<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[cf_jack的专栏]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/cf_jack</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; cf_jack]]></copyright><item><title><![CDATA[mac m1笔记本 访达卡住了]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/135283813</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/135283813</guid><author>cf_jack</author><pubDate>Fri, 29 Dec 2023 09:48:44 +0800</pubDate><description><![CDATA[有时候打开finder出现风火轮，卡住了。结果好使了，如果有类似的问题，不妨试一试。]]></description><category></category></item><item><title><![CDATA[魔改resnet18进而使用灰度图进行图像分类]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/129167837</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/129167837</guid><author>cf_jack</author><pubDate>Wed, 22 Feb 2023 18:15:51 +0800</pubDate><description><![CDATA[修改resnet18结构，使用单通道图]]></description><category></category></item><item><title><![CDATA[groupby cannot reindex from a duplicate axis]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/127066995</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/127066995</guid><author>cf_jack</author><pubDate>Tue, 27 Sep 2022 10:36:22 +0800</pubDate><description><![CDATA[groupby cannot reindex from a duplicate axis]]></description><category></category></item><item><title><![CDATA[pandas resample 聚合，不让时间连续]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/127062155</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/127062155</guid><author>cf_jack</author><pubDate>Mon, 26 Sep 2022 22:14:06 +0800</pubDate><description><![CDATA[pandas resmaple 使用笔记，resample不让时间连续]]></description><category></category></item><item><title><![CDATA[url字符转二进制]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/126937028</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/126937028</guid><author>cf_jack</author><pubDate>Mon, 19 Sep 2022 16:44:20 +0800</pubDate><description><![CDATA[url windows1252编码转二进制]]></description><category></category></item><item><title><![CDATA[seaborn jointgrid 修改x轴方向]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/126895009</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/126895009</guid><author>cf_jack</author><pubDate>Fri, 16 Sep 2022 17:41:51 +0800</pubDate><description><![CDATA[seaborn jointgrid 修改x轴方向。]]></description><category></category></item><item><title><![CDATA[python进行url decode出现乱码、问号]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/126626509</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/126626509</guid><author>cf_jack</author><pubDate>Wed, 31 Aug 2022 16:28:49 +0800</pubDate><description><![CDATA[python进行url decode出现乱码、问号乱码]]></description><category></category></item><item><title><![CDATA[random shuffle注意]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/125555344</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/125555344</guid><author>cf_jack</author><pubDate>Fri, 01 Jul 2022 11:34:43 +0800</pubDate><description><![CDATA[对数据处理，使用random shuffle的坑]]></description><category></category></item><item><title><![CDATA[mac 中word去掉超链接]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/125527189</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/125527189</guid><author>cf_jack</author><pubDate>Wed, 29 Jun 2022 18:13:04 +0800</pubDate><description><![CDATA[word如何去掉超链接]]></description><category></category></item><item><title><![CDATA[import torchvision jupyter或者jupyter-lab崩溃（crash)]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/124669168</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/124669168</guid><author>cf_jack</author><pubDate>Mon, 09 May 2022 16:26:23 +0800</pubDate><description><![CDATA[问题描述：当我在jupyter-lab中import torchvision的时候，jupyter kernel died，网上查了半天资料发现torch和torchvision安装有问题，我想很多人也可能会碰到这种问题，因此，写下这篇内容。

原因：可能是需要安装cpu版本的包

解决办法：

第一步：中国大陆的朋友之下下面代码会加快安装速度。


conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud]]></description><category></category></item><item><title><![CDATA[多个字典合并从一个json文件]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/124308628</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/124308628</guid><author>cf_jack</author><pubDate>Wed, 20 Apr 2022 21:57:57 +0800</pubDate><description><![CDATA[废话不多说上代码：


def Json(time,inde):
	dict_list = []  #设置一个储存列表

	for i in range(len(inde)): #为一次性写入的多个字典设置循环
		dictObj={
			'ID':str(i),
			'A':str(start[i]),
			'B':str(peak[i]),
			}
		dict_list.append(dictObj)

	filename = 'list.json'
	with open('list.json]]></description><category></category></item><item><title><![CDATA[pytorch生成带滑动的训练集测试集（batch)]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/124175312</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/124175312</guid><author>cf_jack</author><pubDate>Thu, 14 Apr 2022 17:16:46 +0800</pubDate><description><![CDATA[话不多说，先上代码

Example1


from torch.utils import data
import torch

batch_size = 3
t1 = np.arange(0,20)
t2 = np.arange(0,20)+100

生成序列0~19和100~190，分别模拟x_train和y_train


tensor1 = torch.from_numpy(t1)
tensor2 = torch.from_numpy(t2)

