Mercurial > octave
changeset 30169:cefa5d2d30bc
New class for filling and running Jupyter Notebooks.
* NEWS: Add to list of new functions announce feature.
* scripts/miscellaneous/JupyterNotebook.m: New classdef class.
* scripts/miscellaneous/module.mk: Add JupyterNotebook to build system.
* test/jupyter-notebook/JupyterNotebook.tst,
test/jupyter-notebook/octave_kernel.ipynb,
test/jupyter-notebook/plot_magic_and_errors.ipynb: New test files.
* test/jupyter-notebook/module.mk: Add new test files to build system.
* test/module.mk: Add "jupyter-notebook" directory to build system.
This is the result of GSoC 2021 by Abdallah Elshamy.
Patch pushed by Kai T. Ohlhus.
| author | Abdallah Elshamy <abdallah.k.elshamy@gmail.com> |
|---|---|
| date | Tue, 14 Sep 2021 17:54:04 +0900 |
| parents | 8e63cdd88ba6 |
| children | 72adc88bc674 |
| files | NEWS scripts/miscellaneous/JupyterNotebook.m scripts/miscellaneous/module.mk test/jupyter-notebook/JupyterNotebook.tst test/jupyter-notebook/module.mk test/jupyter-notebook/octave_kernel.ipynb test/jupyter-notebook/plot_magic_and_errors.ipynb test/module.mk |
| diffstat | 8 files changed, 2180 insertions(+), 0 deletions(-) [+] |
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line diff
--- a/NEWS Mon Sep 13 21:10:02 2021 -0700 +++ b/NEWS Tue Sep 14 17:54:04 2021 +0900 @@ -90,6 +90,12 @@ - As part of GSoC 2020, Abdallah K. Elshamy implemented the `jsondecode` and `jsonencode` functions to read and write JSON data. +- As part of GSoC 2021, Abdallah K. Elshamy implemented the +`JupyterNotebook` classdef class. This class supports running and +filling Jupyter Notebooks using the Octave language kernel from Octave +itself. Making the evaluation of long-running Jupyter Notebooks on a +computing server without permanent browser connection possible. + - By default, the history file is now located at $DATA/octave/history, where $DATA is a platform dependent location for (roaming) user data files (e.g., ${XDG_DATA_HOME} or, if that is not set, ~/.local/share on @@ -239,6 +245,7 @@ * `fill3` * `jsondecode` * `jsonencode` +* `JupyterNotebook` * `listfonts` * `matlab.net.base64decode` * `matlab.net.base64encode`
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/scripts/miscellaneous/JupyterNotebook.m Tue Sep 14 17:54:04 2021 +0900 @@ -0,0 +1,668 @@ +## Copyright (C) 2021 The Octave Project Developers +## +## This program is free software: you can redistribute it and/or modify it +## under the terms of the GNU General Public License as published by +## the Free Software Foundation, either version 3 of the License, or +## (at your option) any later version. +## +## This program is distributed in the hope that it will be useful, but +## WITHOUT ANY WARRANTY; without even the implied warranty of +## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +## GNU General Public License for more details. +## +## You should have received a copy of the GNU General Public License +## along with this program. If not, see +## <https://www.gnu.org/licenses/>. + + +classdef JupyterNotebook < handle + + ## -*- texinfo -*- + ## @deftypefn {} {@var{notebook} =} JupyterNotebook (@var{notebookFileName}) + ## + ## Run and fill the Jupyter Notebook in @var{notebookFileName} within + ## GNU Octave. + ## + ## Supported are textual and graphical Octave outputs. + ## + ## This class has a public attribute @qcode{notebook} which is a struct + ## representing the JSON-decoded Jupyter Notebook. This attribute is + ## intentionally public to enable advanced notebook manipulations. + ## + ## Note: Jupyter Notebook versions (@qcode{nbformat}) lower than 4.0 are + ## not supported. + ## + ## @qcode{%plot} magic is supported with the following settings: + ## @itemize @bullet + ## @item + ## "%plot -f <format>" or "%plot --format <format>": specifies the + ## image storage format. Supported formats are: + ## + ## @itemize @minus + ## @item + ## PNG (default) + ## + ## @item + ## SVG (Note: If SVG images do not appear in the notebook, it is most + ## related to the Jupyter Notebook security mechanism and explicitly + ## "trusting" them is necessary). + ## + ## @item + ## JPG + ## @end itemize + ## + ## @item + ## "%plot -r <number>" or "%plot --resolution <number>": specifies the + ## image resolution. + ## + ## @item + ## "%plot -w <number>" or "%plot --width <number>": specifies the + ## image width. + ## + ## @item + ## "%plot -h <number>" or "%plot --height <number>": specifies the + ## image height. + ## @end itemize + ## + ## Examples: + ## + ## @example + ## @group + ## ## Run all cells and generate the filled notebook + ## + ## ## Instantiate an object from the notebook file + ## notebook = JupyterNotebook("myNotebook.ipynb") + ## @result{} notebook = + ## + ## <object JupyterNotebook> + ## + ## ## Run the code and embed the results in the @qcode{notebook} attribute + ## notebook.runAll() + ## ## Generate the new notebook by overwriting the original notebook + ## notebook.generateNotebook("myNotebook.ipynb") + ## @end group + ## + ## @group + ## ## Run the second cell and generate the filled notebook + ## + ## ## Instantiate an object from the notebook file + ## notebook = JupyterNotebook("myNotebook.ipynb") + ## @result{} notebook = + ## + ## <object JupyterNotebook> + ## + ## ## Run the code and embed the results in the @qcode{notebook} attribute + ## notebook.run(2) + ## ## Generate the new notebook in a new file + ## notebook.generateNotebook("myNewNotebook.ipynb") + ## @end group + ## + ## @group + ## ## Generate an Octave script from a notebook + ## + ## ## Instantiate an object from the notebook file + ## notebook = JupyterNotebook("myNotebook.ipynb") + ## @result{} notebook = + ## + ## <object JupyterNotebook> + ## + ## ## Generate the octave script + ## notebook.generateOctaveScript("myScript.m") + ## @end group + ## @end example + ## + ## @seealso{jsondecode, jsonencode} + ## @end deftypefn + + properties + + notebook = struct() + + endproperties + + properties (Access = "private") + + context = struct("ans", "") + + endproperties + + methods + + function obj = JupyterNotebook (notebookFileName) + + if (nargin != 1) + print_usage (); + endif + + if (! (ischar (notebookFileName) && isrow (notebookFileName))) + error ("JupyterNotebook: