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Verified Commit 15412d46 authored by Owen Graham's avatar Owen Graham
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Refactor plotters into classes

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visualizer/plotting.py
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− 157
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"""Plotting functions."""
from dataclasses import make_dataclass
from io import BytesIO
from types import SimpleNamespace
......@@ -17,170 +16,179 @@ plt.style.use('ggplot')
plt.rcParams['axes.xmargin'] = 0
matplotlib.use('Agg')
Plotter = make_dataclass('Plotter', ['name', 'nav_title', 'plot'])
plotters = {}
class Plotter:
"""Parent of plotter classes."""
def add_plotter(name, nav_title):
"""Decorator to register a plot type."""
def decorator(f):
plotters[name] = Plotter(name, nav_title, f)
return f
return decorator
@add_plotter('time-series', 'Time Series')
def plot_time_series():
class TimeSeries(Plotter):
"""Plot one station/year/measurement."""
station_id = get_param('station')
year = get_param('year', to=year_type)
meas = get_param('measurement', to=meas_type)
station = get_station(station_id)
data = read_data(station, year)
fig, axes = plt.subplots()
fig.set_figheight(6)
fig.set_figwidth(12)
axes.plot(data[:, 0], data[:, meas.field])
avg = np.nanmean(data[:, meas.field], dtype='float32')
axes.hlines(y=avg,
xmin=data[:, 0][0],
xmax=data[:, 0][-1],
linestyle='-',
alpha=0.7)
axes.set_ylabel(meas.title)
axes.grid(True)
maximum = max(data, key=lambda row: row[meas.field])
minimum = min(data, key=lambda row: row[meas.field])
axes.set_title(
(f'Max {meas.title}: {maximum[meas.field]}, Date: ({maximum[0]}). '
f'Min {meas.title}: {minimum[meas.field]}, Date: ({minimum[0]}).'),
fontsize='small',
)
name = station['name']
plt.suptitle(f'{meas.title} measurements, {name} Station, '
f'{data[0][0].year}')
return savefig_response(
fig,
filename=f'time-series.{station_id}.{year}.{meas.url_name}.png',
)
@add_plotter('overlay', 'Overlay')
def plot_overlay():
"""Plot two station/years @ one measurement."""
num_datasets = 2
datasets = tuple(SimpleNamespace() for _ in range(num_datasets))
stations = read_stations()
for n, dset in enumerate(datasets, start=1):
dset.station_id = get_param(f'station{n}')
dset.year = get_param(f'year{n}', to=year_type)
dset.station = get_station(dset.station_id, stations=stations)
dset.name = dset.station['name']
meas = get_param('measurement', to=meas_type)
def ignore_feb_29(rows):
return [row for row in rows if (row[0].month, row[0].day) != (2, 29)]
for dset in datasets:
raw_data = read_data(dset.station, dset.year)
dset.data = np.array(ignore_feb_29(raw_data))
fig, axes = plt.subplots()
fig.set_figheight(6)
fig.set_figwidth(12)
for i, dset in enumerate(datasets):
alpha_kw = {'alpha': 0.6} if i else {}
axes.plot(datasets[0].data[:, 0],
dset.data[:, meas.field],
**alpha_kw,
label=f'{dset.name} {dset.data[0][0].year}')
for dset in datasets:
dset.avg = np.nanmean(dset.data[:, meas.field], dtype='float32')
axes.hlines(y=dset.avg,
xmin=datasets[0].data[:, 0][0],
xmax=datasets[0].data[:, 0][-1],
alpha=0.7,
label=f'Avg {dset.name} {dset.data[0][0].year}')
axes.set_ylabel(meas.title)
for dset in datasets:
dset.max = max(dset.data, key=lambda row: row[meas.field])
dset.min = min(dset.data, key=lambda row: row[meas.field])
max_dset = max(datasets, key=lambda dset: dset.max[meas.field])
min_dset = min(datasets, key=lambda dset: dset.min[meas.field])
axes.grid(True)
axes.set_title((f'Max {meas.title}: {max_dset.max[meas.field]}, '
f'{max_dset.name} Station, Date: ({max_dset.max[0]}). '
f'Min {meas.title}: {min_dset.min[meas.field]}, '
f'{min_dset.name} Station, Date: ({min_dset.min[0]}).'),
fontsize='small')
axes.legend()
axes.tick_params(labelbottom=False)
title_dsets = ' / '.join(f'{dset.name} Station, {dset.data[0][0].year}'
for dset in datasets)
plt.suptitle(f'{meas.title} measurements, {title_dsets}')
filename_dsets = '.'.join(f'{dset.station_id}.{dset.year}'
for dset in datasets)
return savefig_response(
fig,
filename=f'overlay.{filename_dsets}.{meas.url_name}.png',
)
@add_plotter('boxplot', 'Boxplot')
def plot_boxplot():
"""Boxplot one station/measurement @ multiple years."""
