Uses https://github.com/lukasschwab/arxiv.py to perform a query on ArXiv. The output is organized as a Pandas dataframe. By reindexing the dataframe according to
date-like columns as published
or updated
it is possible to compute histograms showing the amount of papers published per year or month-year. Finally,
scipy is used to fit a curve to the histogram data.
Clone the repository, cd in the repository folder and type
pip install -e .
A query, the histogram and fit are performed by running the following code
from arxivq.arxivq import ArxivQ
import matplotlib.pyplot as plt
def func(x, a, b, c):
return a * np.exp(-b * x)
query_dlm = ArxivQ(search_query="deep learning AND music",
id_list=[],
prune=True,
start=0,
max_results=10000,
sort_by="submittedDate",
sort_order="descending")
query_dlm.plot_histogram(bin_by = "Y", column = "published")
query_dlm.fit(func)
- See https://github.com/lukasschwab/arxiv.py for the code to call the ArXiv API