notebookFileName must be a string"); + endif + + obj.notebook = jsondecode (fileread (notebookFileName), + "makeValidName", false); + + ## Validate the notebook's format according to nbformat: 4.0 + if (! (isfield (obj.notebook, "metadata") + && isfield (obj.notebook, "nbformat") + && isfield (obj.notebook, "nbformat_minor") + && isfield (obj.notebook, "cells"))) + error ("JupyterNotebook: not valid format for Jupyter notebooks"); + endif + + ## Issue a warning if the format is lower than 4.0 + if (obj.notebook.nbformat < 4) + warning (["JupyterNotebook: nbformat versions lower than 4.0 are ", ... + "not supported"]); + endif + + ## Handle the case if there is only one cell. + ## Make "obj.notebook.cells" a cell of structs to match the format. + if (numel (obj.notebook.cells) == 1) + obj.notebook.cells = {obj.notebook.cells}; + endif + + ## Handle the case if the cells have the same keys. + ## Make "obj.notebook.cells" a cell of structs instead of struct array + ## to unify the indexing method. + if (isstruct (obj.notebook.cells)) + obj.notebook.cells = num2cell (obj.notebook.cells); + endif + + for i = 1:numel (obj.notebook.cells) + if (! isfield (obj.notebook.cells{i}, "source")) + error ("JupyterNotebook: cells must contain a \"source\" field"); + endif + + if (! isfield (obj.notebook.cells{i}, "cell_type")) + error ("JupyterNotebook: cells must contain a \"cell_type\" field"); + endif + + ## Handle when null JSON values are decoded into empty arrays. + if (isfield (obj.notebook.cells{i}, "execution_count") + && numel (obj.notebook.cells{i}.execution_count) == 0) + obj.notebook.cells{i}.execution_count = 1; + endif + + ## Handle the case if there is only one output in the cell. + ## Make the outputs of the cell a cell of structs to match the format. + if (isfield (obj.notebook.cells{i}, "outputs") + && numel (obj.notebook.cells{i}.outputs) == 1) + obj.notebook.cells{i}.outputs = {obj.notebook.cells{i}.outputs}; + endif + endfor + + endfunction + + + function generateOctaveScript (obj, scriptFileName) + + ## -*- texinfo -*- + ## @deftypefn {} {} generateOctaveScript (@var{scriptFileName}) + ## + ## Write an Octave script that has the contents of the Jupyter Notebook + ## stored in the @qcode{notebook} attribute to @var{scriptFileName}. + ## + ## Non code cells are generated as block comments. + ## + ## See @code{help JupyterNotebook} for examples. + ## + ## @end deftypefn + + if (nargin != 2) + print_usage (); + endif + + if (! (ischar (scriptFileName) && isrow (scriptFileName))) + error ("JupyterNotebook: scriptFileName must be a string"); + endif + + fhandle = fopen (scriptFileName, "w"); + + for i = 1:numel (obj.notebook.cells) + if (strcmp (obj.notebook.cells{i}.cell_type, "markdown")) + fputs (fhandle, "\n#{\n"); + endif + + for k = 1:numel (obj.notebook.cells{i}.source) + fputs (fhandle, obj.notebook.cells{i}.source{k}); + endfor + + if (strcmp (obj.notebook.cells{i}.cell_type, "markdown")) + fputs (fhandle, "\n#}\n"); + endif + fputs (fhandle, "\n"); + endfor + fclose (fhandle); + + endfunction + + + function generateNotebook (obj, notebookFileName) + + ## -*- texinfo -*- + ## @deftypefn {} {} generateNotebook (@var{notebookFileName}) + ## + ## Write the Jupyter Notebook stored in the @qcode{notebook} + ## attribute to @var{notebookFileName}. + ## + ## The @qcode{notebook} attribute is encoded to JSON text. + ## + ## See @code{help JupyterNotebook} for examples. + ## + ## @end deftypefn + + if (nargin != 2) + print_usage (); + endif + + if (! (ischar (notebookFileName) && isrow (notebookFileName))) + error ("JupyterNotebook: notebookFileName must be a string"); + endif + + fhandle = fopen (notebookFileName, "w"); + + fputs (fhandle, jsonencode (obj.notebook, "ConvertInfAndNaN", false, + "PrettyPrint", true)); + + fclose (fhandle); + + endfunction + + + function run (obj, cell_index) + + ## -*- texinfo -*- + ## @deftypefn {} {} run (@var{cell_index}) + ## + ## Run the Jupyter Notebook cell with index @var{cell_index} + ## and eventually replace previous output cells in the object. + ## + ## The first Jupyter Notebook cell has the index 1. + ## + ## Note: The code evaluation of the Jupyter Notebook cells is done + ## in a separate Jupyter Notebook context. Thus currently open + ## figures and workspace variables won't be affected by executing + ## this function. However, current workspace variables cannot be + ## accessed either. + ## + ## See @code{help JupyterNotebook} for examples. + ## + ## @end deftypefn + + if (nargin != 2) + print_usage (); + endif + + if (! (isscalar (cell_index) && ! islogical (cell_index) + && (mod (cell_index, 1) == 0) && (cell_index > 0))) + error ("JupyterNotebook: cell_index must be a scalar positive integer"); + endif + + if (cell_index > length (obj.notebook.cells)) + error ("JupyterNotebook: cell_index is out of bound"); + endif + + if (! strcmp (obj.notebook.cells{cell_index}.cell_type, "code")) + return; + endif + + ## Remove previous outputs. + obj.notebook.cells{cell_index}.outputs = {}; + + if (isempty (obj.notebook.cells{cell_index}.source)) + return; + endif + + ## Default values for printOptions. + printOptions.imageFormat = "png"; + printOptions.resolution = "0"; + + ## The default width and height in Jupyter notebook + printOptions.width = "640"; + printOptions.height = "480"; + + ## Parse "plot magic" commands. + ## https://github.com/Calysto/metakernel/blob/master/metakernel/ ... + ## magics/README.md#plot + for j = 1 : numel (obj.notebook.cells{cell_index}.source) + if (strncmpi (obj.notebook.cells{cell_index}.source{j}, "%plot", 5)) + magics = strsplit (strtrim ( + obj.notebook.cells{cell_index}.source{j})); + for i = 1 : numel (magics) + if (any (strcmp (magics{i}, {"-f", "--format"})) + && (i < numel (magics))) + printOptions.imageFormat = magics{i+1}; + endif + if (any (strcmp (magics{i}, {"-r", "--resolution"})) + && (i < numel (magics))) + printOptions.resolution = magics{i+1}; + endif + if (any (strcmp (magics{i}, {"-w", "--width"})) + && (i < numel (magics))) + printOptions.width = magics{i+1}; + endif + if (any (strcmp (magics{i}, {"-h", "--height"})) + && (i < numel (magics))) + printOptions.height = magics{i+1}; + endif + endfor + endif + endfor + + ## Remember previously