Source code for openquake.commands.plot
# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
#
# Copyright (C) 2015-2020 GEM Foundation
#
# OpenQuake is free software: you can redistribute it and/or modify it
# under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# OpenQuake is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with OpenQuake. If not, see <http://www.gnu.org/licenses/>.
import gzip
import logging
import shapely
import numpy
from openquake.baselib import sap
from openquake.hazardlib.contexts import Effect, get_effect_by_mag
from openquake.hazardlib.calc.filters import getdefault, MagDepDistance
from openquake.calculators.extract import Extractor, WebExtractor
[docs]def make_figure_hcurves(extractors, what):
"""
$ oq plot 'hcurves?kind=mean&imt=PGA&site_id=0'
"""
import matplotlib.pyplot as plt
fig = plt.figure()
got = {} # (calc_id, kind) -> curves
for i, ex in enumerate(extractors):
hcurves = ex.get(what)
for kind in hcurves.kind:
arr = getattr(hcurves, kind)
got[ex.calc_id, kind] = arr
oq = ex.oqparam
n_imts = len(hcurves.imt)
[site] = hcurves.site_id
for j, imt in enumerate(hcurves.imt):
imls = oq.imtls[imt]
ax = fig.add_subplot(n_imts, 1, j + 1)
ax.set_xlabel('%s, site %s, inv_time=%dy' %
(imt, site, oq.investigation_time))
ax.set_ylabel('PoE')
for ck, arr in got.items():
if (arr == 0).all():
logging.warning('There is a zero curve %s_%s', *ck)
ax.loglog(imls, arr.flat, '-', label='%s_%s' % ck)
ax.grid(True)
ax.legend()
return plt
[docs]def make_figure_vs30(extractors, what):
"""
$ oq plot 'vs30?'
"""
import matplotlib.pyplot as plt
fig = plt.figure()
[ex] = extractors
sitecol = ex.get('sitecol')
ax = fig.add_subplot(111)
ax.grid(True)
ax.set_xlabel('vs30 for calculation %d' % ex.calc_id)
vs30 = sitecol['vs30']
vs30[numpy.isnan(vs30)] = 0
ax.scatter(sitecol['lon'], sitecol['lat'], c=vs30, cmap='jet')
return plt
[docs]def make_figure_hmaps(extractors, what):
"""
$ oq plot 'hmaps?kind=mean&imt=PGA'
"""
import matplotlib.pyplot as plt
fig = plt.figure()
ncalcs = len(extractors)
if ncalcs > 2:
raise RuntimeError('Could not plot more than two calculations at once')
elif ncalcs == 2: # plot the differences
ex1, ex2 = extractors
oq1 = ex1.oqparam
oq2 = ex2.oqparam
n_poes = len(oq1.poes)
assert n_poes == len(oq2.poes)
itime = oq1.investigation_time
assert oq2.investigation_time == itime
sitecol = ex1.get('sitecol')
assert (ex2.get('sitecol').array == sitecol.array).all()
hmaps1 = ex1.get(what)
hmaps2 = ex2.get(what)
[imt] = hmaps1.imt
assert [imt] == hmaps2.imt
[kind] = hmaps1.kind
assert hmaps1.kind == [kind]
for j, poe in enumerate(oq1.poes):
diff = hmaps1[kind][:, 0, j] - hmaps2[kind][:, 0, j]
maxdiff = numpy.abs(diff).max()
ax = fig.add_subplot(1, n_poes, j + 1)
ax.grid(True)
ax.set_xlabel('IMT=%s, kind=%s, poe=%s\ncalcs %d-%d, '
'inv_time=%dy\nmaxdiff=%s' %
(imt, kind, poe, ex1.calc_id, ex2.calc_id,
itime, maxdiff))
coll = ax.scatter(sitecol['lon'], sitecol['lat'],
c=diff, cmap='jet')
plt.colorbar(coll)
elif ncalcs == 1: # plot the hmap
[ex] = extractors
oq = ex.oqparam
n_poes = len(oq.poes)
sitecol = ex.get('sitecol')
hmaps = ex.get(what)
[imt] = hmaps.imt
[kind] = hmaps.kind
for j, poe in enumerate(oq.poes):
ax = fig.add_subplot(1, n_poes, j + 1)
ax.grid(True)
ax.set_xlabel('hmap for IMT=%s, kind=%s, poe=%s\ncalculation %d, '
'inv_time=%dy' %
(imt, kind, poe, ex.calc_id, oq.investigation_time))
coll = ax.scatter(sitecol['lon'], sitecol['lat'],
c=hmaps[kind][:, 0, j], cmap='jet')
plt.colorbar(coll)
return plt
[docs]def make_figure_uhs(extractors, what):
"""
$ oq plot 'uhs?kind=mean&site_id=0'
"""
import matplotlib.pyplot as plt
fig = plt.figure()
got = {} # (calc_id, kind) -> curves
for i, ex in enumerate(extractors):
uhs = ex.get(what)
for kind in uhs.kind:
got[ex.calc_id, kind] = uhs[kind]
oq = ex.oqparam
n_poes = len(oq.poes)
periods = [imt.period for imt in oq.imt_periods()]
[site] = uhs.site_id
for j, poe in enumerate(oq.poes):
ax = fig.add_subplot(n_poes, 1, j + 1)
ax.set_xlabel('UHS on site %s, poe=%s, inv_time=%dy' %
(site, poe, oq.investigation_time))
ax.set_ylabel('SA')
for ck, arr in got.items():
curve = list(arr[site][str(poe)])
ax.plot(periods, curve, '-', label='%s_%s' % ck)
ax.plot(periods, curve, '.')
