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qso_charts.py
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qso_charts.py
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import datetime
import logging
import numpy as np
from matplotlib.dates import DateFormatter, YearLocator, MonthLocator, DayLocator, HourLocator, date2num
import matplotlib.pyplot as plt
import matplotlib.backends.backend_agg as agg
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import shapely.geometry as sgeom
import adif
WIDTH_INCHES = 16
HEIGHT_INCHES = 9
FG = 'k'
BG = 'w'
class QsoChart:
def __init__(self, title='untitled', filename=None, tight_layout=True):
self.title = title
self.filename = filename
self.bin_data = None
self.fig = None
self.ax = None
self.WIDTH_INCHES = 16
self.HEIGHT_INCHES = 9
self.FG = 'k'
self.BG = 'w'
if tight_layout:
self.fig = plt.Figure(figsize=(self.WIDTH_INCHES, self.HEIGHT_INCHES), dpi=100, tight_layout=True)
else:
self.fig = plt.Figure(figsize=(self.WIDTH_INCHES, self.HEIGHT_INCHES), dpi=100)
dts = datetime.datetime.now().strftime('%Y-%m-%d')
self.fig.text(1.0, 0.0, dts, fontsize=12, color='black',
ha='right', va='bottom', transform=self.fig.transFigure)
return
def get_figure(self):
return self.fig
def save_chart(self):
if self.filename is not None:
logging.info(f'writing image file {self.filename}')
canvas = agg.FigureCanvasAgg(self.fig)
canvas.draw()
self.fig.savefig(self.filename, facecolor=BG)
else:
plt.show()
plt.close(self.fig)
class BinnedQSOData:
def __init__(self, first_datetime, last_datetime):
self.offset = int(first_datetime.timestamp())
days = (last_datetime - first_datetime)
self.num_days = days.days + 1
if self.num_days <= 7: # a week
self.bin_size = 3600 # 1 hour
self.num_bins = self.num_days * 24 + 1
self.bin_size = 60 * 30 # 1/2 hour
self.num_bins = self.num_days * 24 * 2 + 1
elif self.num_days <= 28: # a month
self.bin_size = 3600 * 12 # 12 hours
self.num_bins = self.num_days * 2 + 1
elif self.num_days <= 365: # 1 year
self.bin_size = 86400 # 1 day
self.num_bins = self.num_days + 1
elif self.num_days <= 3653: # 10 years
self.bin_size = 86400 * 7 # 7 days
self.num_bins = self.num_days // 7 + 1
elif self.num_days <= 7305: # 20 years
self.bin_size = 86400 * 7 # 7 days
self.num_bins = self.num_days // 7 + 1
else: # > 20 years
self.bin_size = 86400 * 28 # 4 weeks
self.num_bins = self.num_days // 28 + 1
self.data = []
for i in range(self.num_bins):
ts = self.offset + i * self.bin_size
dt = datetime.datetime.utcfromtimestamp(ts)
self.data.append({'datetime': dt})
logging.info(f'num_days = {self.num_days}')
logging.info(f'num_bins = {self.num_bins}')
logging.info(f'offset = {self.offset}')
logging.info(f'bin_size = {self.bin_size}')
def get_bin(self, data_datetime):
ts = int(data_datetime.timestamp())
ts = ts - self.offset
bin_num = ts // self.bin_size
return bin_num
def get_bin_size(self):
return datetime.timedelta(seconds=self.bin_size)
class BinnedQSOChart(QsoChart):
def __init__(self, bin_data, title, filename=None, start_date=None, end_date=None, max_y=0):
super().__init__(title, filename, True)
self.bin_data = bin_data
self.start_date = start_date
self.end_date = end_date
self.maxy = max_y
if start_date is None:
bins_start_date = self.bin_data.data[0].get('datetime')
if bins_start_date is not None:
start_date = bins_start_date.date()
if end_date is None:
bins_end_date = self.bin_data.data[-1].get('datetime')
if bins_end_date is not None:
end_date = bins_end_date.date() + datetime.timedelta(days=1) # get one more day
self.ax = self.fig.add_subplot(111, facecolor=self.BG)
self.ax.set_title(self.title, color=self.FG, size='xx-large', weight='bold')
self.ax.set_xlim(start_date, end_date)
if max_y != 0:
self.ax.set_ylim(0, max_y)
self.ax.grid(True)
self.ax.tick_params(axis='y', colors=FG, which='both', direction='out')
self.ax.tick_params(axis='x', colors=FG, which='both', direction='out', top=False)
self.ax.set_ylabel('QSOs', color=FG, size='x-large', weight='bold')
self.ax.spines['left'].set_color(FG)
self.ax.spines['right'].set_color(FG)
self.ax.spines['top'].set_color(FG)
self.ax.spines['bottom'].set_color(FG)
if self.bin_data.num_days <= 31: # month or less
self.ax.xaxis.set_major_locator(DayLocator())
self.ax.xaxis.set_minor_locator(HourLocator())
self.ax.xaxis.set_major_formatter(DateFormatter('%m-%d'))
elif bin_data.num_bins <= 366: # a year or less
self.ax.xaxis.set_major_locator(MonthLocator())
self.ax.xaxis.set_major_formatter(DateFormatter('%b %y'))
else:
self.ax.xaxis.set_major_locator(YearLocator())
self.ax.xaxis.set_minor_locator(MonthLocator())
self.ax.xaxis.set_major_formatter(DateFormatter('%Y'))
self.ax.set_xlabel('Date', color=FG, size='x-large', weight='bold')
def get_axis(self):
return self.ax
def no_zero(n):
if n == 0:
return None
return n
class QSOsByDateChart(BinnedQSOChart):
def __init__(self, bin_data, title, filename=None, start_date=None, end_date=None):
logging.info(f'drawing QSOsByDateChart "{title}" to {filename}.')