opened figures. + fig_ids = findall (0, "type", "figure"); + + ## Create a new figure, if there are existing plots. + if (! isempty (fig_ids)) + newFig = figure (); + endif + + stream_output = struct ("name", "stdout", "output_type", "stream"); + + output_lines = obj.evalCode (strjoin ( + obj.notebook.cells{cell_index}.source)); + + if (! isempty(output_lines)) + stream_output.text = {output_lines}; + endif + + if (isfield (stream_output, "text")) + obj.notebook.cells{cell_index}.outputs{end + 1} = stream_output; + endif + + ## If there are existing plots and newFig is empty, delete it. + if (exist ("newFig") && isempty (get (newFig, "children"))) + delete (newFig); + endif + + ## Check for newly created figures. + fig_ids_new = setdiff (findall (0, "type", "figure"), fig_ids); + + if (numel (fig_ids_new) > 0) + if (exist ("__octave_jupyter_temp__", "dir")) + ## Delete open figures before raising the error. + for i = 1:numel (fig_ids_new) + delete (fig_ids_new(i)); + endfor + error (["JupyterNotebook: temporary directory ", ... + "__octave_jupyter_temp__ exists. Please remove it ", ... + "manually."]); + endif + + [status, msg, msgid] = mkdir ("__octave_jupyter_temp__"); + if (status == 0) + ## Delete open figures before raising the error. + for i = 1 : numel (fig_ids_new) + delete (fig_ids_new(i)); + endfor + error (["JupyterNotebook: Cannot create a temporary directory. ", ... + msg]); + endif + + for i = 1:numel (fig_ids_new) + figure (fig_ids_new(i), "visible", "off"); + obj.embedImage (cell_index, fig_ids_new (i), printOptions); + delete (fig_ids_new(i)); + endfor + + [status, msg, msgid] = rmdir ("__octave_jupyter_temp__"); + if (status == 0) + error (["JupyterNotebook: Cannot delete the temporary ", ... + "directory. ", msg]); + endif + endif + + endfunction + + + function runAll (obj) + + ## -*- texinfo -*- + ## @deftypefn {} {} runAll () + ## + ## Run all Jupyter Notebook cells and eventually replace previous + ## output cells in the object. + ## + ## Note: The code evaluation of the Jupyter Notebook cells is done + ## in a separate Jupyter Notebook context. Thus currently open + ## figures and workspace variables won't be affected by executing + ## this function. However, current workspace variables cannot be + ## accessed either. + ## + ## See @code{help JupyterNotebook} for examples. + ## + ## @end deftypefn + + if (nargin != 1) + print_usage (); + endif + + for i = 1:numel (obj.notebook.cells) + obj.run(i); + endfor + + endfunction + + endmethods + + + methods (Access = "private") + + function retVal = evalCode (__obj__, __code__) + + ## Evaluate the code string "__code__" using "evalc". + ## Before the code is evaluated, the previous notebook context is + ## loaded from "__obj__" and the new context is saved to that struct. + + if (nargin != 2) + print_usage (); + endif + + if (isempty (__code__)) + retVal = []; + return; + endif + + if (! (ischar (__code__) && isrow (__code__))) + error ("JupyterNotebook: code must be a string"); + endif + + __obj__.loadContext (); + + ## Add a statement to detect the value of the variable "ans" + __code__ = [__code__, "\nans"]; + + retVal = strtrim (evalc (__code__, ["printf (\"error: \"); ", ... + "printf (lasterror.message)"])); + + ## Handle the "ans" variable in the context. + start_index = rindex (retVal, "ans =") + 6; + if ((start_index > 6)) + if ((start_index <= length (retVal))) + end_index = start_index; + while ((retVal(end_index) != "\n") && (end_index < length (retVal))) + end_index += 1; + endwhile + __obj__.context.ans = retVal(start_index:end_index); + else + end_index = length (retVal); + __obj__.context.ans = ""; + endif + + ## Delete the output of the additional statement if the execution + ## is completed with no errors. + if (end_index == length (retVal)) + ## Remove the extra new line if there are other outputs with + ## the "ans" statement output + if (start_index == 7) + start_index = 1; + else + start_index = start_index - 7; + endif + retVal(start_index:end_index) = ""; + endif + endif + + __obj__.saveContext (); + + endfunction + + + function saveContext (obj, op) + + ## Save the context in private "obj" attribute. + + ## Handle the "ans" variable in the context. + obj.context = struct ("ans", obj.context.ans); + + forbidden_var_names = {"__code__", "__obj__", "ans"}; + + ## Get variable names. + var_names = {evalin("caller", "whos").name}; + + ## Store all variables to context. + for i = 1:length (var_names) + if (! any (strcmp (var_names{i}, forbidden_var_names))) + obj.context.(var_names{i}) = evalin ("caller", var_names{i}); + endif + endfor + + endfunction + + + function loadContext (obj) + + ## Load the context from private "obj" attribute. + for [val, key] = obj.context + assignin ("caller", key, val); + endfor + + endfunction + + + function embedImage (obj, cell_index, figHandle, printOptions) + + ## Embed images in the notebook. + ## + ## To support a new format: + ## 1. Create a new function that embeds the new format + ## (e.g. embed_svg_image). + ## 2. Add a new case to the switch-statement below. + + if (isempty (get (figHandle, "children"))) + error_text = {"The figure is empty!"}; + obj.addErrorOutput (cell_index, "The figure is empty!"); + return; + endif + + ## Check if the resolution is correct + if (isempty (str2num (printOptions.resolution))) + obj.addErrorOutput (cell_index, + "A number is required for resolution, not a string"); + return; + endif + + ## Check if the width is correct + if (isempty (str2num (printOptions.width))) + obj.addErrorOutput (cell_index, + "A number is required for width, not a string"); + return; + endif + + ## Check if the height is correct + if (isempty (str2num (printOptions.height))) + obj.addErrorOutput (cell_index, + "A number is required for height, not a string"); + return; + endif + + switch (lower (printOptions.imageFormat)) + case "png" + display_output = obj.embed_png_jpg_image (figHandle, + printOptions, "png"); + case "jpg" + display_output = obj.embed_png_jpg_image (figHandle, + printOptions, "jpg"); + case "svg" + display_output = obj.embed_svg_image (figHandle, printOptions); + otherwise + obj.addErrorOutput (cell_index, ["Cannot embed the \'", ... + printOptions.imageFormat, ... + "\' image format\n"]); + return; + endswitch + + obj.notebook.cells{cell_index}.outputs{end + 1} = display_output; + + endfunction + + + function dstruct = embed_png_jpg_image (obj, figHandle, printOptions, fmt) + + if (strcmp (fmt, "png")) + mime = "image/png"; + else + mime = "image/jpeg"; + endif + + image_path = fullfile ("__octave_jupyter_temp__", ["temp.", fmt]); + print (figHandle, image_path, ["-d", fmt], + ["-r" printOptions.resolution]); + + dstruct.output_type = "display_data"; + dstruct.metadata.