Activate mirror tests on pandoc format

#208

tests/notebooks/mirror/ipynb_to_pandoc/Notebook with function and cell metadata 164.md

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+::: {.cell .code execution_count="1"}
+``` {.python}
+1 + 1
+```
+
+::: {.output .execute_result execution_count="1"}
+    2
+:::
+:::
+
+::: {.cell .markdown}
+A markdown cell And below, the cell for function f has non trivial cell
+metadata. And the next cell as well.
+:::
+
+::: {.cell .code execution_count="2" attributes="{"n":"10","id":"","classes":[]}"}
+``` {.python}
+def f(x):
+    return x
+```
+:::
+
+::: {.cell .code execution_count="3" attributes="{"n":"10","id":"","classes":[]}"}
+``` {.python}
+f(5)
+```
+
+::: {.output .execute_result execution_count="3"}
+    5
+:::
+:::
+
+::: {.cell .markdown}
+More text
+:::
+
+::: {.cell .code execution_count="4"}
+``` {.python}
+2 + 2
+```
+
+::: {.output .execute_result execution_count="4"}
+    4
+:::
+:::

tests/notebooks/mirror/ipynb_to_pandoc/Notebook with html and latex cells.md

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+::: {.cell .code execution_count="1"}
+``` {.python}
+%%html
+<p><a href="https://github.com/mwouts/jupytext", style="color: rgb(0,0,255)">Jupytext</a> on GitHub</p>
+```
+
+::: {.output .display_data}
+<p><a href="https://github.com/mwouts/jupytext", style="color: rgb(0,0,255)">Jupytext</a> on GitHub</p>
+:::
+:::
+
+::: {.cell .code execution_count="2"}
+``` {.python}
+%%latex
+$\frac{\pi}{2}$
+```
+
+::: {.output .display_data}
+$\frac{\pi}{2}$
+:::
+:::
+
+::: {.cell .code execution_count="3"}
+``` {.python}
+%load_ext rpy2.ipython
+```
+:::
+
+::: {.cell .code execution_count="4"}
+``` {.python}
+%%R
+library(ggplot2)
+ggplot(data=data.frame(x=c('A', 'B'), y=c(5, 2)), aes(x,weight=y)) + geom_bar()
+```
+
+::: {.output .display_data}
+![](7f97cecde4f72e650de2f3937ac4999467e76306.png)
+:::
+:::
+
+::: {.cell .code execution_count="5"}
+``` {.python}
+%matplotlib inline
+import pandas as pd
+pd.Series({'A':5, 'B':2}).plot(figsize=(3,2), kind='bar')
+```
+
+::: {.output .execute_result execution_count="5"}
+    <matplotlib.axes._subplots.AxesSubplot at 0x2da0c41a9e8>
+:::
+
+::: {.output .display_data}
+![](9344ac2b35133877848c9a89b2fbbcc3dcce81e0.png)
+:::
+:::

tests/notebooks/mirror/ipynb_to_pandoc/Notebook with many hash signs.md

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+::: {.cell .markdown}
+################################################################## 
+
+This is a notebook that contains many hash signs. Hopefully its python
+representation is not recognized as a Sphinx Gallery script\...
+
+################################################################## 
+:::
+
+::: {.cell .code execution_count="1"}
+``` {.python}
+some = 1
+code = 2
+some+code
+
+##################################################################
+# A comment
+##################################################################
+# Another comment
+```
+
+::: {.output .execute_result execution_count="1"}
+    3
+:::
+:::
+
+::: {.cell .markdown}
+##################################################################  {#section}
+
+This is a notebook that contains many hash signs. Hopefully its python
+representation is not recognized as a Sphinx Gallery script\...
+
+##################################################################  {#section-1}
+:::

tests/notebooks/mirror/ipynb_to_pandoc/Notebook with metadata and long cells.md

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+::: {.cell .markdown}
+Part one - various cells
+========================
+:::
+
+::: {.cell .markdown}
+Here we have a markdown cell
+
+with two blank lines
+:::
+
+::: {.cell .markdown}
+Now we have a markdown cell with a code block inside it
+
+``` {.python}
+1 + 1
+```
+
+After that cell we\'ll have a code cell
+:::
+
+::: {.cell .code execution_count="1"}
+``` {.python}
+2 + 2
+
+
+3 + 3
+```
+
+::: {.output .execute_result execution_count="1"}
+    6
+:::
+:::
+
+::: {.cell .markdown}
+Followed by a raw cell
+:::
+
+::: {.cell .raw}
+```{=}
+This is 
+the content
+of the raw cell
+```
+:::
+
+::: {.cell .markdown}
+Part two - cell metadata
+========================
+:::
+
+::: {.cell .markdown key="value"}
+This is a markdown cell with cell metadata `{"key": "value"}`
+:::
+
+::: {.cell .code execution_count="2" .class="null" tags="["parameters"]"}
+``` {.python}
+"""This is a code cell with metadata `{"tags":["parameters"], ".class":null}`"""
+```
+
+::: {.output .execute_result execution_count="2"}
+    'This is a code cell with metadata `{"tags":["parameters"], ".class":null}`'
+:::
+:::
+
+::: {.cell .raw key="value"}
+```{=}
+This is a raw cell with cell metadata `{"key": "value"}`
+```
+:::

