def maps(request):
# Get info from form
search_info = request.session['cleaned_data']
if "new_callsign" in request.session.keys():
request.session['cleaned_data']['callsign'] = request.session[
'new_callsign']
# Retrieve contest object from pickle file
contest = retrieve_contest_object(search_info=search_info,
output_folder=output_folder)
# Get keys from link
options = ""
options_str = ""
if request.GET.get('options'):
options = str(request.GET.get('options')).split(",")
else:
if request.GET.get('band'):
options += "band%s," % str(request.GET.get('band'))
if request.GET.get('continent'):
options += "continent%s," % str(request.GET.get('continent'))
if request.GET.get('fromto'):
fromto = str(request.GET.get('fromto'))
options += "from%s,to%s," % (fromto[0:4], fromto[4:8])
options = options[:-1].split(",")
list_calls = None
extra_conditions = (contest.log["band"] > 0)
for opt in options:
if "band" in opt:
options_str = opt + ","
band = int(opt.replace("band", ""))
extra_conditions &= (contest.log["band"] == band)
if "from" in opt:
time_from = str(opt.replace("from", ""))
extra_conditions &= (contest.log["time"] >= time_from)
if "to" in opt:
time_to = str(opt.replace("to", ""))
extra_conditions &= (contest.log["time"] <= time_to)
list_calls = contest.log[extra_conditions][[
"call", "latitude", "longitude"
]].dropna().values.tolist()
list_calls.sort()
list_calls_unique = list(k for k, _ in itertools.groupby(list_calls))
calls = list(k[0] for k in list_calls_unique)
lat = list(k[1] for k in list_calls_unique)
lon = list(k[2] for k in list_calls_unique)
return render(
request, 'analysis_maps.html', {
'nbar': 'maps',
'latbar': 'maps',
'list_calls': zip(calls, lat, lon),
'mylat': contest.log["mylatitude"].iloc[0],
'mylon': contest.log["mylongitude"].iloc[0],
'old_options': options_str
})
def contest_rates(request):
# --- Get info from form
search_info = request.session['cleaned_data']
if "new_callsign" in request.session.keys():
request.session['cleaned_data']['callsign'] = request.session[
'new_callsign']
# --- Retrieve contest object from pickle file
contest = retrieve_contest_object(search_info=search_info,
output_folder=output_folder)
rates = contest.max_rates
rates_info = []
rates_info.append([
"1", rates["1min"][0], rates["1min"][0] / 1.,
rates["1min"][0] * 60. / 1.,
str(rates["1min"][1][0]),
str(rates["1min"][1][1])
])
rates_info.append([
"5", rates["5min"][0], rates["5min"][0] / 5.,
rates["5min"][0] * 60. / 5.,
str(rates["5min"][1][0]),
str(rates["5min"][1][1])
])
rates_info.append([
"10", rates["10min"][0], rates["10min"][0] / 10.,
rates["10min"][0] * 60. / 10.,
str(rates["10min"][1][0]),
str(rates["10min"][1][1])
])
rates_info.append([
"30", rates["30min"][0], rates["30min"][0] / 30.,
rates["30min"][0] * 60. / 30.,
str(rates["30min"][1][0]),
str(rates["30min"][1][1])
])
rates_info.append([
"60", rates["60min"][0], rates["60min"][0] / 60.,
rates["60min"][0] * 60. / 60.,
str(rates["60min"][1][0]),
str(rates["60min"][1][1])
])
rates_info.append([
"120", rates["120min"][0], rates["120min"][0] / 120.,
rates["120min"][0] * 60. / 120.,
str(rates["120min"][1][0]),
str(rates["120min"][1][1])
])
return render(request, 'analysis_rates.html', {
'rates_info': rates_info,
'nbar': 'rates'
})
def main_page(request):
# --- Get info from form
search_info = request.session['cleaned_data']
if "new_callsign" in request.session.keys():
request.session['cleaned_data']['callsign'] = request.session[
'new_callsign']
# --- Retrieve contest object from pickle file
contest = retrieve_contest_object(search_info=search_info,
output_folder=output_folder)
return render(request, 'analysis_main.html', {
'contest': contest,
'nbar': 'main'
})
def contest_rates_per_minute(request):
# Get info from form
search_info = request.session['cleaned_data']
if "new_callsign" in request.session.keys():
request.session['cleaned_data']['callsign'] = request.session[
'new_callsign']
# Retrieve contest object from pickle file
contest = retrieve_contest_object(search_info=search_info,