上一步很关键，否则报错


data_set = da]]></description><category></category></item><item><title><![CDATA[PyTorch backward原理]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/124045150</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/124045150</guid><author>cf_jack</author><pubDate>Fri, 08 Apr 2022 18:22:43 +0800</pubDate><description><![CDATA[第一部分


x = torch.tensor([2., 1.], requires_grad=True).view(1,2)

print(x)
y = torch.tensor([[1., 2.], [3., 4.]], requires_grad=True)
print(y.shape)
z = torch.mm(x, y)
print(f"z:{z}")

print('*****************')
grad_tensor  = torch.Tensor([[1,0]])
print(z.]]></description><category></category></item><item><title><![CDATA[pandas给符合特定条件的列赋值]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/123586835</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/123586835</guid><author>cf_jack</author><pubDate>Fri, 18 Mar 2022 23:18:09 +0800</pubDate><description><![CDATA[pandas可以给符合特定条件的列赋值，如果这个列不存在也可以创建列名并赋值。

需要注意的是：如果是赋值的内容是个列表，该列表的长度与过滤后的行数要相等。


##获得需要赋值的列表，使用array，可以是series conver to array，这样可以使用np.title，扩展array，扩展方式为[1,2,1,2]
    in_week_mean = callin.loc[:,callin.columns.isin(day_list)].mean(axis=1).array
    dsp(i]]></description><category></category></item><item><title><![CDATA[matplotlib在横坐标某范围画出阴影]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/123536790</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/123536790</guid><author>cf_jack</author><pubDate>Wed, 16 Mar 2022 21:31:03 +0800</pubDate><description><![CDATA[参考效果如下图：





上图实现代码如下：


import pandas as pd
import matplotlib.transforms as mtransforms
import matplotlib.pyplot as plt

url  = 'https://fred.stlouisfed.org/graph/fredgraph.csv?id=VIXCLS'

vix = pd.read_csv(url, index_col=0, parse_dates=True, na_values=.]]></description><category></category></item><item><title><![CDATA[pandas 合并日期和时间列]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/123382565</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/123382565</guid><author>cf_jack</author><pubDate>Fri, 11 Mar 2022 00:03:02 +0800</pubDate><description><![CDATA[原始数据的样子如下：



需要达到的效果如下图：

方法一：这个方法比较简单，代码为：


data['datetime'] = data['Date'] + ' ' + data['Time']

参考连链接：Pandas：将日期和时间合并到一个datetime列中 - 问答 - Python中文网

使用python pandas合并日期和时间列-Python 实用宝典


...]]></description><category></category></item><item><title><![CDATA[seaborn修改画图大小]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/122608655</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/122608655</guid><author>cf_jack</author><pubDate>Wed, 09 Mar 2022 17:19:32 +0800</pubDate><description><![CDATA[这个是自己作图中的笔记


labelsize = 25
lengend_size = 10
linewidth=1
ms =4
figuresize = (19,15)
font1 = {'family': 'Times New Roman',
         'weight': 'normal',
         'size': labelsize+4,
         }
plt.figure(figsize=figuresize)
# plt.tick_params(fontpropertie]]></description><category></category></item><item><title><![CDATA[macos安装joy工具]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/123045442</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/123045442</guid><author>cf_jack</author><pubDate>Mon, 21 Feb 2022 13:48:02 +0800</pubDate><description><![CDATA[joy工具链接：GitHub - cisco/joy: A package for capturing and analyzing network flow data and intraflow data, for network research, forensics, and security monitoring.


安装过程报错：ld: symbol(s) not found for architecture x86_64


然后解决：

通过查issue，大概率是openssl的问题，系统看到]]></description><category></category></item><item><title><![CDATA[matplotlib画图保存png图片黑边]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/122608821</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/122608821</guid><author>cf_jack</author><pubDate>Thu, 20 Jan 2022 19:52:49 +0800</pubDate><description><![CDATA[保存图片代码如下：

plt.savefig('fig/kde.png',dpi=300)
效果如下：



那么如何解决呢，参考链接：关于python：Matplotlib.savefig忽略轴并在图像周围绘制黑色边框 | 码农家园

只需要plt.savefig('fig/kde.png',dpi=300,facecolor='w')，加入facecolor='w'即可了
...]]></description><category></category></item><item><title><![CDATA[omnet++ 5.7 macos安装]]></title><link>https://blog.youkuaiyun.com/cf_jack/article/details/121444302</link><guid>https://blog.youkuaiyun.com/cf_jack/article/details/121444302</guid><author>cf_jack</author><pubDate>Sat, 20 Nov 2021 19:47:58 +0800</pubDate><description><![CDATA[官方安装教程：https://doc.omnetpp.org/omnetpp/InstallGuide.pdf









不过缺少下面非常重要的第二部环境的配置

环境安装：

1，source setenv之后，执行./configure，缺什么安装什么

2，.bash_rc或者.zshrc下编辑设置如下：


##omnet++
PATH=$HOME/omnetpp-5.7.2/tools/macosx/bin:$PATH
QT_PLUGIN_PATH=$HOME/omnetpp-5.7...]]></description><category></category></item></channel></rss>