Fastest approach to read thousands of images into one big numpy array

I'm trying to find the fastest approach to read a bunch of images from a directory into a numpy array. My end goal is to compute statistics such as the max, min, and nth percentile of the pixels from all these images. This is straightforward and fast when the pixels from all the images are in one big numpy array, since I can use the inbuilt array methods such as .max and .min , and the np.p

最快的方法可以将数千张图像读入一个大的numpy阵列

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在YouTube V3 API上突然获得了Oauth 2.0同意的403(Forbidden)

我有3个YouTube频道的品牌帐户。 对其中两个我已连接并成功通过身份验证,但第三个在尝试进行身份验证时给我一个403错误。 我使用python youtube上传脚本。 我已经设置了凭据和项目,启用了YouTube v3 api和一切。 我几个小时前为第二个帐户做了这个,现在第三个帐户不工作。 可能是什么问题? 选择你的账户或品牌账户继续上传: 我选择一个我管理的品牌账户(但我不拥有它,只能管理)。 错误403.这是一个错误。

undefined reference to `

I am trying to compile a Fortran 90 file with f2py, to use in a Python module. The file is composed of two subroutines. I can compile the file, using gfortran ljlib3.f90 in the command window, but I get errors when trying to compile the subroutine with f2py. I am using Python(x,y) on Win 10 (Python 2.7.10) and Mingw-w64 (all properly installed). It's difficult because this is someone els

未定义的参考`

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I am trying install some Python modules in my system using f2py, which are related to an ocean model (in Fortran 90). I am facing some problems with f2py. To be specific, the f2py is unable to link with the NetCDF library even though I have the required library and include files installed. I am using Python 2.7 with Anaconda 2 on Ubuntu16.04 on a 64-bit machine. I'm using gfortran. To t

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我尝试在我的系统中使用f2py安装一些Python模块,这些模块与海洋模型(在Fortran 90中)相关。 我正面临f2py的一些问题。 具体而言,即使我安装了所需的库和包含文件,f2py也无法与NetCDF库链接。 我在64位机器上的Ubuntu16.04上使用Python 2.7与Anaconda 2。 我正在使用gfortran。 为了测试它的工作,我写了一个小代码 - 一个包含一个小子程序的f90模块。 该子程序执行基本的数学任务,并调用一个NetCDF例程来打印安装的

Issue creating f2py shared object file when linking to libraries and modules

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链接到库和模块时,创建f2py共享对象文件

我可以通过这些命令正常编译fortran程序: ifort -O2 -I/work/GSI/include -c create_upperair.f90 ifort -o create_upperair.exe -O2 create_upperair.o -L/work/GSI/lib -lbufr 我试图采用相同的fortran程序,但将其编译为python共享对象文件,以便我可以从python脚本调用此子例程。 但是,f2py命令给我的问题。 这是我目前使用的命令: f2py -c -L/work/GSI/lib -lbufr -I/work/GSI/include --f90flags=-O2 --fcompiler=

Python ImportError using F2py

I have two F90 files that I want to use with python, so I'm using f2py to compile them (together) and result a python module, I'm doing it like this: f2py -c ControlParameters.F90 vector.F90 -m test When I do this, everything is fine, and I can use functions and subroutines from those files with python. But now, I need to use f2py with those two files, adding a couple of libraries, li

Python导入错误使用F2py

我有两个F90文件,我想用python,所以我使用f2py编译它们(一起)并生成一个python模块,我这样做: f2py -c ControlParameters.F90 vector.F90 -m test 当我这样做时,一切都很好,我可以使用Python中的函数和子例程。 但现在,我需要对这两个文件使用f2py,添加一些库,如-liomp5或-lzmumps ,我得到了像大写的python模块,但是当我尝试从python导入它时,我有以下错误: ImportError: /opt/intel/composer_xe_2013.1.117/

f2py with fortran netcdf

I'm trying to use f2py to compile some fortran code that makes use of netcdf libraries. The compilation appears to work but when I try to import the module in python I get the error message: Traceback (most recent call last): File "<stdin>", line 1, in <module> ImportError: ./cdfio_simple.so: undefined symbol: netcdf_mp_nf90_get_var_2d_fourbytereal_ There is also the following

f2py与fortran netcdf

我正在尝试使用f2py来编译一些使用netcdf库的fortran代码。 编译似乎工作,但是当我尝试在python中导入模块时,我收到错误消息: Traceback (most recent call last): File "<stdin>", line 1, in <module> ImportError: ./cdfio_simple.so: undefined symbol: netcdf_mp_nf90_get_var_2d_fourbytereal_ 编译期间还有以下输出: In: :cdfio_simple:cdfio_simple.f90:cdfio_simple get_useparameters: no module

f2py doesn't like explicit shaped array in subroutine

I am trying to compile a python module from some Fortran code using f2py . The code compiles fine with ifort, but throws up errors when using f2py. Here is the code (it is over two files): gdat.f90: MODULE GDAT PUBLIC INTEGER :: NX, NY END MODULE GDAT part.f90: SUBROUTINE PART(ARR) USE GDAT, ONLY: NX, NY INTEGER, INTENT(IN) :: ARR(NX,NY) PRINT*, ARR END SUBROUTINE PAR

f2py不喜欢子程序中的显式整形数组

我正在尝试使用f2py从一些Fortran代码编译python模块。 该代码与ifort编译良好,但在使用f2py时抛出错误。 这里是代码(它是两个文件): gdat.f90: MODULE GDAT PUBLIC INTEGER :: NX, NY END MODULE GDAT part.f90: SUBROUTINE PART(ARR) USE GDAT, ONLY: NX, NY INTEGER, INTENT(IN) :: ARR(NX,NY) PRINT*, ARR END SUBROUTINE PART 我使用f2py -c gdat.f90 part.f90 -m part编译,但是我得

Problems with f2py: undefined references to module in subroutine

I am trying to compile a Fortran f90 file with f2py, to use in Python. The file is a subroutine that calls a module from another file. The module is basically for allocation. I can compile the module, using 'gfortran my_dec.f90' in the command window, but I get errors when trying to compile the subroutine file. It's especially difficult because I've barely used Fortran and thi

f2py的问题:未定义的子程序中的模块引用

我正在尝试用f2py编译Fortran f90文件,以便在Python中使用。 该文件是从另一个文件调用模块的子例程。 该模块基本上用于分配。 我可以在命令窗口中使用'gfortran my_dec.f90'来编译模块,但在编译子例程文件时出现错误。 这特别困难,因为我几乎没有使用Fortran,而这是别人的代码。 这里是模块和子程序的一部分,因为它很长,包括它的开始和结束: module my_dec integer ndir, nfreq integer ihmax,i

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I have recently started working on Flask and Flask-SQLAlchemy. Coming from Django background I found Flask-SQLAlchmey to be quite complex. I have read that SQLAlchemy implements Data Mapper pattern while Django ORM is based on Active Record Pattern. Here is a sample code written that implements repository pattern to access the database. Here is another link of a comment by S.Lott (271k repu

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我最近开始研究Flask和Flask-SQLAlchemy。 从Django的背景来看,我发现Flask-SQLAlchmey相当复杂。 我读过SQLAlchemy实现Data Mapper模式,而Django ORM基于Active Record Pattern。 下面是一个实现代码库模式以访问数据库的示例代码。 这是S.Lott(271k声誉)评论的另一个链接,他说ORM是数据访问层,它与模型是分开的。 我的问题是这些: 你可以在上面的例子中提供一个实际的用例,或者你可以提供一个Data Mapper模