在IPython笔记本中显示分配结果? [英] Showing assignment results in IPython notebook?

问题描述

我正在从ipython笔记本中的传热问题中写出一系列方程式/赋值(我是新手)，像这样:

I am writing a chain of equations/assignments from a heat transfer problem in ipython notebook (I am new to that one), like this:

# nominal diameter
d=3.55 # m
# ambient temperature
T0=15  # C
# surface temperature
Tw=300 # C
# average film temperature
Tm=(T0+Tw)/2+273.15 # K!
# expansion coefficient, $$\beta=1/T$$ for ideal gas
beta=1./Tm
# temperature difference
dT=Tw-T0 # C or K

是否有一种方法可以回显每个分配，以便显示那些(主要是计算出的)值?我知道%whos的魔力，但是可以按字母顺序显示变量.

Is there a way to echo each assignment, so that those (mostly computed) values are shown? I am aware of the %whos magic, but that shows variables alphabetically.

理想情况下，我想得到这样的东西:

Ideally, I would like to get something like this:

# nominal diameter
d=3.55 # m
3.55
# ambient temperature
T0=15  # C
15
# surface temperature
Tw=300 # C
300
# average film temperature
Tm=(T0+Tw)/2+273.15 # K!
430.15
# expansion coefficient, $$\beta=1/T$$ for ideal gas
beta=1./Tm
0.00232477042892
# temperature difference
dT=Tw-T0 # C or K
285

也许带有输入/输出提示(我不介意)并且语法高亮.

perhaps with In/Out promps (I don't mind) and syntax-highlighted.

使用IPython以这种方式记录计算的正确方法是什么?

What is the proper way to document the computation this way with IPython?

推荐答案

此功能是不是 IPython核心功能的一部分.相反，它已合并到扩展 displaytools 中.回购报价:

This feature is not part of the core functionality of IPython. It has instead been incorporated into the extension displaytools. Quote from the repo:

使用%load_ext displaytools或%reload_ext displaytools加载此扩展名.后者对于调试很有用.

Load this extension with %load_ext displaytools or %reload_ext displaytools. The latter is useful for debugging.

示例调用:

my_random_variable = np.random.rand() ##

由于特殊注释##，扩展名插入行 display(my_random_variable)传递给源代码，然后再传递给 解释器，即在执行之前.

Due to the special comment ## the extension inserts the line display(my_random_variable) to the source code, before it is passed to the interpreter, i.e. before its execution.

这样，将生成其他输出，从而使笔记本成为 更容易理解(因为读者知道 my_random_variable).节省打字工作和代码 重复添加display(my_random_variable).

That way, additional output is generated, which makes the notebook be more comprehensible (because the reader knows the content of my_random_variable). It saves the typing effort and the code duplication of manually adding display(my_random_variable).

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