station_id = get_param('station')
year1 = get_param('year1', to=year_type)
year2 = get_param('year2', to=year_type)
meas = get_param('measurement', to=meas_type)
station = get_station(station_id)
plot_data = []
name = 'time-series'
nav_title = 'Time Series'
start_year, end_year = sorted([year1, year2])
years = range(start_year, end_year + 1)
maximum = minimum = None
@classmethod
def plot(cls):
station_id = get_param('station')
year = get_param('year', to=year_type)
meas = get_param('measurement', to=meas_type)
station = get_station(station_id)
data = read_data(station, year)
fig, axes = plt.subplots()
fig.set_figheight(6)
fig.set_figwidth(12)
axes.plot(data[:, 0], data[:, meas.field])
avg = np.nanmean(data[:, meas.field], dtype='float32')
axes.hlines(y=avg,
xmin=data[:, 0][0],
xmax=data[:, 0][-1],
linestyle='-',
alpha=0.7)
axes.set_ylabel(meas.title)
axes.grid(True)
maximum = max(data, key=lambda row: row[meas.field])
minimum = min(data, key=lambda row: row[meas.field])
axes.set_title(
(f'Max {meas.title}: {maximum[meas.field]}, Date: ({maximum[0]}). '
f'Min {meas.title}: {minimum[meas.field]}, '
f'Date: ({minimum[0]}).'),
fontsize='small',
)
name = station['name']
plt.suptitle(f'{meas.title} measurements, {name} Station, '
f'{data[0][0].year}')
return savefig_response(fig, filename=(
f'{cls.name}.{station_id}.{year}.{meas.url_name}.png'
))
class Overlay(Plotter):
"""Plot two station/years @ one measurement."""
def at_index(row):
"""Get the selected field of `row`."""
return row[meas.field]
name = 'overlay'
nav_title = 'Overlay'
@classmethod
def plot(cls):
num_datasets = 2
datasets = tuple(SimpleNamespace() for _ in range(num_datasets))
stations = read_stations()
for n, dset in enumerate(datasets, start=1):
dset.station_id = get_param(f'station{n}')
dset.year = get_param(f'year{n}', to=year_type)
dset.station = get_station(dset.station_id, stations=stations)
dset.name = dset.station['name']
meas = get_param('measurement', to=meas_type)
def ignore_feb_29(rows):
return [row for row in rows
if (row[0].month, row[0].day) != (2, 29)]
for dset in datasets:
raw_data = read_data(dset.station, dset.year)
dset.data = np.array(ignore_feb_29(raw_data))
fig, axes = plt.subplots()
fig.set_figheight(6)
fig.set_figwidth(12)
for i, dset in enumerate(datasets):
alpha_kw = {'alpha': 0.6} if i else {}
axes.plot(datasets[0].data[:, 0],
dset.data[:, meas.field],
**alpha_kw,
label=f'{dset.name} {dset.data[0][0].year}')
for dset in datasets:
dset.avg = np.nanmean(dset.data[:, meas.field], dtype='float32')
axes.hlines(y=dset.avg,
xmin=datasets[0].data[:, 0][0],
xmax=datasets[0].data[:, 0][-1],
alpha=0.7,
label=f'Avg {dset.name} {dset.data[0][0].year}')
axes.set_ylabel(meas.title)
for dset in datasets:
dset.max = max(dset.data, key=lambda row: row[meas.field])
dset.min = min(dset.data, key=lambda row: row[meas.field])
max_dset = max(datasets, key=lambda dset: dset.max[meas.field])
min_dset = min(datasets, key=lambda dset: dset.min[meas.field])
axes.grid(True)
axes.set_title(
(f'Max {meas.title}: {max_dset.max[meas.field]}, '
