%matplotlib ipympl
import numpy as np
import matplotlib.pyplot as plt
import itertools
import spectrochempy as scp
import pandas as pd
|
SpectroChemPy's API - v.0.5.1 © Copyright 2014-2023 - A.Travert & C.Fernandez @ LCS |
Warning: Cannot change to a different GUI toolkit: widget. Using ipympl instead.
def cmtoum(x):
return 10000/x
def umtocm(x):
return 10000/x
def CreateDualAxisIRPlot(FontSize=12):
# Plot with two axes.
fig, axcm = plt.subplots()
axcm.set_xlabel('cm$^{-1}$', fontsize=FontSize)
axum = axcm.secondary_xaxis('top', functions=(cmtoum, umtocm))
axum.set_xlabel('$\mu$m', fontsize=FontSize)
axcm.set_ylabel('a.u.', fontsize=FontSize)
axcm.tick_params('x', labelsize=FontSize)
axcm.tick_params('y', labelsize=FontSize)
axum.tick_params('x', labelsize=FontSize)
axum.xaxis.set_ticks(range(6,12))
axcm.xaxis.set_ticks(range(900,1900,100))
return fig, axcm
def FinishDualAxisIRPlot(fig, axcm, Title='', FontSize=12):
axcm.legend()
axcm.invert_xaxis()
plt.title(Title, fontsize=FontSize*1.5)
plt.tight_layout()
def plotone(ax, SpecName, Spectradf, offset=0, Norm=False, **kwargs):
S = Spectradf[SpecName].to_numpy()
if Norm==True:
S -= np.min(S)
S /= np.max(S)
axcm = Spectradf['X value [cm-1]'].to_numpy()
ax.plot(axcm, S+offset, label=SpecName, **kwargs)
def EncapsulateSpectrum(df, csvlabel):
S = scp.NDDataset(df[csvlabel].to_numpy(), units='a.u.', title='absorption')
S.data -= np.min(S.data)
S.data /= np.max(S.data)
S.x = scp.NDDataset(df['X value [cm-1]'].to_numpy(), units='cm^-1', title='wavenumbers')
return S
# Read in the raw csv files.
df016 = pd.read_csv('016 - Point Spectra.csv')
df016 = df016[~df016['X value [cm-1]'].isin([1505, 1537, 1557, 1621, 1633, 1645, 1681])]
df018 = pd.read_csv('018 spectra.csv')
df018 = df018[~df018['X value [cm-1]'].isin([1419, 1507, 1521, 1539, 1557, 1558, 1559, 1616, 1623, 1635, 1645, 1652, 1683, 1684, 1696, 1701, 1704, 1706, 1717, 1718, 1733, 1754, 1780, 1784, 1790, 1792, 1799])]
# Convert the csv files into a dictionary of spectrum objects.
Spectra = {}
SmoothLength = 19
Spectra['Green'] = EncapsulateSpectrum(df018, 'Spectrum 5 Green phase').smooth(window_length=SmoothLength)
Spectra['CarbonateBottom'] = EncapsulateSpectrum(df018, 'Spectrum 11 Carbonate bottom').smooth(window_length=SmoothLength)
Spectra['CarbonateTop'] = EncapsulateSpectrum(df018, 'Spectrum 3 Carbonate top').smooth(window_length=SmoothLength)
Spectra['White'] = EncapsulateSpectrum(df018, 'Spectrum 2 White').smooth(window_length=SmoothLength)
Spectra['TopRed'] = EncapsulateSpectrum(df018, 'Spectrum 9 Top red').smooth(window_length=SmoothLength)
Spectra['Purple'] = EncapsulateSpectrum(df016, 'Spectrum 3 Purple').smooth(window_length=1)
Spectra['Red'] = EncapsulateSpectrum(df016, 'Spectrum 1 Red').smooth(window_length=1)
Spectra['Blue'] = EncapsulateSpectrum(df016, 'Spectrum 2 Blue').smooth(window_length=1)
fig,ax = CreateDualAxisIRPlot(FontSize=12)
S = Spectra['TopRed']
ax.plot(S.x.data, S.data+1.8, label='a', linewidth=2, color='xkcd:dark pink')
S = Spectra['CarbonateTop']
ax.plot(S.x.data, S.data+1, label='b', linewidth=2, color='xkcd:yellowy brown')
# ax.plot(S.x.data, S.smooth(window_length=19).data+2, label='Carbonate Top', linewidth=2, color='gray')
S = Spectra['CarbonateBottom']
ax.plot(S.x.data, S.data+0.5, label='c', linewidth=2, color='orange')
S = Spectra['Green']
ax.plot(S.x.data, S.data, label='d', linewidth=2, color='forestgreen')
S = Spectra['White']
ax.plot(S.x.data, S.data-0.5, label='e', linewidth=2, color='xkcd:cement')
# S = Spectra['Purple']
# ax.plot(S.x.data, S.data-1.0, label='Purple', linewidth=2, color='Purple')
FinishDualAxisIRPlot(fig, ax, Title='', FontSize=12)
