Matplotlib: Saving an self-contained, editable Figure - python

Is there way to save a "Figure" in matplotlib to a file such that if you later wanted to modify the Figure, e.g. change data points, resize the figure, etc. you could load up the file in a new python script and do that?
Right now I save the majority of my plots as Pdfs, but that doesn't allow me to make edits later on. I have to go dig up my old source code and data files. I've lost track of the number of times I've lost the plot-generating code and have to essentially reproduce it all from scratch.
It would be nice if I could just save a plot as a self-contained data file, like Photoshop does with its .psd files, so that I can just load it up directly, type "object.plot()", and not have to worry about external dependencies. Does such a format exist, or if not is there any way I could achieve this?


There is a method of saving the plotted object called pickling. I don't have much experience with it but it should allow you to save the plot to a file using
fig = plt.figure
pl.dump(fig, file('file_name.pickle','w'))
and using
fig = pl.load(open('file_name.pickle','rb'))
fig.show()
to load the saved graph.
Matplotlib warns that, "Pickle files are not designed for long term storage, are unsupported when restoring a pickle saved in another matplotlib version". To be safe, I would just save the array containing the data to the plot to either a .csv or .txt file, and keep this file in a folder with the python file to plot the graph. This way you will always be able to plot your data (no matter the version of matplotlib you are using). You will also have the data and code in the same place, and you can easily read the data from the .csv or .txt file, save it to arrays, and graph it using
file = open("file_name.txt", "r")
if file.mode == 'r':
data = f.read().splitlines()
data_array1 = data[0].split(",")
data_array2 = data[1].split(",")
p, = plt.plot(data_array1, data_array2)
I also suggest uploading your python files along with your .csv or .txt files to Github.
If you would like to read more about pickling in matplotlib I suggest reading the two pages linked below.
(1) Pickle figures from matplotlib
and (2) https://matplotlib.org/3.1.3/users/prev_whats_new/whats_new_1.2.html#figures-are-picklable

Related

how to combine matplotlib figures after they are saved?

I know that the ideal solution would be to plot them in multiple axes by calling plt.subplots(nrows=x, ncols=y) but the code where I am plotting was already structured in a way which would make it very hard for me to convert to plotting in the same context like that...
So that being said, I have a folder with 5 saved .pdf images that were created in matplotlib. Is there a way I can open these up and save them in the same file while maintaining the .pdf filetype (i.e. not converting them to .pngs in some image editing program)?

Is there any way to save all graphs generated using the script to a single file (image preferably)

The scripts I use generate a lot of graphs. I was wondering if there was a way to save them or specified ones into a single file as image or pdf for quicklooks.
Thank you.

If you are using matplotlib, it would be easiest to use the subplots feature. This will make all of your graphs part of a single object, which can be saved as an image like you want. I would redirect you to the matplotlib website for a ton of good example on the subject. https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.subplots.html
Then, do
fig.savefig('mysweetsubplots.png')
and you are done.

How to use Python Seaborn Visualizations in PowerPoint?

I created some figures with Seaborn in a Jupyter Notebook. I would now like to present those figures in a PowerPoint presentation.
I know that it is possible to export the figures as png and include them in the presentation. But then they would be static, and if something changes in the dataframe, the picture would be the same. Is there an option to have a dynamic figure in PowerPoint? Something like a small Jupyter Notebook you could Display in the slides?

You could try Anaconda Fusion (also the video here), which let's you use Python inside of Excel. This could possibly work since you can link figures/data elements between Excel and PowerPoint (but special restrictions might apply when the figure is created via Python rather than standard Excel). Anaconda Fusion is free to try for a couple of months.
Another solution would be to use the Jupyter Notebook to create your presentation instead of PowerPoint. Go to View -> Cell Toolbar -> Slideshowand you can choose which code cells should become slides.
A third approach would be to create an animation of the figure as the data frame changes and then include the animation (GIF or video) in PowerPoint.

