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[U] Use reporter

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This commit is contained in:
Hykilpikonna
2021-11-24 18:32:45 -05:00
parent ebeba08c19
commit d2e2f4adbf
1 changed files with 47 additions and 24 deletions
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src/process/twitter_visualization.py
+47 -24
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@@ -2,6 +2,7 @@
TODO: Module Docstring
"""
import statistics
from typing import Any
from matplotlib import pyplot as plt
from tabulate import tabulate
@@ -21,8 +22,18 @@ class Reporter:
report = ''
self.file = file
def print(self, line: str) -> None:
self.report += line + '\n'
def print(self, line: str = '', arg: Any = None) -> None:
"""
Add a line to the report
:param line: Line content
:param arg: Additional argument
:return: None
"""
self.report += line
if arg is not None:
self.report += str(arg)
self.report += '\n'
def save(self) -> None:
write(self.file, self.report)
@@ -51,17 +62,20 @@ def view_covid_tweets_freq(users: list[str],
# Sort by frequency
user_frequency.sort(key=lambda x: x[1], reverse=True)
# Init reporter
r = Reporter(f'{REPORT_DIR}/1-covid-tweet-frequency/{sample_name}.md')
r.print(f"In {sample_name} -")
# How many people didn't post about COVID?
print(f"In {sample_name} -")
print("How many people didn't post about COVID:",
len([a for a in user_frequency if a[1] == 0]))
print("How many people have less than 1% of their posts about COVID:",
r.print("How many people didn't post about COVID:",
len([a for a in user_frequency if a[1] == 0]))
r.print("How many people have less than 1% of their posts about COVID:",
len([a for a in user_frequency if a[1] <= 0.01]))
print()
r.print()
# Top 20
print(f"20 Users of who post COVID-related tweets most frequently:")
print(tabulate([[u[0], f'{u[1] * 100:.1f}%'] for u in user_frequency[:20]],
r.print(f"20 Users of who post COVID-related tweets most frequently:")
r.print(tabulate([[u[0], f'{u[1] * 100:.1f}%'] for u in user_frequency[:20]],
['Username', 'Frequency']))
# Graph histogram
@@ -70,6 +84,9 @@ def view_covid_tweets_freq(users: list[str],
plt.tight_layout()
plt.hist([f[1] for f in user_frequency], bins=100, color='#ffcccc')
plt.savefig(f'{REPORT_DIR}/1-covid-tweet-frequency/{sample_name}.png')
# Save report
r.save()
def view_covid_tweets_pop(users: list[str],
@@ -90,35 +107,38 @@ def view_covid_tweets_pop(users: list[str],
"""
user_popularity = load_covid_tweets_pop(users)
# Init reporter
r = Reporter(f'{REPORT_DIR}/2-covid-tweet-popularity/{sample_name}.md')
r.print(f"In {sample_name} -")
# How many people are ignored
print(f"In {sample_name} -")
print("To prevent division by zero, we ignored people who didn't post about COVID or didn't "
r.print("To prevent division by zero, we ignored people who didn't post about COVID or didn't "
f"post at all. We ignored {len(users) - len(user_popularity)} people in this list.")
print()
r.print()
# Top 20
print(f"20 Users of whose COVID-related posts are the most popular:")
print(tabulate([[u[0], f'{u[1]:.2f}'] for u in user_popularity[:20]],
r.print(f"20 Users of whose COVID-related posts are the most popular:")
r.print(tabulate([[u[0], f'{u[1]:.2f}'] for u in user_popularity[:20]],
['Username', 'Popularity Ratio']))
print()
r.print()
# Calculate statistics
x_list = [f[1] for f in user_popularity]
s = get_statistics(x_list)
print(f'With outliers, ')
print(f'- mean: {s.mean:.2f}, median: {s.median:.2f}, stddev: {s.stddev:.2f}')
print()
r.print(f'With outliers, ')
r.print(f'- mean: {s.mean:.2f}, median: {s.median:.2f}, stddev: {s.stddev:.2f}')
r.print()
# Remove outliers
print('As there are many outliers in the popularity ratio, they are removed in graphing.')
print()
r.print('As there are many outliers in the popularity ratio, they are removed in graphing.')
r.print()
x_list = remove_outliers(x_list)
# Calculate statistics without outliers
s = get_statistics(x_list)
print(f'Without outliers, ')
print(f'- mean: {s.mean:.2f}, median: {s.median:.2f}, stddev: {s.stddev:.2f}')
print()
r.print(f'Without outliers, ')
r.print(f'- mean: {s.mean:.2f}, median: {s.median:.2f}, stddev: {s.stddev:.2f}')
r.print()
# Graph histogram
plt.title(f'COVID-related popularity ratios for {sample_name}')
@@ -126,7 +146,10 @@ def view_covid_tweets_pop(users: list[str],
plt.tight_layout()
plt.hist(x_list, bins=40, color='#ffcccc')
plt.axvline([1], color='lightgray')
plt.show()
plt.savefig(f'{REPORT_DIR}/2-covid-tweet-popularity/{sample_name}.png')
# Save report
r.save()
def load_covid_tweets_pop(users: list[str]):