# calculate some data before setting up the chart...
qso_dates = []
data = [[], [], [], []]
biggest = 0
worked = 0
confirmed = 0
challenge = 0
dxcc = 0
for bin_dict in bin_data.data:
bin_date = bin_dict['datetime']
worked = bin_dict['total_worked']
confirmed = bin_dict['total_confirmed']
challenge = bin_dict['total_challenge']
dxcc = bin_dict['total_dxcc']
qso_dates.append(bin_date)
data[0].append(dxcc)
data[1].append(challenge - dxcc)
data[2].append(confirmed - challenge)
data[3].append(worked - confirmed)
if worked > biggest:
biggest = worked
scale_factor = 1000
upper = (biggest // scale_factor + 1) * scale_factor
super().__init__(bin_data, title, filename, start_date, end_date, upper)
plot_dates = date2num(qso_dates)
colors = ['#ffff00', '#ff9933', '#cc6600', '#660000']
labels = [f'{dxcc} dxcc', f'{challenge} challenge', f'{confirmed} confirmed', f'{worked} logged']
self.ax.stackplot(plot_dates, data[0], data[1], data[2], data[3], labels=labels, colors=colors, linewidth=0.2)
self.ax.set_ylabel('QSOs', color=FG, size='x-large', weight='bold')
legend = self.ax.legend(loc='upper left', facecolor=BG, edgecolor=FG)
for text in legend.get_texts():
text.set_color(FG)
self.save_chart()
class DXCCQSOsChart(BinnedQSOChart):
def __init__(self, bin_data, title, filename=None, start_date=None, end_date=None):
logging.info(f'drawing DXCCQSOsChart "{title}" to {filename}.')
# calculate some data before setting up the chart...
dates = []
total_dxcc_data = []
total_challenge_data = []
for bin_dict in bin_data.data:
qso_date = bin_dict['datetime']
dates.append(qso_date)
total_dxcc_data.append(bin_dict['total_dxcc'])
total_challenge_data.append(bin_dict['total_challenge'])
number_dxcc = bin_data.data[-1]['total_dxcc']
number_challenge = bin_data.data[-1]['total_challenge']
plot_dates = date2num(dates)
super().__init__(bin_data, title, filename, start_date, end_date, 0)
axb = self.ax.twinx()
self.ax.set_ylim(0, 350)
axb.set_ylim(0, 3500)
lines1 = self.ax.plot_date(plot_dates, total_dxcc_data,
fmt='r-',
mew=0, markersize=5, label='Current DXCCs ({:d})'.format(number_dxcc))
lines2 = axb.plot_date(plot_dates, total_challenge_data,
fmt='g:',
mew=0, markersize=5, label='Challenge ({:d})'.format(number_challenge))
self.ax.set_ylabel('DXCCs', color='r', size='x-large', weight='bold')
yticks = [0, 50, 100, 150, 200, 250, 300, 331, 340, 350]
labels = ['0', '50', '100', '150', '200', '250', '300', 'Honor Roll', '340', '350']
self.ax.set_yticks(yticks, labels)
self.ax.tick_params(axis='y', colors=FG, which='major', direction='out', right=False, labelcolor='r')
self.ax.tick_params(axis='x', colors=FG, which='both', direction='out', top=False)
axb.set_ylabel('Challenge', color='g', size='x-large', weight='bold')
challenge_ticks = [500, 1000, 1500, 2000, 2500, 3000, 3500]
axb.set_yticks(challenge_ticks)
axb.tick_params(axis='y', colors=FG, which='major', direction='out', left=False, labelcolor='g')
axb.tick_params(axis='y', colors=FG, which='minor', direction='out', left=False, labelcolor='g', pad=-72)
lines = lines1 + lines2
labels = [str(line.get_label()) for line in lines]
legend = self.ax.legend(lines, labels, loc='upper left', numpoints=1, facecolor=BG, edgecolor=FG)
for text in legend.get_texts():
text.set_color(FG)
self.save_chart()
class VuccFfmaQSOsChart(BinnedQSOChart):
def __init__(self, bin_data, title, filename=None, start_date=None, end_date=None):
logging.info(f'drawing VuccFfmaQSOsChart "{title}" to {filename}.')