The following procedures probably won't be the most elegant solution, but it will let you produce a Seaborn plot, store it as an image file, and export the same image to an open powerpoint presentation. Depending on whether you set LinkToFile to True or False, the images will or will not update when the source changes. I'm messing around with this using cells in Spyder, but it should work in a Jupyter notebook as well. Make sure that you have a folder named c:\pptSeaborn\.
Here it is:
# Some imports
import numpy as np
import seaborn as sns
import os
import matplotlib.pyplot as plt
import win32com.client
import win32api
os.chdir('C:/pptSeaborn')
# Settings for some random data
mu = 0
sigma = 1
simulation = np.random.normal(mu, sigma, 10)
# Make seaborn plot from simulated data. Save as image file.
def SeabornPlot(data, filename = 'c:\\pptSeaborn\\snsPlot.png'):
ax = sns.kdeplot(data, shade=True)
fig = ax.get_figure()
fig.savefig(filename, bbox_inches='tight', dpi = 440)
plt.close(fig)
# Import image file to active powerpoint presentation
def SeabornPPT(plotSource, linkImage):
Application = win32com.client.Dispatch("PowerPoint.Application")
Presentation = Application.Activepresentation
slidenr = Presentation.Slides.Count + 1
Base = Presentation.Slides.Add(slidenr, 12)
gph = Base.Shapes.AddPicture(FileName=plotSource,
LinkToFile=linkImage, SaveWithDocument=True,
Left=50, Top=25, Width=800, Height=500)
Presentation.slides(slidenr).select()
# Produce data, save plot as image, and export image to powerpoint
SeabornPlot(data = simulation)
SeabornPPT(plotSource = 'c:\\pptSeaborn\\snsPlot.png', linkImage = False)
Now, if you have an open powerpoint presentation and run this whole thing five times, you will get somthing like this:
If you go ahead and save this somewhere, and reopen it, it will still look the same.
Now you can set linkImage = True, and run the whole thing five times again. Depending on the random data generated, you will still get five slides with different graphs.
But NOW, if you save the presentation and reopen it, all plots will look the same because they're linked to the same image file:
The next step could be to wrap the whole thing into a function that takes filename and LinkToFile as arguments. You could also include whether or not the procedure makes a new slide each time an image is exported. I hope you find my sggestion useful. I liked your question, and I'm hoping to see a few other suggestions as well.

We now went with this approach:
You can save the figures as a .png file and insert this into Powerpoint. There is an Option when inserting it, that the Picture will be updated every time you open PowerPoint, retrivining a new version of the file from the Folder I saved it to. So when I make changes in Seaborn, a new version of the file is automatically saved as a Picture which will then be updated in PowerPoint.

Store plotted data for later use

I do much (practically all) of my data analysis in Jupyter/iPython-notebooks. For convenience, I obviously also plot my data in those notebooks using matplotlib/pyplot.
Some of those plots I need to recreate externally later on, for example to use them in latex. For this I save the corresponding data as textfiles to the harddrive. Right now, I manually create a numpy-array by stacking all the data needed for the plot, and save this using numpy.savetxt.
What I would like to have is a way to save all data needed for a specific plot written to the same file in an (semi)automatic way, but I am at a loss if it comes to the smart way of doing so.
Thus I have two questions:
Is it possible (and save to do) to create something like a plot-memory object, that stores all data plotted per figure, and has a method similar to Memoryobject.save_plot_to_file(figname)? This object would need to know which figure I am working on, so I would need to create a layer above matplotlib, or get this information from the matplotlib objects
Is there a simpler way? The python universe is huge, and I do not know half of it. Maybe something like this already exists?
Edit: Clarification: I do not want to save the figure object. What I want to do is something like this:
fig = plt.figure()
fig.plot(x1, y1)
fig.plot(x2, y2 + y3)
# and at a later point
arrays = get_data_from_plot(fig)
data = process(arrays)
np.savetxt('textfile', data)

You could pickle the object (using the cPickle module). See this question here.

extracting the data through python script in paraview

How to extract data from plot data filter in paraview through python script?? I want to get data through python script by which paraview is drawing the graph.
If anyone know this answer please help
Thank you

Usually plots are made by plotting one data array versus another. You can often obtain that data directly from the filter/source that produced it and save it to a CSV file. To do this, select
You can save data from a filter as a CSV file by selecting the filter/source in the Pipeline Browser and choosing File -> Save Data. Choose the CSV File (*.csv) file type. Arrays in the filter/source output are written to different columns in the CSV file.

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