"""Plotting functions."""
from io import BytesIO
from types import SimpleNamespace
from flask import Response
from .data import read_data
from .parameters import get_param, meas_type, year_type
from .records import get_station
class Selector:
"""Information about a `<select>`."""
def __init__(self, **kwargs):
if kwargs['type'] not in ('station', 'year', 'measurement'):
raise ValueError('unknown type')
self.type = kwargs['type']
self.name = kwargs['name']
self.id = kwargs['id']
self.label = kwargs['label']
self.onchange = kwargs.get('onchange')
def get_param(self):
if self.type == 'year':
to = year_type
elif self.type == 'measurement':
to = meas_type
else:
to = str
return get_param(self.name, to=to, call_abort=False)
def put_param(self, param):
"""Convert a parameter of this type back to a string."""
if self.type == 'measurement':
return param.slug
return str(param)
class Plotter:
"""Parent of plotter classes."""
class TimeSeries(Plotter):
"""Plot one station/year/measurement."""
name = 'time-series'
nav_title = 'Time Series'
page_title = 'Plot Data'
onsubmit_fn = 'timeSeriesVisualize'
selectors = (
Selector(type='station', name='station', id='station', label='Station',
onchange='getYears()'),
Selector(type='year', name='year', id='year', label='Year'),
Selector(type='measurement', name='measurement', id='measurement',
label='Measurement'),
)
source_param_maps = (
{'station': 'station', 'year': 'year'},
)
@classmethod
def plot(cls):
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
plt.style.use('ggplot')
plt.rcParams['axes.xmargin'] = 0
matplotlib.use('Agg')
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[-1, 0],
linestyle='-',
alpha=0.7)
axes.set_ylabel(f'{meas.title.title()} ({meas.units})')
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]} {meas.units} '
f'on {maximum[0]:%F at %R} / '
f'Min {meas.title}: {minimum[meas.field]} {meas.units} '
f'on {minimum[0]:%F at %R}'),
fontsize='small',
)
name = station['name']
plt.suptitle(f'{meas.title.capitalize()} measurements, '
f'{name} Station, {data[0, 0].year}')
return savefig_response(fig, filename=(
f'{cls.name}.{station_id}.{year}.{meas.slug}.png'
))
class Overlay(Plotter):
"""Plot two station/years @ one measurement."""
name = 'overlay'
nav_title = 'Overlay'
page_title = 'Overlay Stations'
onsubmit_fn = 'overlayVisualize'
selectors = (
Selector(type='station', name='station1', id='station-1',
label='Station #1', onchange='getYears(1)'),
Selector(type='year', name='year1', id='year-1', label='Year #1'),
Selector(type='station', name='station2', id='station-2',
label='Station #2', onchange='getYears(2)'),
Selector(type='year', name='year2', id='year-2', label='Year #2'),
Selector(type='measurement', name='measurement', id='measurement',
label='Measurement'),
)
source_param_maps = (
{'station': 'station1', 'year': 'year1'},
{'station': 'station2', 'year': 'year2'},
)
@classmethod
def plot(cls):
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
plt.style.use('ggplot')
plt.rcParams['axes.xmargin'] = 0
matplotlib.use('Agg')
num_datasets = 2
datasets = tuple(SimpleNamespace() for _ in range(num_datasets))
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)
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[-1, 0],
alpha=0.7,
label=f'Avg {dset.name} {dset.data[0, 0].year}')
axes.set_ylabel(f'{meas.title.title()} ({meas.units})')
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.name} Station, '
f'{max_dset.max[meas.field]} {meas.units} '
f'on {max_dset.max[0]:%F at %R} / '
f'Min {meas.title}: {min_dset.name} Station, '
f'{min_dset.min[meas.field]} {meas.units} '
f'on {min_dset.min[0]:%F at %R}'),
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.capitalize()} measurements, '
f'{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.slug}.png'
))
class Boxplot(Plotter):
"""Boxplot one station/measurement @ multiple years."""
name = 'boxplot'
nav_title = 'Boxplot'
page_title = 'Boxplot Years'
onsubmit_fn = 'boxplotVisualize'
selectors = (
Selector(type='station', name='station', id='station', label='Station',
onchange='boxplotGetYears()'),
Selector(type='year', name='year1', id='year-1', label='Year #1'),
Selector(type='year', name='year2', id='year-2', label='Year #2'),
Selector(type='measurement', name='measurement', id='measurement',
label='Measurement'),
)
source_param_maps = (
{'station': 'station', 'year': 'year1'},
)
@classmethod
def plot(cls):
import matplotlib
import matplotlib.pyplot as plt
plt.style.use('ggplot')
plt.rcParams['axes.xmargin'] = 0
matplotlib.use('Agg')
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(f'{meas.title.title()} ({meas.units})')
axes.grid(True)
axes.set_title(
(f'Max {meas.title}: {maximum[meas.field]} {meas.units} '
f'on {maximum[0]:%F at %R} / '
f'Min {meas.title}: {minimum[meas.field]} {meas.units} '
f'on {minimum[0]:%F at %R}'),
fontsize='small',
)
name = station['name']
plt.suptitle(f'{meas.title.capitalize()} measurements, '
f'{name} Station, {start_year} - {end_year}.')
return savefig_response(fig, filename=(
f'{cls.name}.{station_id}.{year1}.{year2}.{meas.slug}.png'
))
plotters = {plotter.name: plotter for plotter in Plotter.__subclasses__()}
def savefig_response(fig, filename=None):
"""Make an image response with `fig.savefig()`."""
buf = BytesIO()
fig.savefig(buf, format='png')
res = Response(buf.getvalue(), mimetype='image/png')
if filename is not None:
res.headers['Content-Disposition'] = f'inline; filename="{filename}"'
return res