output_folder=output_folder)
list_rates = contest.ratesPerMinute
range_mins = []
for i in range(60):
range_mins.append(str(i).zfill(2))
days = list(contest.log.groupby("date").groups.keys())
days.sort()
range_hours = []
for i in range(24):
range_hours.append(str(i).zfill(2))
range_hours = range_hours * len(days)
range_days = []
for d in days:
range_days += [d] * 24
# --- list_rates is a list made of 48 sub-lists. Each sub-list has 60 rates, for each minute in each hour of the
# contest. Now we will convert each rate in a list of [min, rate]
list_rates_min = []
for h, lh in enumerate(list_rates):
list_rates_min.append([])
for m, lm in enumerate(lh):
list_rates_min[h].append([str(m).zfill(2), lm])
return render(
request, 'analysis_rate_per_min.html', {
'list_rates': zip(range_days, range_hours, list_rates_min),
'range_mins': range_mins,
'nbar': 'rates'
})
def contest_plots(request):
# Get info from form
search_info = request.session['cleaned_data']
if "new_callsign" in request.session.keys():
request.session['cleaned_data']['callsign'] = request.session[
'new_callsign']
# Retrieve contest object from pickle file
contest = retrieve_contest_object(search_info=search_info,
output_folder=output_folder)
# Get keys from link
plot_key = "dummie"
if request.GET.get('chart'):
plot_key = str(request.GET.get('chart'))
options = ""
if request.GET.get('options'):
options = str(request.GET.get('options'))
else:
if request.GET.get('band'):
options += "band%s," % str(request.GET.get('band'))
if request.GET.get('continent'):
options += "continent%s," % str(request.GET.get('continent'))
if request.GET.get('station_type'):
options += "%s," % str(request.GET.get('station_type'))
if request.GET.get('avg'):
options += "avg%s," % str(request.GET.get('avg'))
if request.GET.get('fromto'):
fromto = str(request.GET.get('fromto'))
options += "from%s,to%s," % (fromto[0:4], fromto[4:8])
options = options[:-1]
# Generate code to inject to html
plot_dict = plot_dictionary
plot_snippet = ""
for plot in plot_dict.names():
if plot == plot_key:
plot_snippet = plot_dict.plots()[plot_key].do_plot(contest=contest,
doSave=True,
options=options)
# Mark active block in html
nbar = ""
if plot_key == 'plot_qsos_vs_time__band':
nbar = "rates"
if plot_key == 'plot_qsos_vs_time__continent':
nbar = "rates"
if plot_key == 'plot_qsos_vs_time__stationtype':
nbar = "rates"
if plot_key == 'plot_fraction_stationtype':
nbar = "operation"
if plot_key == 'plot_ratio_qsos_min':
nbar = "rates"
if plot_key == 'plot_mults_vs_qsos':
nbar = "operation"
if plot_key == 'plot_time_vs_band_vs_continent':
nbar = "rates"
if plot_key == 'plot_freq_vs_date':
nbar = "operation"
if plot_key == 'plot_lenghtcallmorse':
nbar = "morse"
if plot_key == 'plot_heading':
nbar = "operation"
if plot_key == 'plot_db_vs_date':
nbar = "operation"
if plot_key == 'plot_cwspeed':
nbar = "morse"
if plot_key == 'plot_cwsignal':
nbar = "morse"
#--- Lateral bar
latbar = ""
if "plot_qsos_vs_time__band" in plot_key:
latbar = "qsos_vs_time__band"
if "plot_ratio_qsos_min" in plot_key:
latbar = "ratio_qsos_min"
if "plot_heading" in plot_key:
latbar = "heading"
if "plot_db_vs_date" in plot_key:
latbar = "db_vs_time"
if plot_key == 'plot_cwspeed':
latbar = "cwspeed"
# Old options to retain
old_options = ""
for opt in options.split(","):
if "plot_heading" in plot_key:
if "from" in opt:
old_options += opt + ","
if "to" in opt:
old_options += opt + ","
if "plot_db_vs_date" in plot_key:
if "continent" in opt:
old_options += opt + ","
if "avg" in opt:
old_options += opt + ","
return render(
request, 'analysis_images.html', {
"plot_snippet": plot_snippet,
'nbar': nbar,
'latbar': latbar,
'old_options': old_options
})
def contest_dxcc_frequency(request):
# --- Get info from form
search_info = request.session['cleaned_data']
if "new_callsign" in request.session.keys():
request.session['cleaned_data']['callsign'] = request.session[
'new_callsign']