fig.set_size_inches(6,8)
plt.savefig('FIBSpectra.png', dpi=300)
fig,ax = CreateDualAxisIRPlot(FontSize=12)
S = Spectra['TopRed']
ax.plot(S.x.data, S.data+0.1, label='a', linewidth=2, color='xkcd:dark pink')
S = Spectra['Green']
ax.plot(S.x.data, S.data, label='d', linewidth=2, color='forestgreen')
S = Spectra['White']
ax.plot(S.x.data, S.data-0.1, label='e', linewidth=2, color='xkcd:cement')
FinishDualAxisIRPlot(fig, ax, Title='', FontSize=12)
fig.set_size_inches(6,8)
plt.ylim([-0.1,0.3])
plt.xlim([1800,1100])
plt.savefig('PhylloOrganics.png', dpi=300)
!jupyter nbconvert --to html 'PlotSpectra.ipynb'
This application is used to convert notebook files (*.ipynb)
to various other formats.
WARNING: THE COMMANDLINE INTERFACE MAY CHANGE IN FUTURE RELEASES.
Options
=======
The options below are convenience aliases to configurable class-options,
as listed in the "Equivalent to" description-line of the aliases.
To see all configurable class-options for some <cmd>, use:
<cmd> --help-all
--debug
set log level to logging.DEBUG (maximize logging output)
Equivalent to: [--Application.log_level=10]
--show-config
Show the application's configuration (human-readable format)
Equivalent to: [--Application.show_config=True]
--show-config-json
Show the application's configuration (json format)
Equivalent to: [--Application.show_config_json=True]
--generate-config
generate default config file
Equivalent to: [--JupyterApp.generate_config=True]
-y
Answer yes to any questions instead of prompting.
Equivalent to: [--JupyterApp.answer_yes=True]
--execute
Execute the notebook prior to export.
Equivalent to: [--ExecutePreprocessor.enabled=True]
--allow-errors
Continue notebook execution even if one of the cells throws an error and include the error message in the cell output (the default behaviour is to abort conversion). This flag is only relevant if '--execute' was specified, too.
Equivalent to: [--ExecutePreprocessor.allow_errors=True]
--stdin
read a single notebook file from stdin. Write the resulting notebook with default basename 'notebook.*'
Equivalent to: [--NbConvertApp.from_stdin=True]
--stdout
Write notebook output to stdout instead of files.
Equivalent to: [--NbConvertApp.writer_class=StdoutWriter]
--inplace
Run nbconvert in place, overwriting the existing notebook (only
relevant when converting to notebook format)
Equivalent to: [--NbConvertApp.use_output_suffix=False --NbConvertApp.export_format=notebook --FilesWriter.build_directory=]
--clear-output
Clear output of current file and save in place,
overwriting the existing notebook.
Equivalent to: [--NbConvertApp.use_output_suffix=False --NbConvertApp.export_format=notebook --FilesWriter.build_directory= --ClearOutputPreprocessor.enabled=True]
--no-prompt
Exclude input and output prompts from converted document.
Equivalent to: [--TemplateExporter.exclude_input_prompt=True --TemplateExporter.exclude_output_prompt=True]
--no-input
Exclude input cells and output prompts from converted document.
This mode is ideal for generating code-free reports.
Equivalent to: [--TemplateExporter.exclude_output_prompt=True --TemplateExporter.exclude_input=True --TemplateExporter.exclude_input_prompt=True]
--allow-chromium-download
Whether to allow downloading chromium if no suitable version is found on the system.
Equivalent to: [--WebPDFExporter.allow_chromium_download=True]
--disable-chromium-sandbox
Disable chromium security sandbox when converting to PDF..
Equivalent to: [--WebPDFExporter.disable_sandbox=True]
--show-input
Shows code input. This flag is only useful for dejavu users.
