB FX3软件开发套件（FX3SDKv1.3.3）和GPIFI Designer工具，这有助于用户设计和优化通用接口总线（GPIF）配置，以适应不同的传输需求。 接着，文档列举了用于测试和评估性能的硬件设置，同时总结了关键性能指标，包括不同类型的传输方式，如同步传输、批量传输和中断传输。其中，同步传输适合实时性要求高的应用，批量传输适合大量非实时数据传输，而中断传输则适用于需要低延迟的少量数据传输。 文档深入分析了如何通过调整GPIF到USB的AUTODMA通道实现最优性能，并且对比了不同主机控制器和操作系统的性能差异，这对于理解系统级的瓶颈至关重要。此外，还探讨了其他可能影响吞吐量的因素，如USB设计的细节，如传输类型的选择和缓冲区大小的设定。 最后，文档提供了额外的资源链接，如完整的USBSuperSpeed代码示例，以帮助开发者进一步提升USB 3.0应用的性能。此外，还包括了文档修订历史，便于追踪更新，以及赛普拉斯全球的销售和支持信息，为用户提供全面的技术支持。 通过这份应用笔记，读者不仅可以了解到USB 3.0技术的基本原理，还能掌握如何利用EZ-USB FX3控制器来优化系统性能，从而在实际应用中实现更高的数据传输效率。

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Traceback (most recent call last): File "d:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 128, in <module> data = optimizing() File "d:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 15, in __init__ self.optimizing_main() File "d:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 124, in optimizing_main self.child2=self.mutation_cdata(fitness_data,self.cross_data) File "d:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 92, in mutation_cdata print('cross_data[波束场景No]',bs_data[8]) IndexError: index 8 is out of bounds for axis 0 with size 1

2023-07-14 上传
根据错误信息，看起来你正在尝试从一个长度为1的DataFrame中获取索引8的数据，但是该索引超出了DataFrame的范围，导致出现了IndexError异常。 请确保你的DataFrame确实包含索引为8的数据。你可以使用`df.shape`来...

import random import fitness class optimizing(): def __int__(self): self.finess_data=fitness.fitness() #print(self.finess_data) def p(self): print(self.finess_data) data=optimizing() data.p() 报错：C:\Users\z84259074\AppData\Local\Programs\Python\Python310\python310.exe D:/Users/z84259074/PycharmProjects/参数自优化/self_optimizing.py Traceback (most recent call last): File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 11, in <module> data.p() File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 8, in p print(self.finess_data) AttributeError: 'optimizing' object has no attribute 'finess_data'

2023-07-12 上传
这个错误是因为在 `__int__()` 方法中，使用了双下划线 `__` 代替了双下划线 `__init__()` 方法的名称。在 Python 中，类的构造方法应该被...这样就可以正确地初始化 `optimizing` 类的实例对象并调用 `p()` 方法了。

bs_data = w_data[w_data['波束场景No'] == cross_data['波束场景No'][0]] 报错：Traceback (most recent call last): File "C:\Users\z84259074\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\indexes\base.py", line 3652, in get_loc return self._engine.get_loc(casted_key) File "pandas\_libs\index.pyx", line 147, in pandas._libs.index.IndexEngine.get_loc File "pandas\_libs\index.pyx", line 176, in pandas._libs.index.IndexEngine.get_loc File "pandas\_libs\hashtable_class_helper.pxi", line 7080, in pandas._libs.hashtable.PyObjectHashTable.get_item File "pandas\_libs\hashtable_class_helper.pxi", line 7088, in pandas._libs.hashtable.PyObjectHashTable.get_item KeyError: '波束场景No' The above exception was the direct cause of the following exception: Traceback (most recent call last): File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 127, in <module> data = optimizing() File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 18, in __init__ self.optimizing_main() File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 120, in optimizing_main self.child2=self.mutation_cdata(fitness_data,self.cross_data) File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 86, in mutation_cdata bs_data = w_data[w_data['波束场景No'] == cross_data['波束场景No'][0]] File "C:\Users\z84259074\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\frame.py", line 3761, in __getitem__ indexer = self.columns.get_loc(key) File "C:\Users\z84259074\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\indexes\base.py", line 3654, in get_loc raise KeyError(key) from err KeyError: '波束场景No'

2023-07-14 上传
根据错误信息，看起来在使用`w_data[w_data['波束场景No'] == cross_data['波束场景No'][0]]`时出现了`KeyError: '波束场景No'`错误。这个错误通常表示在`w_data` DataFrame中不存在名为'波束场景No'的列。...