# --- Retrieve contest object from pickle file
contest = retrieve_contest_object(search_info=search_info,
output_folder=output_folder)
qsos_page = 10
log = contest.log
cumulated_info = []
if request.GET.get('filter'):
rule = str(request.GET['filter']).split(",")
for r in rule:
if "band" in r:
band = int(r.replace("band:", ""))
log = log[log["band"] == band]
cumulated_info.append(r)
if 'date' in r:
date = str(r.replace("date:", ""))
log = log[log["date"] == date]
cumulated_info.append(r)
if 'time' in r:
time = str(r.replace("time:", ""))
log = log[log["time"] == time]
cumulated_info.append(r)
if 'dxcc' in r:
dxcc = str(r.replace("dxcc:", ""))
log = log[log["dxcc"] == dxcc]
cumulated_info.append(r)
cumulated_info = ','.join(cumulated_info)
page = 1
if request.GET.get('filter'):
rule = str(request.GET['filter']).split(",")
for r in rule:
if "page" in r:
page = int(r.replace("page:", ""))
grouped_counts = log.groupby("dxcc")["dxcc"].count()
counts = grouped_counts.tolist()
names = grouped_counts.index.tolist()
num_pages = []
filtered_length = len(grouped_counts)
for i in range(1, int(round(filtered_length / float(qsos_page), 0) + 1)):
num_pages.append(i)
list_dxcc = []
for n, c in zip(names, counts):
list_dxcc.append([n, c])
from operator import itemgetter
list_dxcc = sorted(list_dxcc, key=itemgetter(1))
list_dxcc = list(reversed(list_dxcc))
list_dxcc = list_dxcc[(page - 1) * qsos_page:page * qsos_page]
return render(
request, 'analysis_dxccfreq.html', {
'list_dxcc': list_dxcc,
'page': page,
'num_pages': num_pages,
'total_pages': len(num_pages),
'nbar': 'log'
})
def contest_log(request):
# --- Get info from form
search_info = request.session['cleaned_data']
if "new_callsign" in request.session.keys():
request.session['cleaned_data']['callsign'] = request.session[
'new_callsign']
# --- Retrieve contest object from pickle file
contest = retrieve_contest_object(search_info=search_info,
output_folder=output_folder)
qsos_page = 50
log = contest.log
cumulated_info = []
if request.GET.get('filter'):
rule = str(request.GET['filter']).split(",")
for r in rule:
if "band" in r:
band = int(r.replace("band:", ""))
log = log[log["band"] == band]
cumulated_info.append(r)
if 'call' in r:
call = str(r.replace("call:", ""))
log = log[log["call"] == call]
cumulated_info.append(r)
if 'freq' in r:
freq = float(r.replace("freq:", ""))
log = log[log["frequency"] == freq]
cumulated_info.append(r)
if 'date' in r:
date = str(r.replace("date:", ""))
log = log[log["date"] == date]
cumulated_info.append(r)
if 'time' in r:
time = str(r.replace("time:", ""))
log = log[log["time"] == time]
cumulated_info.append(r)
if 'cont' in r:
cont = str(r.replace("cont:", ""))
log = log[log["continent"] == cont]
cumulated_info.append(r)
if 'dxcc' in r:
dxcc = str(r.replace("dxcc:", ""))
log = log[log["dxcc"] == dxcc]
cumulated_info.append(r)
if 'cq' in r:
zonecq = int(r.replace("cq:", ""))
log = log[log["zonecq"] == zonecq]
cumulated_info.append(r)
if 'points' in r:
points = int(r.replace("points:", ""))
log = log[log["points"] == points]
cumulated_info.append(r)
if 'maxRate_1min' in r:
log = log[log["maxRate_1min"] == 1]
cumulated_info.append(r)
if 'maxRate_5min' in r:
log = log[log["maxRate_5min"] == 1]
cumulated_info.append(r)
if 'maxRate_10min' in r:
log = log[log["maxRate_10min"] == 1]
cumulated_info.append(r)
if 'maxRate_30min' in r:
log = log[log["maxRate_30min"] == 1]
cumulated_info.append(r)
if 'maxRate_60min' in r:
log = log[log["maxRate_60min"] == 1]
cumulated_info.append(r)
if 'maxRate_120min' in r:
log = log[log["maxRate_120min"] == 1]
cumulated_info.append(r)
cumulated_info = ','.join(cumulated_info)
cumulated_unique_band = []
if request.GET.get('unique_band'):
rule = str(request.GET['unique_band']).split(",")
for r in rule:
if 'call' in r:
log = log.groupby(["call", "band"], sort=False,
as_index=False).first()
cumulated_unique_band.append(r)
if 'freq' in r:
log = log.groupby(["frequency", "band"],
sort=False,
as_index=False).first()
cumulated_unique_band.append(r)
if 'date' in r:
log = log.groupby(["date", "band"], sort=False,
as_index=False).first()
cumulated_unique_band.append(r)
if 'time' in r:
log = log.groupby(["time", "band"], sort=False,
as_index=False).first()
cumulated_unique_band.append(r)
if 'cont' in r:
log = log.groupby(["continent", "band"],
sort=False,
as_index=False).first()
cumulated_unique_band.append(r)
if 'dxcc' in r:
log = log.groupby(["dxcc", "band"], sort=False,
as_index=False).first()
cumulated_unique_band.append(r)
if 'cq' in r:
log = log.groupby(["zonecq", "band"],
sort=False,
as_index=False).first()
cumulated_unique_band.append(r)
cumulated_unique_band = ','.join(cumulated_unique_band)
cumulated_unique = []
if request.GET.get('unique'):
rule = str(request.GET['unique']).split(",")
for r in rule:
if "band" in r:
log = log.groupby(["band"], sort=False, as_index=False).first()
cumulated_unique.append(r)
if 'call' in r:
log = log.groupby(["call"], sort=False, as_index=False).first()
cumulated_unique.append(r)
if 'freq' in r:
log = log.groupby(["frequency"], sort=False,
as_index=False).first()
cumulated_unique.append(r)
if 'date' in r:
log = log.groupby(["date"], sort=False, as_index=False).first()
cumulated_unique.append(r)
if 'time' in r:
log = log.groupby(["time"], sort=False, as_index=False).first()
cumulated_unique.append(r)
if 'cont' in r:
log = log.groupby(["continent"], sort=False,
as_index=False).first()
cumulated_unique.append(r)
if 'dxcc' in r:
log = log.groupby(["dxcc"], sort=False, as_index=False).first()
cumulated_unique.append(r)
if 'cq' in r:
log = log.groupby(["zonecq"], sort=False,
as_index=False).first()
cumulated_unique.append(r)
cumulated_unique = ','.join(cumulated_unique)
filtered_length = len(log)
page = 1
if request.GET.get('filter'):
rule = str(request.GET['filter']).split(",")
for r in rule:
if "page" in r:
page = int(r.replace("page:", ""))
log = log[(page - 1) * qsos_page:page * qsos_page]
num_pages = []
for i in range(1, int(round(filtered_length / float(qsos_page), 0) + 1)):
num_pages.append(i)
log_info = []
for index, row in log.iterrows():
log_info.append([
row["counter"],
row["band"],
row["frequency"],
row["date"],
row["time"],
row["call"],
row["continent"],
row["dxcc"],
row["zonecq"],
row["points"],
])
return render(
request, 'analysis_log.html', {
"log_info": log_info,
'cumulated_info': cumulated_info,
'cumulated_unique': cumulated_unique,
'cumulated_unique_band': cumulated_unique_band,
'page': page,
'num_pages': num_pages,
'total_pages': len(num_pages),
'nbar': 'log',
'latbar': 'log'
})
def contest_summary(request):
# Get info from form
search_info = request.session['cleaned_data']
if "new_callsign" in request.session.keys():
request.session['cleaned_data']['callsign'] = request.session[
'new_callsign']
# Retrieve contest object from pickle file
contest = retrieve_contest_object(search_info=search_info,
output_folder=output_folder)
summary_info = []
summary_info_total = []
qsos_cumul = 0
dxcc_cumul = 0
zones_cumul = 0
points_cumul = 0
for band in [10, 15, 20, 40, 80, 160]:
qsos = contest.log[(contest.log["isdupe"] == False)
& (contest.log["band"] == band)]["call"].count()
dxcc = contest.log[(contest.log["isdupe"] == False) & (
contest.log["band"] == band)]["dxcc"].value_counts().count()
zones = contest.log[(contest.log["isdupe"] == False) & (
contest.log["band"] == band)]["mynr"].value_counts().count()
points = contest.log[(contest.log["isdupe"] == False)
& (contest.log["band"] == band)]["points"].sum()
qsos_cumul += qsos
dxcc_cumul += dxcc
zones_cumul += zones
points_cumul += points
if qsos > 0:
summary_info.append([
band,
qsos,
dxcc,
zones,
points,
float(points) / qsos,
])
else:
summary_info.append([
band,
qsos,
dxcc,
zones,
points,
0.,
])
summary_info_total.append([
"Total", qsos_cumul, dxcc_cumul, zones_cumul, points_cumul,
float(points_cumul) / qsos_cumul,
(zones_cumul + dxcc_cumul) * points_cumul
])
return render(
request, 'analysis_summary.html', {
'summary_info': summary_info,
'summary_info_total': summary_info_total,
'nbar': 'summary'
})