# calculate some data before setting up the chart...
dates = []
total_vucc_data = []
total_ffma_data = []
for bin_dict in bin_data.data:
qso_date = bin_dict['datetime']
dates.append(qso_date)
total_vucc_data.append(bin_dict['total_vucc'])
total_ffma_data.append(bin_dict['total_ffma'])
number_vucc = bin_data.data[-1]['total_vucc']
number_ffma = bin_data.data[-1]['total_ffma']
plot_dates = date2num(dates)
limit_factor = 500
limit = (int(number_vucc / limit_factor) + 1) * limit_factor
super().__init__(bin_data, title, filename, start_date, end_date, limit)
self.ax.set_ylim(0, limit)
axb = self.ax.twinx()
axb.set_ylim(0, 500) # 488 FFMA grids
lines1 = self.ax.plot_date(plot_dates, total_vucc_data,
fmt='r-',
mew=0, markersize=5, label='Confirmed VUCC QSOs ({:d})'.format(number_vucc))
lines2 = axb.plot_date(plot_dates, total_ffma_data,
fmt='g:',
mew=0, markersize=5, label='Confirmed FFMA QSOs({:d})'.format(number_ffma))
self.ax.tick_params(axis='y', colors=FG, which='major', direction='out', right=False, labelcolor='r')
step = 50 if limit < 1000 else 100
yticks = [i for i in range(0, limit + 1, step)]
self.ax.set_yticks(yticks)
self.ax.set_ylabel('Confirmed VUCC QSOs', color='r', size='x-large', weight='bold')
axb.set_ylabel('Confirmed FFMA QSOs', color='g', size='x-large', weight='bold')
ffma_ticks = [0, 50, 100, 150, 200, 250, 300, 350, 400, 450, 488]
ffma_tick_labels = ['0', '50', '100', '150', '200', '250', '300', '350', '400', '450', 'FFMA 488']
axb.tick_params(axis='y', colors=FG, which='major', direction='out', left=False, labelcolor='g')
axb.set_yticks(ffma_ticks, ffma_tick_labels)
axb.tick_params(axis='y', colors=FG, which='minor', direction='out', left=False, labelcolor='g', pad=-72)
lines = lines1 + lines2
labels = [str(line.get_label()) for line in lines]
legend = self.ax.legend(lines, labels, loc='upper left', numpoints=1, facecolor=BG, edgecolor=FG)
for text in legend.get_texts():
text.set_color(FG)
self.save_chart()
class ChallengeBandsByDateChart(BinnedQSOChart):
def __init__(self, bin_data, title, filename=None, start_date=None, end_date=None):
logging.info(f'drawing ChallengeBandsByDateChart "{title}" to {filename}.')
# calculate some data before setting up the chart...
challenge_bands = ['160M', '80M', '40M', '30M', '20M', '17M', '15M', '12M', '10M', '6M']
colors = ['r', 'g', 'b', 'c', 'r', '#990099', '#ff6600', '#00ff00', '#663300', '#00ff99']
line_styles = [':', '--', '--', '-', '--', ':', '--', ':', '--', '--']
data = [[], [], [], [], [], [], [], [], [], [], []]
totals = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
biggest = 0
for bin_dict in bin_data.data:
bin_date = bin_dict['datetime']
data[0].append(bin_date)
for i in range(0, len(challenge_bands)):
totals[i] += bin_dict['challenge_' + challenge_bands[i]]
if totals[i] > biggest:
biggest = totals[i]
data[i + 1].append(totals[i])
scale_factor = 50
y_end = (int(biggest / scale_factor) + 1) * scale_factor
plot_dates = date2num(data[0])
super().__init__(bin_data, title, filename, start_date, end_date, 0)
self.ax.set_ylim(0, y_end)
step = scale_factor # 50 if y_end < 1000 else 100
yticks = [i for i in range(0, y_end + 1, step)]
self.ax.set_yticks(yticks)
for i in range(0, len(challenge_bands)):
self.ax.plot_date(plot_dates, data[i + 1],
color=colors[i],
fmt=line_styles[i],
mew=0, markersize=5, label='{:s} ({:d})'.format(challenge_bands[i], totals[i]))
legend = self.ax.legend(loc='upper left', numpoints=1, facecolor=BG, edgecolor=FG)
for text in legend.get_texts():
text.set_color(FG)
self.save_chart()
class QSOsRateChart(BinnedQSOChart):
def __init__(self, bin_data, title, filename=None, start_date=None, end_date=None):
logging.info(f'drawing QSOsRateChart "{title}" to {filename}.')