(mime).width = printOptions.width; + dstruct.metadata.(mime).height = printOptions.height; + dstruct.data.("text/plain") = {"<IPython.core.display.Image object>"}; + dstruct.data.(mime) = base64_encode (uint8 (fileread (image_path))); + + delete (image_path); + + endfunction + + + function dstruct = embed_svg_image (obj, figHandle, printOptions) + + image_path = fullfile ("__octave_jupyter_temp__", "temp.svg"); + print (figHandle, image_path, "-dsvg", ["-r" printOptions.resolution]); + + dstruct.output_type = "display_data"; + dstruct.metadata = struct (); + dstruct.data.("text/plain") = {"<IPython.core.display.SVG object>"}; + dstruct.data.("image/svg+xml") = strsplit (fileread (image_path), "\n"); + + ## FIXME: The following is a workaround until we can properly print + ## SVG images in the right width and height. + ## Detect the <svg> tag. it is either the first or the second item + if (strncmpi (dstruct.data.("image/svg+xml"){1}, "<svg", 4)) + i = 1; + else + i = 2; + endif + + ## Embed the width and height in the image itself + svg_tag = dstruct.data.("image/svg+xml"){i}; + svg_tag = regexprep (svg_tag, "width=\"(.*?)\"", + ["width=\"" printOptions.width "px\""]); + svg_tag = regexprep (svg_tag, "height=\"(.*?)\"", + ["height=\"" printOptions.height "px\""]); + dstruct.data.("image/svg+xml"){i} = svg_tag; + + delete (image_path); + + endfunction + + + function addErrorOutput (obj, cell_index, error_msg) + + stream_output.name = "stderr"; + stream_output.output_type = "stream"; + stream_output.text = {error_msg}; + obj.notebook.cells{cell_index}.outputs{end + 1} = stream_output; + + endfunction + + endmethods + +endclassdef + +#!error JupyterNotebook ()
--- a/scripts/miscellaneous/module.mk Mon Sep 13 21:10:02 2021 -0700 +++ b/scripts/miscellaneous/module.mk Tue Sep 14 17:54:04 2021 +0900 @@ -40,6 +40,7 @@ %reldir%/ismethod.m \ %reldir%/ispc.m \ %reldir%/isunix.m \ + %reldir%/JupyterNotebook.m \ %reldir%/license.m \ %reldir%/list_primes.m \ %reldir%/loadobj.m \
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test/jupyter-notebook/JupyterNotebook.tst Tue Sep 14 17:54:04 2021 +0900 @@ -0,0 +1,231 @@ +######################################################################## +## +## Copyright (C) 2021 The Octave Project Developers +## +## See the file COPYRIGHT.md in the top-level directory of this +## distribution or <https://octave.org/copyright/>. +## +## This file is part of Octave. +## +## Octave is free software: you can redistribute it and/or modify it +## under the terms of the GNU General Public License as published by +## the Free Software Foundation, either version 3 of the License, or +## (at your option) any later version. +## +## Octave is distributed in the hope that it will be useful, but +## WITHOUT ANY WARRANTY; without even the implied warranty of +## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +## GNU General Public License for more details. +## +## You should have received a copy of the GNU General Public License +## along with Octave; see the file COPYING. If not, see +## <https://www.gnu.org/licenses/>. +## +######################################################################## + + + + + +%! visibility = get (0, "defaultfigurevisible"); +%! toolkit = graphics_toolkit (); +%! unwind_protect +%! if (! __have_feature__ ("QT_OFFSCREEN") +%! || ! strcmp (graphics_toolkit (), "qt")) +%! try +%! graphics_toolkit ("gnuplot"); +%! catch +%! ## The system doesn't support gnuplot for drawing hidden +%! ## figures. Just return and have test marked as passing. +%! return; +%! end_try_catch +%! endif +%! set (0, "defaultfigurevisible", "off"); +%! + + +%! unwind_protect_cleanup +%! set (0, "defaultfigurevisible", visibility); +%! graphics_toolkit (toolkit); +%! end_unwind_protect + + + + + + +## Test running a single cell +%!test +%! visibility = get (0, "defaultfigurevisible"); +%! toolkit = graphics_toolkit (); +%! unwind_protect +%! if (! __have_feature__ ("QT_OFFSCREEN") +%! || ! strcmp (graphics_toolkit (), "qt")) +%! try +%! graphics_toolkit ("gnuplot"); +%! catch +%! ## The system doesn't support gnuplot for drawing hidden +%! ## figures. Just return and have test marked as passing. +%! return; +%! end_try_catch +%! endif +%! set (0, "defaultfigurevisible", "off"); +%! +%! n = JupyterNotebook (fullfile ("octave_kernel.ipynb")); +%! +%! ## Test embedding images +%! n.run (2); +%! assert (n.notebook.cells{2}.outputs{1}.output_type, "display_data") +%! assert (isfield (n.notebook.cells{2}.outputs{1}.data, "image/png")); +%! assert (getfield (n.notebook.cells{2}.outputs{1}.data, "text/plain"), +%! {"<IPython.core.display.Image object>"}); +%! +%! ## Test running non-code cells +%! markdown_cell = n.notebook.cells{1}; +%! n.run (1); +%! assert (markdown_cell, n.notebook.cells{1}); +%! unwind_protect_cleanup +%! set (0, "defaultfigurevisible", visibility); +%! graphics_toolkit (toolkit); +%! end_unwind_protect + +## Test running all cells +%!test +%! visibility = get (0, "defaultfigurevisible"); +%! toolkit = graphics_toolkit (); +%! unwind_protect +%! if (! __have_feature__ ("QT_OFFSCREEN") +%! || ! strcmp (graphics_toolkit (), "qt")) +%! try +%! graphics_toolkit ("gnuplot"); +%! catch +%! ## The system doesn't support gnuplot for drawing hidden +%! ## figures. Just return and have test marked as passing. +%! return; +%! end_try_catch +%! endif +%! set (0, "defaultfigurevisible", "off"); +%! +%! n = JupyterNotebook (fullfile ("octave_kernel.ipynb")); +%! n.runAll (); +%! +%! ## Test embedding images +%! assert (n.notebook.cells{3}.outputs{1}.output_type, "display_data") +%! assert (isfield (n.notebook.cells{3}.outputs{1}.data, "image/png")); +%! assert (getfield (n.notebook.cells{3}.outputs{1}.data, "text/plain"), +%! {"<IPython.core.display.Image