eventplotter.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jun 30 20:01:53 2021

@author: amandabreton
Allows user to pick view a species result from eventchecker.py.
Takes in the text files created by BirdNET and provides
the user with a list of the most probable bird species.
The user then tells the script which speices they would
like to investigate further and a graph is shown that
shows how the counts of that bird species changes throughout
the day.

"""
# set up modules and paths
import pandas as pd
import os
import numpy as np
import exiftool
import matplotlib.pyplot as plt
import argparse
import yaml
import eventplotter_functions as epf
import math
# %% setup your paths
parser = argparse.ArgumentParser()
parser.add_argument('config_filename')
args = parser.parse_args()
CONFIG_FILE = args.config_filename
with open(CONFIG_FILE) as f:
    configs = yaml.load(f, Loader=yaml.SafeLoader)
path = configs['path']
threshold = configs['threshold']
biodiversity_reserve_bird_list = configs['biodiversity_reserve_bird_list']
# %% yaml file example
# path:'/Users/amandabreton/Documents/GitHub/gnatcatcher/sounds/'
# threshold: 0.8
# biodiversity_reserve_bird_list: '/Users/amandabreton/Documents/GitHub/gnatcatcher/reservebirds.csv'
# %%
# %% use epf.listtxtfiles to create list of txt files made by BirdNET.
txtfiles = epf.listtxtfiles(path)
# %% Create dataframe of BirdNET species, confidences and audio sources
knbirds, confidences, source = epf.df_details(txtfiles, threshold)

# %% setting up stuff to graph
specieslist, df1, df2 = epf.speciesplotlist(knbirds, source)

BRBLdf = pd.read_csv(biodiversity_reserve_bird_list, header=0)
reservebirds = BRBLdf['COMMON']

foundinreserve = []
for i in range(len(specieslist)):
    bird = specieslist[i]
    if reservebirds.str.contains(bird).any():
        foundinreserve.append(bird)
# %%
print('Here are the species you can plot:')
print(df2)
print('Based on the reserve, here are the most probable birds:')
print(foundinreserve)
print('Which species would you like to investigate further?')
print('Input the index corresponding to the spcies')
val = input()
val = int(val)
bird = specieslist[val]
# %%
sources = []
count = []
times = []
comments = []

for i in range(len(df1['Audio Source'])):
    if bird == str(df1['Species'][i]):
        audsource = (df1['Audio Source'][i])
        sources.append(audsource)
        freq = (df1['Count'][i])
        count.append(freq)
        exifpath = str(path) + str(df1['Audio Source'][i])
        with exiftool.ExifTool() as et:
            audComment = et.get_tag("Comment", exifpath)
        time = audComment[12:17]
        comments.append(audComment)
        times.append(time)
    else:
        pass

df3 = pd.DataFrame(list(zip(times, sources, count)),
                   columns=['Time', 'Audio Source', 'Count'])
# %%

#%%

df3.plot.bar(x='Time', y='Count', rot=0)
plt.xlabel("Time")
plt.ylabel("Count")
plt.title(bird)
plt.gca().set_yticks(df3["Count"].unique())
plt.show()