# calculate some data before setting up the chart...
plot_dates = []
data = [[], [], [], []]
plot_widths = []
maxy = 0
for bin_dict in bin_data.data:
bin_date = bin_dict['datetime'].date()
if (start_date is None or bin_date >= start_date) and (end_date is None or bin_date <= end_date):
# compute stacked bar sizes
new_dxcc = bin_dict['new_dxcc']
challenge = bin_dict['challenge'] - bin_dict['new_dxcc']
confirmed = bin_dict['confirmed'] - bin_dict['challenge']
worked = bin_dict['worked'] - bin_dict['confirmed']
plot_dates.append(np.datetime64(bin_date))
data[0].append(new_dxcc)
data[1].append(challenge)
data[2].append(confirmed)
data[3].append(worked)
plot_widths = np.timedelta64(bin_data.bin_size, 's')
for i in range(0, len(data[0])):
total = data[0][i] + data[1][i] + data[2][i] + data[3][i]
if total > maxy:
maxy = total
super().__init__(bin_data, title, filename, start_date, end_date, 0)
offsets = np.zeros((len(plot_dates)), np.int32)
colors = ['#ff3333', '#cccc00', '#009900', '#000099']
labels = ['Logged', 'Confirmed', 'Challenge', 'DXCC Entity']
d = np.array(data[0])
self.ax.bar(plot_dates, d, plot_widths, bottom=offsets, color=colors[0], label=labels[3])
offsets += d
d = np.array(data[1])
self.ax.bar(plot_dates, d, plot_widths, bottom=offsets, color=colors[1], label=labels[2])
offsets += d
d = np.array(data[2])
self.ax.bar(plot_dates, d, plot_widths, bottom=offsets, color=colors[2], label=labels[1])
offsets += d
d = np.array(data[3])
self.ax.bar(plot_dates, d, plot_widths, bottom=offsets, color=colors[3], label=labels[0])
legend = self.ax.legend(loc='upper left', numpoints=1, facecolor=BG, edgecolor=FG)
for text in legend.get_texts():
text.set_color(FG)
self.save_chart()
class QSOsByBandRateChart(BinnedQSOChart):
def __init__(self, bin_data, title, filename=None, start_date=None, end_date=None):
logging.info(f'drawing QSOsByBandRateChart "{title}" to {filename}.')
# calculate some data before setting up the chart...
challenge_bands = ['160M', '80M', '40M', '30M', '20M', '17M', '15M', '12M', '10M', '6M']
colors = ['violet', 'g', 'b', 'c', 'r', '#ffff00', '#ff6600', '#00ff00', '#663300', '#00ffff']
data = [[], [], [], [], [], [], [], [], [], []]
plot_dates = []
plot_widths = []
for bin_dict in bin_data.data:
bin_date = bin_dict['datetime'].date()
if (start_date is None or bin_date >= start_date) and (end_date is None or bin_date <= end_date):
plot_dates.append(np.datetime64(bin_date))
plot_widths.append(np.timedelta64(bin_data.bin_size, 's'))
for i in range(0, len(challenge_bands)):
band_count = bin_dict[challenge_bands[i]]
data[i].append(band_count)
maxy = 0
for i in range(0, len(data[0])):
total = 0
for j in range(0, len(challenge_bands)):
total += data[j][i]
if total > maxy:
maxy = total
super().__init__(bin_data, title, filename, start_date, end_date, maxy)
offset = np.zeros((len(plot_dates)), dtype=np.int32)
for i in range(0, len(challenge_bands)):
ta = np.array(data[i])
self.ax.bar(plot_dates, ta, width=plot_widths, bottom=offset, color=colors[i], label=challenge_bands[i])
# ax.bar(dates, ta, bottom=offset, color=colors[i], label=challenge_bands[i])
offset += ta
legend = self.ax.legend(loc='upper left', numpoints=1, facecolor=BG, edgecolor=FG)
for text in legend.get_texts():
text.set_color(FG)
self.save_chart()
class QSOsByModeRateChart(BinnedQSOChart):
def __init__(self, bin_data, title, filename=None, start_date=None, end_date=None):
logging.info(f'drawing QSOsByModeRateChart "{title}" to {filename}.')