object>"}); +%! +%! ## Test running non-code cells +%! markdown_cell = n.notebook.cells{1}; +%! n.run (1); +%! assert (markdown_cell, n.notebook.cells{1}); +%! +%! ## Test embedding textual output +%! assert (n.notebook.cells{6}.outputs{1}.output_type, "stream") +%! assert (n.notebook.cells{6}.outputs{1}.name, "stdout"); +%! unwind_protect_cleanup +%! set (0, "defaultfigurevisible", visibility); +%! graphics_toolkit (toolkit); +%! end_unwind_protect + +## Test plot magic +%!test +%! visibility = get (0, "defaultfigurevisible"); +%! toolkit = graphics_toolkit (); +%! unwind_protect +%! if (! __have_feature__ ("QT_OFFSCREEN") +%! || ! strcmp (graphics_toolkit (), "qt")) +%! try +%! graphics_toolkit ("gnuplot"); +%! catch +%! ## The system doesn't support gnuplot for drawing hidden +%! ## figures. Just return and have test marked as passing. +%! return; +%! end_try_catch +%! endif +%! set (0, "defaultfigurevisible", "off"); +%! +%! n = JupyterNotebook (fullfile ("plot_magic_and_errors.ipynb")); +%! +%! ## PNG format +%! n.run (1); +%! assert (n.notebook.cells{1}.outputs{1}.output_type, "display_data") +%! assert (isfield (n.notebook.cells{1}.outputs{1}.data, "image/png")); +%! assert (getfield (n.notebook.cells{1}.outputs{1}.data, "text/plain"), +%! {"<IPython.core.display.Image object>"}); +%! +%! ## SVG format +%! n.run (2); +%! assert (n.notebook.cells{2}.outputs{1}.output_type, "display_data") +%! assert (isfield (n.notebook.cells{2}.outputs{1}.data, "image/svg+xml")); +%! assert (getfield (n.notebook.cells{2}.outputs{1}.data, "text/plain"), +%! {"<IPython.core.display.SVG object>"}); +%! +%! ## JPG format +%! n.run (3); +%! assert (n.notebook.cells{3}.outputs{1}.output_type, "display_data") +%! assert (isfield (n.notebook.cells{3}.outputs{1}.data, "image/jpeg")); +%! assert (getfield (n.notebook.cells{3}.outputs{1}.data, "text/plain"), +%! {"<IPython.core.display.Image object>"}); +%! unwind_protect_cleanup +%! set (0, "defaultfigurevisible", visibility); +%! graphics_toolkit (toolkit); +%! end_unwind_protect + +## Test errors +%!test +%! visibility = get (0, "defaultfigurevisible"); +%! toolkit = graphics_toolkit (); +%! unwind_protect +%! if (! __have_feature__ ("QT_OFFSCREEN") +%! || ! strcmp (graphics_toolkit (), "qt")) +%! try +%! graphics_toolkit ("gnuplot"); +%! catch +%! ## The system doesn't support gnuplot for drawing hidden +%! ## figures. Just return and have test marked as passing. +%! return; +%! end_try_catch +%! endif +%! set (0, "defaultfigurevisible", "off"); +%! +%! n = JupyterNotebook (fullfile ("plot_magic_and_errors.ipynb")); +%! +%! ## Wrong resolution +%! n.run (4); +%! assert (n.notebook.cells{4}.outputs{1}.output_type, "stream") +%! assert (n.notebook.cells{4}.outputs{1}.name, "stderr"); +%! assert (n.notebook.cells{4}.outputs{1}.text, +%! {"A number is required for resolution, not a string"}); +%! +%! ## Wrong width +%! n.run (5); +%! assert (n.notebook.cells{5}.outputs{1}.output_type, "stream") +%! assert (n.notebook.cells{5}.outputs{1}.name, "stderr"); +%! assert (n.notebook.cells{5}.outputs{1}.text, +%! {"A number is required for width, not a string"}); +%! +%! ## Wrong height +%! n.run (6); +%! assert (n.notebook.cells{6}.outputs{1}.output_type, "stream") +%! assert (n.notebook.cells{6}.outputs{1}.name, "stderr"); +%! assert (n.notebook.cells{6}.outputs{1}.text, +%! {"A number is required for height, not a string"}); +%! +%! ## Empty figure +%! n.run (7); +%! assert (n.notebook.cells{7}.outputs{1}.output_type, "stream") +%! assert (n.notebook.cells{7}.outputs{1}.name, "stderr"); +%! assert (n.notebook.cells{7}.outputs{1}.text, +%! {"The figure is empty!"}); +%! +%! ## Wrong format +%! n.run (8); +%! assert (n.notebook.cells{8}.outputs{1}.output_type, "stream") +%! assert (n.notebook.cells{8}.outputs{1}.name, "stderr"); +%! assert (n.notebook.cells{8}.outputs{1}.text, +%! {"Cannot embed the 'pdf' image format\n"}); +%! unwind_protect_cleanup +%! set (0, "defaultfigurevisible", visibility); +%! graphics_toolkit (toolkit); +%! end_unwind_protect
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test/jupyter-notebook/module.mk Tue Sep 14 17:54:04 2021 +0900 @@ -0,0 +1,6 @@ +jupyter_TEST_FILES = \ + %reldir%/JupyterNotebook.tst \ + %reldir%/octave_kernel.ipynb \ + %reldir%/plot_magic_and_errors.ipynb + +TEST_FILES += $(jupyter_TEST_FILES)
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test/jupyter-notebook/octave_kernel.ipynb Tue Sep 14 17:54:04 2021 +0900 @@ -0,0 +1,1050 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This Jupyter notebook is taken from <https://github.com/Calysto/octave_kernel>.\n", + "\n", + "##### Jupyter Octave Kernel\n", + "============\n", + "\n", + "Interact with Octave in Notebook. All commands are interpreted by Octave. Since this is a [MetaKernel](https://github.com/Calysto/metakernel), a standard set of magics are available. Help on commands is available using the `%help` magic or using `?` with a command." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<IPython.core.display.Image object>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "t = linspace(0,6*pi,100);\n", + "plot(sin(t))\n", + "grid on\n", + "hold on\n", + "plot(cos(t), 'r')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "<IPython.core.display.Image object>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%plot --format png \n", + "tx = ty = linspace (-8, 8, 41)';\n", + "[xx, yy] = meshgrid (tx, ty);\n", + "r = sqrt (xx .^ 2 + yy .^ 2) + eps;\n", + "tz = sin (r) ./ r;\n", + "mesh (tx, ty, tz);" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "a =\n", + "\n", + " 1 2 3\n", + "\n" + ] + } + ], + "source": [ + "a = [1,2,3]\n", + "5+3;" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ans = 8\n", + "a =\n", + "\n", + " 1 2 3\n", + "\n" + ] + } + ], + "source": [ + "ans\n", + "a\n", + "b = a + 3;" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 4 5 6\n" + ] + } + ], + "source": [ + "disp(b)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The width or the height can be specified to constrain the image while maintaining the original aspect ratio." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/svg+xml": [ + "<svg height=\"450px\" viewBox=\"0 0 560 420\" width=\"600px\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n", + "\n", + "<title>Gnuplot</title>\n", + "<desc>Produced by GNUPLOT 5.2 patchlevel 2 </desc>\n", + "\n", + "<g id=\"gnuplot_canvas\">\n", + "\n", + "<rect fill=\"none\" height=\"420\" width=\"560\" x=\"0\" y=\"0\"/>\n", + "<defs>\n", + "\n", + "\t<circle id=\"gpDot\" r=\"0.5\" stroke-width=\"0.5\"/>\n", + "\t<path d=\"M-1,0 h2 M0,-1 v2\" id=\"gpPt0\" stroke=\"currentColor\" stroke-width=\"0.222\"/>\n", + "\t<path d=\"M-1,-1 L1,1 M1,-1 L-1,1\" id=\"gpPt1\" 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stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "\t<path class=\"gridline\" d=\"M72.8,31.6 L506.7,31.6 \" opacity=\"0.15\" stroke=\"rgb( 38, 38, 38)\"/></g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 38, 38, 38)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "\t<path d=\"M72.8,31.6 L85.3,31.6 M506.7,31.6 L494.2,31.6 \" stroke=\"rgb( 0, 0, 0)\"/>\t<g fill=\"rgb(38,38,38)\" font-family=\"Arial\" font-size=\"10.00\" stroke=\"none\" text-anchor=\"end\" transform=\"translate(64.5,34.9)\">\n", + "\t\t<text><tspan font-family=\"Arial\">0</tspan></text>\n", + "\t</g>\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" 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text-anchor=\"middle\" transform=\"translate(72.8,195.0)\">\n", + "\t\t<text><tspan font-family=\"Arial\">0</tspan></text>\n", + "\t</g>\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 0, 0, 0)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "\t<path class=\"gridline\" d=\"M159.6,173.7 L159.6,31.6 \" opacity=\"0.15\" stroke=\"rgb( 38, 38, 38)\"/></g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 38, 38, 38)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + 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color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "\t<path class=\"gridline\" d=\"M419.9,173.7 L419.9,31.6 \" opacity=\"0.15\" stroke=\"rgb( 38, 38, 38)\"/></g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 38, 38, 38)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "\t<path d=\"M419.9,173.7 L419.9,161.2 M419.9,31.6 L419.9,44.1 \" stroke=\"rgb( 0, 0, 0)\"/>\t<g fill=\"rgb(38,38,38)\" font-family=\"Arial\" font-size=\"10.00\" stroke=\"none\" text-anchor=\"middle\" transform=\"translate(419.9,195.0)\">\n", + "\t\t<text><tspan font-family=\"Arial\">0.8</tspan></text>\n", + "\t</g>\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" 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\" stroke=\"rgb( 0, 0, 0)\"/>\t<g fill=\"rgb(38,38,38)\" font-family=\"Arial\" font-size=\"10.00\" stroke=\"none\" text-anchor=\"end\" transform=\"translate(64.5,235.1)\">\n", + "\t\t<text><tspan font-family=\"Arial\">0</tspan></text>\n", + "\t</g>\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 0, 0, 0)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "\t<path class=\"gridline\" d=\"M72.8,373.8 L72.8,231.8 \" opacity=\"0.15\" stroke=\"rgb( 38, 38, 38)\"/></g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 38, 38, 38)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "\t<path d=\"M72.8,373.8 L72.8,361.3 M72.8,231.8 L72.8,244.3 \" stroke=\"rgb( 0, 0, 0)\"/>\t<g fill=\"rgb(38,38,38)\" font-family=\"Arial\" font-size=\"10.00\" stroke=\"none\" text-anchor=\"middle\" transform=\"translate(72.8,395.1)\">\n", + "\t\t<text><tspan font-family=\"Arial\">0</tspan></text>\n", + "\t</g>\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 0, 0, 0)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "\t<path class=\"gridline\" d=\"M159.6,373.8 L159.6,231.8 \" opacity=\"0.15\" stroke=\"rgb( 38, 38, 38)\"/></g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 38, 38, 38)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "\t<path d=\"M159.6,373.8 L159.6,361.3 M159.6,231.8 L159.6,244.3 \" stroke=\"rgb( 0, 0, 0)\"/>\t<g fill=\"rgb(38,38,38)\" font-family=\"Arial\" font-size=\"10.00\" stroke=\"none\" text-anchor=\"middle\" transform=\"translate(159.6,395.1)\">\n", + "\t\t<text><tspan font-family=\"Arial\">0.2</tspan></text>\n", + "\t</g>\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 0, 0, 0)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "\t<path class=\"gridline\" d=\"M246.4,373.8 L246.4,231.8 \" opacity=\"0.15\" stroke=\"rgb( 38, 38, 38)\"/></g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 38, 38, 38)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "\t<path d=\"M246.4,373.8 L246.4,361.3 M246.4,231.8 L246.4,244.3 \" stroke=\"rgb( 0, 0, 0)\"/>\t<g fill=\"rgb(38,38,38)\" font-family=\"Arial\" font-size=\"10.00\" stroke=\"none\" text-anchor=\"middle\" transform=\"translate(246.4,395.1)\">\n", + "\t\t<text><tspan font-family=\"Arial\">0.4</tspan></text>\n", + "\t</g>\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 0, 0, 0)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "\t<path class=\"gridline\" d=\"M333.1,373.8 L333.1,231.8 \" opacity=\"0.15\" stroke=\"rgb( 38, 38, 38)\"/></g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 38, 38, 38)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "\t<path d=\"M333.1,373.8 L333.1,361.3 M333.1,231.8 L333.1,244.3 \" stroke=\"rgb( 0, 0, 0)\"/>\t<g fill=\"rgb(38,38,38)\" font-family=\"Arial\" font-size=\"10.00\" stroke=\"none\" text-anchor=\"middle\" transform=\"translate(333.1,395.1)\">\n", + "\t\t<text><tspan font-family=\"Arial\">0.6</tspan></text>\n", + "\t</g>\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 0, 0, 0)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "\t<path class=\"gridline\" d=\"M419.9,373.8 L419.9,231.8 \" opacity=\"0.15\" stroke=\"rgb( 38, 38, 38)\"/></g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 38, 38, 38)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "\t<path d=\"M419.9,373.8 L419.9,361.3 M419.9,231.8 L419.9,244.3 \" stroke=\"rgb( 0, 0, 0)\"/>\t<g fill=\"rgb(38,38,38)\" font-family=\"Arial\" font-size=\"10.00\" stroke=\"none\" text-anchor=\"middle\" transform=\"translate(419.9,395.1)\">\n", + "\t\t<text><tspan font-family=\"Arial\">0.8</tspan></text>\n", + "\t</g>\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 0, 0, 0)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "\t<path class=\"gridline\" d=\"M506.7,373.8 L506.7,231.8 \" opacity=\"0.15\" stroke=\"rgb( 