(random.randint(0, bs_data[12]-1))*3+bs_data[8] 报错：Traceback (most recent call last): File "C:\Users\z84259074\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\indexes\base.py", line 3652, in get_loc return self._engine.get_loc(casted_key) File "pandas\_libs\index.pyx", line 147, in pandas._libs.index.IndexEngine.get_loc File "pandas\_libs\index.pyx", line 176, in pandas._libs.index.IndexEngine.get_loc File "pandas\_libs\hashtable_class_helper.pxi", line 7080, in pandas._libs.hashtable.PyObjectHashTable.get_item File "pandas\_libs\hashtable_class_helper.pxi", line 7088, in pandas._libs.hashtable.PyObjectHashTable.get_item KeyError: 12 The above exception was the direct cause of the following exception: Traceback (most recent call last): File "d:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 128, in <module> data = optimizing() File "d:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 15, in __init__ self.optimizing_main() File "d:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 124, in optimizing_main self.child2=self.mutation_cdata(fitness_data,self.cross_data) File "d:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 92, in mutation_cdata print('cross_data[波束场景No]',bs_data[12]) File "C:\Users\z84259074\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\frame.py", line 3761, in __getitem__ indexer = self.columns.get_loc(key) File "C:\Users\z84259074\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\indexes\base.py", line 3654, in get_loc raise KeyError(key) from err KeyError: 12

2023-07-14 上传
根据错误信息，看起来是你试图从一个Pandas DataFrame中获取列索引为12的数据，但是该列索引不存在导致出现了KeyError异常。 请确认一下你的DataFrame中是否存在列索引为12的列。你可以使用`df.columns`来查看...

import random import fitness class optimizing: def __int__(self): self.finess_data=fitness.fitness() self.a=1 print(self.a) def p(self): print(self.a) data=optimizing() data.p() 报错如何解决：C:\Users\z84259074\AppData\Local\Programs\Python\Python310\python310.exe D:/Users/z84259074/PycharmProjects/参数自优化/self_optimizing.py Traceback (most recent call last): File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 12, in <module> data.p() File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 9, in p print(self.a) AttributeError: 'optimizing' object has no attribute 'a'

2023-07-12 上传
这个错误是因为在 `__int__()` 方法中，你使用了双下划线 `__` 代替了双下划线 `__init__()` 方法的名称。在 Python 中，类的构造方法应该被...这样就可以正确地初始化 `optimizing` 类的实例对象并调用 `p()` 方法了。

'波束场景No': bs_data['覆盖场景No'][0]报错：Traceback (most recent call last): File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 106, in <module> data = optimizing() File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 18, in __init__ self.optimizing_main() File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 100, in optimizing_main self.child1=self.mutation(fitness_data,gene_len) File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 70, in mutation '波束场景No': bs_data['覆盖场景No'][0], File "C:\Users\z84259074\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\series.py", line 1007, in __getitem__ return self._get_value(key) File "C:\Users\z84259074\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\series.py", line 1116, in _get_value loc = self.index.get_loc(label) File "C:\Users\z84259074\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\indexes\range.py", line 349, in get_loc raise KeyError(key) KeyError: '覆盖场景No' 覆盖场景No 覆盖场

2023-07-14 上传
根据错误信息，看起来在`bs_data`数据框中没有名为'覆盖场景No'的列。请确保列名的拼写和大小写与数据框中的实际列名完全匹配。 如果你想要查看`bs_data`数据框的列名，可以使用`columns`属性： ...

Traceback (most recent call last): File "C:\Users\z84259074\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\indexes\range.py", line 345, in get_loc return self._range.index(new_key) ValueError: 17 is not in range The above exception was the direct cause of the following exception: Traceback (most recent call last): File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 107, in <module> data = optimizing() File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 18, in __init__ self.optimizing_main() File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 101, in optimizing_main self.child1=self.mutation(fitness_data,gene_len) File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 66, in mutation bs_data=w_data.loc[random.randint(0, len(w_data))] File "C:\Users\z84259074\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\indexing.py", line 1103, in __getitem__ return self._getitem_axis(maybe_callable, axis=axis) File "C:\Users\z84259074\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\indexing.py", line 1343, in _getitem_axis return self._get_label(key, axis=axis) File "C:\Users\z84259074\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\indexing.py", line 1293, in _get_label return self.obj.xs(label, axis=axis) File "C:\Users\z84259074\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\generic.py", line 4095, in xs loc = index.get_loc(key) File "C:\Users\z84259074\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\indexes\range.py", line 347, in get_loc raise KeyError(key) from err KeyError: 17报错如何修改

2023-07-14 上传
根据错误信息，看起来在调用`w_data.loc[random.randint(0, len(w_data))]`时出现了`KeyError: 17`错误。这个错误通常表示索引值17在`w_data`的索引范围之外。 要解决这个问题，你可以先检查一下`w_data` DataFrame...

Traceback (most recent call last): File "D:\Users\z84259074\PycharmProjects\参数自优化\self_optimizing.py", line 11, in <module> data.p() TypeError: optimizing.p() missing 1 required positional argument: 'self'

2023-07-12 上传
data = optimizing() # 实例化对象 data.p() # 调用方法 ``` 如果`data`是一个类的静态方法或类方法，则无需实例化对象。根据方法的定义，可以直接使用类来调用方法。例如，如果`p()`是一个静态方法，可以使用以下...
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