Equivalent to: [--TemplateExporter.exclude_input=False]
--embed-images
Embed the images as base64 dataurls in the output. This flag is only useful for the HTML/WebPDF/Slides exports.
Equivalent to: [--HTMLExporter.embed_images=True]
--log-level=<Enum>
Set the log level by value or name.
Choices: any of [0, 10, 20, 30, 40, 50, 'DEBUG', 'INFO', 'WARN', 'ERROR', 'CRITICAL']
Default: 30
Equivalent to: [--Application.log_level]
--config=<Unicode>
Full path of a config file.
Default: ''
Equivalent to: [--JupyterApp.config_file]
--to=<Unicode>
The export format to be used, either one of the built-in formats
['asciidoc', 'custom', 'html', 'latex', 'markdown', 'notebook', 'pdf', 'python', 'rst', 'script', 'slides', 'webpdf']
or a dotted object name that represents the import path for an
``Exporter`` class
Default: ''
Equivalent to: [--NbConvertApp.export_format]
--template=<Unicode>
Name of the template to use
Default: ''
Equivalent to: [--TemplateExporter.template_name]
--template-file=<Unicode>
Name of the template file to use
Default: None
Equivalent to: [--TemplateExporter.template_file]
--theme=<Unicode>
Template specific theme(e.g. the name of a JupyterLab CSS theme distributed
as prebuilt extension for the lab template)
Default: 'light'
Equivalent to: [--HTMLExporter.theme]
--writer=<DottedObjectName>
Writer class used to write the
results of the conversion
Default: 'FilesWriter'
Equivalent to: [--NbConvertApp.writer_class]
--post=<DottedOrNone>
PostProcessor class used to write the
results of the conversion
Default: ''
Equivalent to: [--NbConvertApp.postprocessor_class]
--output=<Unicode>
overwrite base name use for output files.
can only be used when converting one notebook at a time.
Default: ''
Equivalent to: [--NbConvertApp.output_base]
--output-dir=<Unicode>
Directory to write output(s) to. Defaults
to output to the directory of each notebook. To recover
previous default behaviour (outputting to the current
working directory) use . as the flag value.
Default: ''
Equivalent to: [--FilesWriter.build_directory]
--reveal-prefix=<Unicode>
The URL prefix for reveal.js (version 3.x).
This defaults to the reveal CDN, but can be any url pointing to a copy
of reveal.js.
For speaker notes to work, this must be a relative path to a local
copy of reveal.js: e.g., "reveal.js".
If a relative path is given, it must be a subdirectory of the
current directory (from which the server is run).
See the usage documentation
(https://nbconvert.readthedocs.io/en/latest/usage.html#reveal-js-html-slideshow)
for more details.
Default: ''
Equivalent to: [--SlidesExporter.reveal_url_prefix]
--nbformat=<Enum>
The nbformat version to write.
Use this to downgrade notebooks.
Choices: any of [1, 2, 3, 4]
Default: 4
Equivalent to: [--NotebookExporter.nbformat_version]
Examples
--------
The simplest way to use nbconvert is
> jupyter nbconvert mynotebook.ipynb --to html
Options include ['asciidoc', 'custom', 'html', 'latex', 'markdown', 'notebook', 'pdf', 'python', 'rst', 'script', 'slides', 'webpdf'].
> jupyter nbconvert --to latex mynotebook.ipynb
Both HTML and LaTeX support multiple output templates. LaTeX includes
'base', 'article' and 'report'. HTML includes 'basic', 'lab' and
'classic'. You can specify the flavor of the format used.
> jupyter nbconvert --to html --template lab mynotebook.ipynb
You can also pipe the output to stdout, rather than a file
> jupyter nbconvert mynotebook.ipynb --stdout
PDF is generated via latex
> jupyter nbconvert mynotebook.ipynb --to pdf
You can get (and serve) a Reveal.js-powered slideshow
> jupyter nbconvert myslides.ipynb --to slides --post serve
Multiple notebooks can be given at the command line in a couple of
different ways:
> jupyter nbconvert notebook*.ipynb
> jupyter nbconvert notebook1.ipynb notebook2.ipynb
or you can specify the notebooks list in a config file, containing::
c.NbConvertApp.notebooks = ["my_notebook.ipynb"]
> jupyter nbconvert --config mycfg.py
To see all available configurables, use `--help-all`.
[NbConvertApp] WARNING | pattern "'PlotSpectra.ipynb'" matched no files