38, 38, 38)\"/></g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 38, 38, 38)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "\t<path d=\"M506.7,373.8 L506.7,361.3 M506.7,231.8 L506.7,244.3 \" stroke=\"rgb( 0, 0, 0)\"/>\t<g fill=\"rgb(38,38,38)\" font-family=\"Arial\" font-size=\"10.00\" stroke=\"none\" text-anchor=\"middle\" transform=\"translate(506.7,395.1)\">\n", + "\t\t<text><tspan font-family=\"Arial\">1</tspan></text>\n", + "\t</g>\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "\t<g fill=\"rgb(38,38,38)\" font-family=\"Arial\" font-size=\"11.00\" stroke=\"none\" text-anchor=\"middle\" transform=\"translate(16.8,302.8) rotate(-90)\">\n", + "\t\t<text><tspan font-family=\"Arial\">Phase (degrees)</tspan></text>\n", + "\t</g>\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "\t<g fill=\"rgb(38,38,38)\" font-family=\"Arial\" font-size=\"11.00\" stroke=\"none\" text-anchor=\"middle\" transform=\"translate(289.7,422.3)\">\n", + "\t\t<text><tspan font-family=\"Arial\">Normalized Frequency (</tspan><tspan font-family=\"Symbol\">�</tspan><tspan font-family=\"Symbol\">p</tspan><tspan font-family=\"Arial\"> rad/sample)</tspan></text>\n", + "\t</g>\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "\t<g id=\"gnuplot_plot_1b\"><title>gnuplot_plot_1b</title>\n", + "<g color=\"white\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "\t<path d=\"M72.8,231.8 L86.4,234.6 L99.9,237.5 L113.5,240.4 L127.0,243.4 L140.6,246.5 L154.2,249.8 L167.7,253.2 L181.3,256.8 L194.8,260.7 L208.4,264.9 L222.0,269.4 L235.5,274.1 L249.1,279.2 L262.6,284.5 L276.2,290.1 L289.8,295.7 L303.3,301.3 L316.9,306.9 L330.4,312.2 L344.0,317.3 L357.5,322.0 L371.1,326.5 L384.7,330.7 L398.2,334.6 L411.8,338.2 L425.3,341.6 L438.9,344.9 L452.5,348.0 L466.0,351.0 L479.6,353.9 L493.1,356.8 L506.7,359.6 \" stroke=\"rgb( 0, 114, 189)\"/></g>\n", + "\t</g>\n", + "<g color=\"white\" fill=\"none\" stroke=\"rgb( 0, 114, 189)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"2.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"2.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"black\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "\t<path d=\"M72.8,373.8 L506.7,373.8 M72.8,231.8 L506.7,231.8 M72.8,373.8 L72.8,231.8 M506.7,373.8 L506.7,231.8 \" stroke=\"rgb( 38, 38, 38)\"/></g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"rgb( 38, 38, 38)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "</g>\n", + "</svg>" + ], + "text/plain": [ + "<IPython.core.display.SVG object>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%plot -f svg -w 600\n", + "\n", + "% butterworth filter, order 2, cutoff pi/2 radians\n", + "b = [0.292893218813452 0.585786437626905 0.292893218813452];\n", + "a = [1 0 0.171572875253810];\n", + "freqz(b, a, 32);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Multiple figures can be drawn. Note that when using imshow the image will be created as a PNG with the raw\n", + "image dimensions unless the image has a title or labels." + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "image/png": 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9x2b8Z+gk06uqbHrdghJxHfxXzksrWoQp9BNaixme5/M1Tmx19TYuubaKMvqw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\nnf+DYErCj4zoKk2a/j8NF8ZQWtGvJAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "<IPython.core.display.Image object>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "% small image\n", + "imshow(randn(100,100))\n", + "\n", + "% let's change the data range\n", + "figure\n", + "imshow(randn(100,100), [-10 10])\n", + "\n", + "% let's try automatic range and different size\n", + "figure\n", + "imshow(randn(100,200), [])\n", + "colormap('autumn')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "image/png": 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tsgTm14FROeHwDsgQCTSVYVtH6DgB+p6AxfEhdWrYnhjaloLBs6BeS1jcHw63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+ "text/plain": [ + "<IPython.core.display.Image object>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "% Create an RGB image with no title or labels\n", + "close all hidden\n", + "image = zeros(300,400,3);\n", + "image(1:100,:,1) = 0.9; % Red\n", + "image(101:200,:,2) = rand(100,400); % Green\n", + "image(201:300,:,3) = 0.9; % Blue\n", + "imshow(image)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "image/svg+xml": [ + "<svg height=\"420px\" viewBox=\"0 0 560 420\" width=\"560px\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n", + "\n", + "<title>Gnuplot</title>\n", + "<desc>Produced by GNUPLOT 5.1 patchlevel 0 </desc>\n", + "\n", + "<g id=\"gnuplot_canvas\">\n", + "\n", + "<rect fill=\"none\" height=\"420\" width=\"560\" x=\"0\" y=\"0\"/>\n", + "<defs>\n", + "\n", + "\t<circle id=\"gpDot\" r=\"0.5\" stroke-width=\"0.5\"/>\n", + "\t<path d=\"M-1,0 h2 M0,-1 v2\" id=\"gpPt0\" stroke=\"currentColor\" stroke-width=\"0.333\"/>\n", + "\t<path d=\"M-1,-1 L1,1 M1,-1 L-1,1\" id=\"gpPt1\" stroke=\"currentColor\" stroke-width=\"0.333\"/>\n", + "\t<path d=\"M-1,0 L1,0 M0,-1 L0,1 M-1,-1 L1,1 M-1,1 L1,-1\" id=\"gpPt2\" stroke=\"currentColor\" stroke-width=\"0.333\"/>\n", + "\t<rect height=\"2\" id=\"gpPt3\" stroke=\"currentColor\" stroke-width=\"0.333\" width=\"2\" x=\"-1\" y=\"-1\"/>\n", + "\t<rect fill=\"currentColor\" height=\"2\" id=\"gpPt4\" stroke=\"currentColor\" stroke-width=\"0.333\" width=\"2\" x=\"-1\" y=\"-1\"/>\n", + "\t<circle cx=\"0\" cy=\"0\" id=\"gpPt5\" r=\"1\" stroke=\"currentColor\" stroke-width=\"0.333\"/>\n", + "\t<use fill=\"currentColor\" id=\"gpPt6\" stroke=\"none\" xlink:href=\"#gpPt5\"/>\n", + "\t<path d=\"M0,-1.33 L-1.33,0.67 L1.33,0.67 z\" id=\"gpPt7\" stroke=\"currentColor\" stroke-width=\"0.333\"/>\n", + "\t<use 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filterUnits=\"objectBoundingBox\" height=\"1\" id=\"greybox\" width=\"1\" x=\"0\" y=\"0\">\n", + "\t <feFlood flood-color=\"lightgrey\" flood-opacity=\"1\" result=\"grey\"/>\n", + "\t <feComposite in=\"SourceGraphic\" in2=\"grey\" operator=\"atop\"/>\n", + "\t</filter>\n", + "</defs>\n", + "<g color=\"white\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "\t<g id=\"gnuplot_plot_1a\"><title>gnuplot_plot_1a</title>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "<image