f'{max_dset.name} Station, Date: ({max_dset.max[0]}). '
f'Min {meas.title}: {min_dset.min[meas.field]}, '
f'{min_dset.name} Station, Date: ({min_dset.min[0]}).'),
fontsize='small')
axes.legend()
axes.tick_params(labelbottom=False)
title_dsets = ' / '.join(f'{dset.name} Station, {dset.data[0][0].year}'
for dset in datasets)
plt.suptitle(f'{meas.title} measurements, {title_dsets}')
filename_dsets = '.'.join(f'{dset.station_id}.{dset.year}'
for dset in datasets)
return savefig_response(fig, filename=(
f'{cls.name}.{filename_dsets}.{meas.url_name}.png'
))
class Boxplot(Plotter):
"""Boxplot one station/measurement @ multiple years."""
for year in years:
data = read_data(station, year)
selected_data = data[:, meas.field]
plot_data.append(selected_data)
year_max = max(data, key=at_index)
year_min = min(data, key=at_index)
if maximum is None:
maximum, minimum = year_max, year_min
else:
maximum = max(maximum, year_max, key=at_index)
minimum = min(minimum, year_min, key=at_index)
fig, axes = plt.subplots()
fig.set_figheight(6)
fig.set_figwidth(12)
axes.boxplot(plot_data, positions=years)
axes.set_ylabel(meas.title)
axes.grid(True)
axes.set_title(
(f'Max {meas.title}: {maximum[meas.field]}, Date: ({maximum[0]}). '
f'Min {meas.title}: {minimum[meas.field]}, Date: ({minimum[0]}).'),
fontsize='small',
)
name = station['name']
plt.suptitle(f'{meas.title} measurements, {name} Station, '
f'{start_year} - {end_year}.')
return savefig_response(
fig,
filename=(f'boxplot.{station_id}.{year1}.{year2}.{meas.url_name}.png'),
)
name = 'boxplot'
nav_title = 'Boxplot'
@classmethod
def plot(cls):
station_id = get_param('station')
year1 = get_param('year1', to=year_type)
year2 = get_param('year2', to=year_type)
meas = get_param('measurement', to=meas_type)
station = get_station(station_id)
plot_data = []
start_year, end_year = sorted([year1, year2])
years = range(start_year, end_year + 1)
maximum = minimum = None
def at_index(row):
"""Get the selected field of `row`."""
return row[meas.field]
for year in years:
data = read_data(station, year)
plot_data.append(data[:, meas.field])
year_max = max(data, key=at_index)
year_min = min(data, key=at_index)
if maximum is None:
maximum, minimum = year_max, year_min
else:
maximum = max(maximum, year_max, key=at_index)
minimum = min(minimum, year_min, key=at_index)
fig, axes = plt.subplots()
fig.set_figheight(6)
fig.set_figwidth(12)
axes.boxplot(plot_data, positions=years)
axes.set_ylabel(meas.title)
axes.grid(True)
axes.set_title(
(f'Max {meas.title}: {maximum[meas.field]}, Date: ({maximum[0]}). '
f'Min {meas.title}: {minimum[meas.field]}, '
f'Date: ({minimum[0]}).'),
fontsize='small',
)
name = station['name']
plt.suptitle(f'{meas.title} measurements, {name} Station, '
f'{start_year} - {end_year}.')
return savefig_response(fig, filename=(
f'{cls.name}.{station_id}.{year1}.{year2}.{meas.url_name}.png'
))
plotters = {plotter.name: plotter for plotter in Plotter.__subclasses__()}
def savefig_response(fig, filename=None):
......
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