# calculate some data before setting up the chart...
colors = ['r', 'g', 'c', 'b']
data = [[], [], [], []]
plot_dates = []
plot_widths = []
for bin_dict in bin_data.data:
bin_date = bin_dict['datetime'].date()
if (start_date is None or bin_date >= start_date) and (end_date is None or bin_date <= end_date):
plot_dates.append(np.datetime64(bin_date))
plot_widths.append(np.timedelta64(bin_data.bin_size, 's'))
for i in range(0, len(adif.MODES)):
mode_count = bin_dict[adif.MODES[i]]
data[i].append(mode_count)
maxy = 0
for i in range(0, len(data[0])):
total = 0
for j in range(0, len(adif.MODES)):
total += data[j][i]
if total > maxy:
maxy = total
super().__init__(bin_data, title, filename, start_date, end_date, maxy)
offset = np.zeros((len(plot_dates)), dtype=np.int32)
for i in range(0, len(adif.MODES)):
ta = np.array(data[i])
self.ax.bar(plot_dates, ta, plot_widths, bottom=offset, color=colors[i], label=adif.MODES[i])
offset += ta
legend = self.ax.legend(loc='upper left', numpoints=1, facecolor=BG, edgecolor=FG)
for text in legend.get_texts():
text.set_color(FG)
self.save_chart()
def grid_square_box(grid):
grid = grid.upper()
ord_A = ord('A')
ord_0 = ord('0')
lon = (ord(grid[0]) - ord_A) * 20
lon += (ord(grid[2]) - ord_0) * 2
lat = (ord(grid[1]) - ord_A) * 10
lat += (ord(grid[3]) - ord_0)
lon -= 180
lat -= 90
return sgeom.box(lon, lat, lon + 2, lat + 1)
class QSOsMap(QsoChart):
def __init__(self, qsos, title, filename=None, start_date=None, end_date=None, confirmed_only=True):
logging.info(f'drawing QSOsMap "{title}" to {filename}.')
super().__init__(title, filename, tight_layout=False)
grids = {}
most = 0
for qso in qsos:
if start_date is not None:
qso_date_string = qso.get('qso_date')
qso_date = datetime.datetime.strptime(qso_date_string, '%Y%m%d').date()
if qso_date < start_date or qso_date >= end_date:
continue
qsl_received = (qso.get('qsl_rcvd') or 'N').lower()
if not confirmed_only or qsl_received != 'n':
grid = qso.get('gridsquare')
if grid is not None:
if qsl_received == 'n':
logging.info('QSO has grid but is not confirmed.')
grid = grid[0:4].upper()
if grid not in grids:
grids[grid] = 0
grids[grid] += 1
if grids[grid] > most:
most = grids[grid]
projection = ccrs.PlateCarree(central_longitude=-110)
# noinspection PyTypeChecker
ax = self.fig.add_axes((0, 0, 1, 1), projection=projection)
ax.set_title(title, color=self.FG, size='xx-large', weight='bold')
# ax.stock_img()
ax.add_feature(cfeature.LAND, color='white')
ax.add_feature(cfeature.OCEAN, color='#afdfef')
ax.add_feature(cfeature.LAKES, color='#afdfef')
ax.add_feature(cfeature.COASTLINE, linewidth=0.5)
ax.add_feature(cfeature.BORDERS, linewidth=0.5)
# geographic lines: add international date line, equator, etc.
map_lines = cfeature.NaturalEarthFeature(
category='physical',
name='geographic_lines',
scale='110m',
facecolor='none',
edgecolor='black',
linewidth=0.5
)
ax.add_feature(map_lines)
color_palette = ['#0b0089', '#4100a0', '#6500aa', '#8500aa', '#a4109c', '#c03486',
'#cf4875', '#e3615f', '#f28047', '#fb9b30', '#ffb804', '#fbdc00', '#f0fb00',
]
num_colors = len(color_palette)
scale = most / num_colors
scale = max(scale, 1)
for grid in grids.keys():
if len(grid) >= 4:
box = grid_square_box(grid)
count = grids[grid]
index = int(count / scale)
index = min(index, num_colors - 1)
clr = color_palette[index]
ax.add_geometries([box], ccrs.PlateCarree(), alpha=0.5, facecolor=clr, edgecolor=clr, linewidth=0)
self.save_chart()