height=\"342.2\" preserveAspectRatio=\"none\" width=\"342.2\" x=\"118.6\" xlink:href=\"gp_image_01.png\" y=\"31.6\"/>\n", + "</g>\n", + "\t</g>\n", + "<g color=\"black\" fill=\"none\" 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color=\"black\" fill=\"none\" stroke=\"rgb(255, 255, 255)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "\t<path d=\"M72.8,373.8 L81.2,373.8 M252.5,373.8 L244.1,373.8 \" stroke=\"black\"/>\t<g fill=\"rgb(0,0,0)\" font-family=\"{}\" font-size=\"10.00\" stroke=\"none\" text-anchor=\"end\" transform=\"translate(67.2,377.5)\">\n", + "\t\t<text><tspan font-family=\"{}\">1</tspan></text>\n", + "\t</g>\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "\t<path d=\"M72.8,288.2 L81.2,288.2 M252.5,288.2 L244.1,288.2 \" stroke=\"black\"/>\t<g fill=\"rgb(0,0,0)\" font-family=\"{}\" font-size=\"10.00\" stroke=\"none\" text-anchor=\"end\" transform=\"translate(67.2,291.9)\">\n", + "\t\t<text><tspan 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stroke-width=\"0.50\">\n", + "\t<path d=\"M72.8,31.6 L72.8,373.8 L252.5,373.8 L252.5,31.6 L72.8,31.6 Z \" stroke=\"black\"/></g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "\t<g id=\"gnuplot_plot_1a\"><title>gnuplot_plot_1a</title>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "\t<path d=\"M72.8,373.8 L162.7,202.7 L252.5,31.6 \" stroke=\"rgb( 0, 0, 255)\"/></g>\n", + "\t</g>\n", + "<g color=\"white\" fill=\"none\" stroke=\"rgb( 0, 0, 255)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"2.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"2.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"black\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "\t<g id=\"gnuplot_plot_1b\"><title>gnuplot_plot_1b</title>\n", + "<g color=\"white\" fill=\"none\" stroke=\"black\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"1.00\">\n", + "<image height=\"179.7\" preserveAspectRatio=\"none\" width=\"179.7\" x=\"327.0\" xlink:href=\"gp_image_01.png\" y=\"112.9\"/>\n", + "</g>\n", + "\t</g>\n", + "<g color=\"white\" fill=\"none\" stroke=\"rgb(148, 0, 211)\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"black\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"2.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"2.00\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"black\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "<g color=\"black\" fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" stroke-width=\"0.50\">\n", + "</g>\n", + "</g>\n", + "</svg>" + ], + "text/plain": [ + "<IPython.core.display.SVG object>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "% let's add a title - this produces full figure\n", + "imshow(rand(100,100))\n", + "title('Hello')\n", + "\n", + "% let's create an image next to a plot\n", + "figure\n", + "subplot(121)\n", + "plot([1,2,3])\n", + "subplot(122)\n", + "imshow(randn(100,100))" + ] + } + ], + "metadata": { + "anaconda-cloud": {}, + "kernelspec": { + "display_name": "Octave", + "language": "octave", + "name": "octave" + }, + "language_info": { + "file_extension": ".m", + "help_links": [ + { + "text": "GNU Octave", + "url": "https://www.gnu.org/software/octave/support.html" + }, + { + "text": "Octave Kernel", + "url": "https://github.com/Calysto/octave_kernel" + }, + { + "text": "MetaKernel Magics", + "url": "https://metakernel.readthedocs.io/en/latest/source/README.html" + } + ], + "mimetype": "text/x-octave", + "name": "octave", + "version": "6.3.0" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test/jupyter-notebook/plot_magic_and_errors.ipynb Tue Sep 14 17:54:04 2021 +0900 @@ -0,0 +1,216 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "healthy-group", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "<IPython.core.display.Image object>" + ] + }, + "metadata": { + "image/jpeg": { + "height": "480", + "width": "640" + } + }, + "output_type": "display_data" + } + ], + "source": [ + "%plot --format jpg \n", + "x = -10:0.1:10;\n", + "plot (x, sin (x));\n", + "title (\"sin(x) for x = -10:0.1:10\");\n", + "xlabel (\"x\");\n", + "ylabel (\"sin (x)\");\n", + "text (pi, 0.7, \"arbitrary text\");\n", + "legend (\"sin (x)\");" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "global-latex", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "A number is required for resolution, not a string" + ] + } + ], + "source": [ + "%plot -f jpg -r 1a0\n", + "plot([5 4])" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "designing-greece", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "A number is required for width, not a string" + ] + } + ], + "source": [ + "%plot -f jpg --width 1a0\n", + "plot([5 4])" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "configured-eating", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "A number is required for height, not a string" + ] + } + ], + "source": [ + "%plot -f jpg -h 1a0\n", + "plot([5 4])" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "specified-omega", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "The figure is empty!" + ] + } + ], + "source": [ + "figure" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "serious-exhibit", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Cannot embed the 'pdf' image format\n" + ] + } + ], + "source": [ + "%plot -f pdf\n", + "plot([5 4])" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Octave", + "language": "octave", + "name": "octave" + }, + "language_info": { + "file_extension": ".m", + "help_links": [ + { + "text": "GNU Octave", + "url": "https://www.gnu.org/software/octave/support.html" + }, + { + "text": "Octave Kernel", + "url": "https://github.com/Calysto/octave_kernel" + }, + { + "text": "MetaKernel Magics", + "url": "https://metakernel.readthedocs.io/en/latest/source/README.html" + } + ], + "mimetype": "text/x-octave", + "name": "octave", + "version": "6.3.0" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}
--- a/test/module.mk Mon Sep 13 21:10:02 2021 -0700 +++ b/test/module.mk Tue Sep 14 17:54:04 2021 +0900 @@ -104,6 +104,7 @@ include %reldir%/ctor-vs-method/module.mk include %reldir%/fcn-handle/module.mk include %reldir%/json/module.mk +include %reldir%/jupyter-notebook/module.mk include %reldir%/local-functions/module.mk include %reldir%/mex/module.mk include %reldir%/nest/module.mk