def test_simple_structure_file_catches_mixed_indents(self, tmpdir):
with open(os.path.join(str(tmpdir), "simple.txt"), "w", encoding= "utf-8") as f:
f.write("""DATA
pics: Photos
sounds: sound
audio: recording.wav
ANALYSIS
srcid: SRCID.txt""")
with pytest.raises(ValueError):
ds = iyore.Dataset(os.path.join(str(tmpdir), "simple.txt"))
def test_simple_structure_file_tabs(self, tmpdir):
with open(os.path.join(str(tmpdir), "simple.txt"), "w", encoding= "utf-8") as f:
f.write("""DATA
pics: Photos
sounds: sound
audio: recording.wav
ANALYSIS
srcid: SRCID.txt""")
ds = iyore.Dataset(os.path.join(str(tmpdir), "simple.txt"))
self.assert_simple_structure(ds)
def test_simple_structure_file_allow_comment_lines(self, tmpdir):
with open(os.path.join(str(tmpdir), "simple.txt"), "w", encoding= "utf-8") as f:
f.write("""
# first line comment
DATA
pics: Photos
# indented comment
sounds: sound
audio: recording.wav
#comment no preceding space
ANALYSIS
srcid: SRCID.txt
#extra indented comment""")
ds = iyore.Dataset(os.path.join(str(tmpdir), "simple.txt"))
self.assert_simple_structure(ds)
def dataset(self):
return iyore.Dataset(os.path.join(base, structureFile))
def datafiles_endpoint(self, request, makeTestTree):
if request.param == "manual":
return datafiles
else:
return iyore.Dataset(os.path.join(base, structureFile)).datafiles
def code_to_splat(file, code, outputdir):
# import the output of event extraction
flight_events = pd.read_csv(file, sep=",")
# extract the times of closest approach for each event
flight_events["ClosestApch"] = pd.to_datetime(flight_events["ClosestApch"])
print("Transcribing columns for " + code)
# create an empty srcid dataframe
srcid = pd.DataFrame()
# column 1: nvsplDate
flight_events["ClosestApch_date"] = flight_events["ClosestApch"].apply(
lambda x: x.date())
srcid['nvsplDate'] = flight_events["ClosestApch_date"]
# column 2: hr
flight_events["ClosestApch_time"] = flight_events["ClosestApch"].apply(
lambda x: x.time())
srcid['hr'] = flight_events["ClosestApch_time"].apply(lambda x: x.hour)
# column 3: secs
flight_events["ClosestApch_mins"] = flight_events["ClosestApch"].apply(
lambda x: x.time())
flight_events["ClosestApch_mins"] = flight_events["ClosestApch"].apply(
lambda x: x.minute)
flight_events["ClosestApch_secs"] = flight_events["ClosestApch"].apply(
lambda x: x.time())
flight_events["ClosestApch_secs"] = flight_events["ClosestApch"].apply(
lambda x: x.second)
# convert minutes to seconds
flight_events["ClosestApch_mins"] = flight_events[
"ClosestApch_mins"].apply(lambda x: 60 * x)
# add seconds from above step to seconds
srcid['secs'] = flight_events["ClosestApch_mins"] + flight_events[
"ClosestApch_secs"]
# column 4: len
srcid['len'] = 60
# column 5: srcID
srcid['srcID'] = flight_events["EventID"].apply(
lambda x: "1." + str(x).zfill(3))
#column 6
srcid['Hz_L'] = 12.5
#column 6
srcid['Hz_U'] = 2000
#column 7
srcid['MaxSPL'] = 0
#column 8
srcid['SEL'] = 0
#column 9
srcid['MaxSPLt'] = 0
#column 10
srcid['SELt'] = 0
#column 11
srcid['userName'] = "******"
#column 9
srcid['tagDate'] = "1000-01-01 00:00:01"
# column for sound data presence/absence -> will be populated after all processing
srcid['data'] = 1
# store initial frame length
framelength = len(srcid)
###############
################
# Check for audio data
###############
print("Removing points without available audio for " + code)
failure_count = 0
ds = iyore.Dataset("Y:")
# for every event in the srcid list
for i in srcid.index:
# extract time data
ymd = srcid.iat[i, 0]
hour = srcid.iat[i, 1]
year = ymd.year
month = ymd.month
day = ymd.day
#check availablity of a given event in the soundDB database
available = [
e for e in ds.nvspl(
site=code, year=year, month=month, day=day, hour=hour)
]
# if nothing is available, set avaialable field to zero
if (len(available) == 0):
srcid.ix[i, 13] = 0
failure_count = failure_count + 1
# generate the file name
filename = "SRCID_DENA" + str(flight_events.iloc[0,
0]) + "eventExtractor.txt"
print("Sorting and extracting data.")
#sort the dataframe by date/time
srcid = srcid.sort_values("nvsplDate")
srcid = srcid.loc[srcid["data"] == 1]
srcid = srcid.drop("data", axis=1)
# export to csv with correct naming convention based on station code
srcid.to_csv(outputdir + "SRCID_DENA" + code + ".txt",
sep="\t",
index=False)
# function for adding header lines to files
def prepend(path, text):
with open(path, 'r+') as f:
body = f.read()
f.seek(0)
f.write(text + body)
# add the splat format version header to the file
prepend(outputdir + "SRCID_DENA" + code + ".txt",
"%% SRCID file v20111005" + "\n")
print("")
print(
str(framelength - failure_count) + " of " + str(framelength) +
" points had matching data for station id " + code + ".")
# In[6]:
import sys
sys.path.append(r"C:\Program Files (x86)\ArcGIS\Desktop10.5\arcpy")
sys.path.append(r"C:\Program Files (x86)\ArcGIS\Desktop10.5\bin")
import os
import datetime
import numpy as np
import pandas as pd
import soundDB
import iyore
ds = iyore.Dataset("K:")
import matplotlib.pyplot as plt
# SPLAT_append combines a srcID file output by Flight_Event_to_SRCID with the output of the flight_event_extractor
# script. The srcID file should contain both the output of the Flight_Event_to_SRCID script and the events manually
# annotated in SPLAT.
#
#
# The resulting csv file contains a list of all overflight events with associated flight data, such as flight number, elevation,
# climb/descent rate, ground speed, etc.
#
# example function call: SPLAT_append("C:/overflights","UWBT_overflights.csv","SRCID_DENAUWBT.txt")
#
#
# change display options to make all rows and columns visible for debugging