tests/notebooks/mirror/ipynb_to_pandoc/Notebook_with_R_magic.md

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+::: {.cell .markdown}
+A notebook with R cells
+=======================
+
+This notebook shows the use of R cells to generate plots
+:::
+
+::: {.cell .code execution_count="1"}
+``` {.python}
+%load_ext rpy2.ipython
+```
+:::
+
+::: {.cell .code execution_count="2"}
+``` {.python}
+%%R
+suppressMessages(require(tidyverse))
+```
+:::
+
+::: {.cell .code execution_count="3"}
+``` {.python}
+%%R
+ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point()
+```
+
+::: {.output .display_data}
+![](3fc4493185b3637a4127483394ece754faff16c7.png)
+:::
+:::
+
+::: {.cell .markdown}
+The default plot dimensions are not good for us, so we use the -w and -h
+parameters in %%R magic to set the plot size
+:::
+
+::: {.cell .code execution_count="4"}
+``` {.python}
+%%R -w 400 -h 240
+ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point()
+```
+
+::: {.output .display_data}
+![](92a00f6aa6af61f269e4b4a9db7fe31d5f8b1dbb.png)
+:::
+:::

tests/notebooks/mirror/ipynb_to_pandoc/Notebook_with_more_R_magic_111.md

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+::: {.cell .code execution_count="1"}
+``` {.python}
+%load_ext rpy2.ipython
+import pandas as pd
+
+df = pd.DataFrame(
+    {
+        "Letter": ["a", "a", "a", "b", "b", "b", "c", "c", "c"],
+        "X": [4, 3, 5, 2, 1, 7, 7, 5, 9],
+        "Y": [0, 4, 3, 6, 7, 10, 11, 9, 13],
+        "Z": [1, 2, 3, 1, 2, 3, 1, 2, 3],
+    }
+)
+```
+:::
+
+::: {.cell .code execution_count="2"}
+``` {.python}
+%%R -i df
+library("ggplot2")
+ggplot(data = df) + geom_point(aes(x = X, y = Y, color = Letter, size = Z))
+```
+
+::: {.output .stream .stderr}
+    C:\Users\Marco\AppData\Local\conda\conda\envs\python3\lib\site-packages\rpy2-2.9.4-py3.6-win-amd64.egg\rpy2\robjects\pandas2ri.py:191: FutureWarning: from_items is deprecated. Please use DataFrame.from_dict(dict(items), ...) instead. DataFrame.from_dict(OrderedDict(items)) may be used to preserve the key order.
+      res = PandasDataFrame.from_items(items)
+:::
+
+::: {.output .display_data}
+![](7d03ea06cc5a2be89de49cf90faff680e9b93dfa.png)
+:::
+:::

tests/notebooks/mirror/ipynb_to_pandoc/convert_to_py_then_test_with_update83.md

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+::: {.cell .code execution_count="1" scrolled="false"}
+``` {.python}
+%%time
+
+print('asdf')
+```
+
+::: {.output .stream .stdout}
+    asdf
+    CPU times: user 132 µs, sys: 57 µs, total: 189 µs
+    Wall time: 188 µs
+:::
+:::
+
+::: {.cell .markdown}
+Thanks for jupytext!
+:::
+
+::: {.cell .code collapsed="true"}
+``` {.python}
+```
+:::

tests/notebooks/mirror/ipynb_to_pandoc/frozen_cell.md

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+::: {.cell .code execution_count="1" ExecuteTime="{"start_time":"2018-10-17T10:31:56.157308Z","end_time":"2018-10-17T10:31:56.160823Z"}"}
+``` {.python}
+# This is an unfrozen cell. Works as usual.
+print("I'm a regular cell so I run and print!")
+```
+
+::: {.output .stream .stdout}
+    I'm a regular cell so I run and print!
+:::
+:::
+
+::: {.cell .code deletable="false" editable="false" run_control="{"frozen":true}"}
+``` {.python}
+# This is an frozen cell
+print("I'm frozen so Im not executed :(")
+```
+:::

tests/notebooks/mirror/ipynb_to_pandoc/ir_notebook.md

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+::: {.cell .markdown}
+This is a jupyter notebook that uses the IR kernel.
+:::
+
+::: {.cell .code execution_count="8"}
+``` {.R}
+sum(1:10)
+```
+
+::: {.output .display_data}
+55
+:::
+:::
+
+::: {.cell .code execution_count="9"}
+``` {.R}
+plot(cars)
+```
+
+::: {.output .display_data}
+![](6816e48e6ab4ff95b3497067ec010f529f3ae4c5.png)
+:::
+:::
+
+::: {.cell .code}
+``` {.R}
+```
+:::