ax.grid(True)
ax.legend()
return plt
[docs]def stacked_bar(ax, x, ys, width):
cumsum = ys.cumsum(axis=0)
for i, y in enumerate(ys):
if i > 0:
ax.bar(x, y, width, bottom=cumsum[i-1])
else:
ax.bar(x, y, width)
[docs]def make_figure_disagg(extractors, what):
"""
$ oq plot 'disagg?kind=Mag&imt=PGA'
"""
import matplotlib.pyplot as plt
from matplotlib import cm
fig = plt.figure()
oq = extractors[0].oqparam
disagg = extractors[0].get(what)
[sid] = disagg.site_id
[imt] = disagg.imt
[poe_id] = disagg.poe_id
y = disagg.array
print(y)
ndims = len(y.shape)
axis = disagg.kind.split('_')
bins = getattr(disagg, axis[0])
ncalcs = len(extractors)
width = (bins[1] - bins[0]) * 0.5
x = middle(bins) if ncalcs == 1 else middle(bins) - width
if ndims == 1: # simple bar chart
ax = fig.add_subplot(1, 1, 1)
ax.set_xlabel('Disagg%s on site %s, imt=%s, poe_id=%d, inv_time=%dy' %
(disagg.kind, sid, imt, poe_id, oq.investigation_time))
ax.set_xlabel(axis[0])
ax.set_xticks(bins)
ax.bar(x, y, width)
for ex in extractors[1:]:
ax.bar(x + width, ex.get(what).array, width)
return plt
if ncalcs > 1:
raise NotImplementedError('Comparison for %s' % disagg.kind)
# 2D images
if ndims == 2:
y = y.reshape(y.shape + (1,))
zbins = ['']
else:
zbins = getattr(disagg, axis[2])
Z = y.shape[-1]
axes = []
for z in range(Z):
arr = y[:, :, z]
ax = fig.add_subplot(Z, 1, z + 1)
axes.append(ax)
ax.set_ylabel(axis[1])
ax.set_title(zbins[z])
vbins = getattr(disagg, axis[1]) # vertical bins
cmap = cm.get_cmap('jet', 100)
extent = bins[0], bins[-1], vbins[0], vbins[-1]
im = ax.imshow(arr, cmap=cmap, extent=extent,
aspect='auto', vmin=y.min(), vmax=y.max())
# stacked bar chart
# stacked_bar(ax, x, y.T, width)
# ys = ['%.1f' % y for y in getattr(disagg, axis[1])]
# ax.legend(ys)
fig.colorbar(im, ax=axes)
return plt
[docs]def make_figure_task_info(extractors, what):
"""
$ oq plot 'task_info?kind=classical'
"""
import matplotlib.pyplot as plt
fig = plt.figure()
[ex] = extractors
[(task_name, task_info)] = ex.get(what).to_dict().items()
x = task_info['duration']
ax = fig.add_subplot(1, 1, 1)
mean, std = x.mean(), x.std(ddof=1)
ax.hist(x, bins=50, rwidth=0.9)
ax.set_xlabel("mean=%d+-%d seconds" % (mean, std))
ax.set_ylabel("tasks=%d" % len(x))
#from scipy.stats import linregress
#ax = fig.add_subplot(2, 1, 2)
#arr = numpy.sort(task_info, order='duration')
#x, y = arr['duration'], arr['weight']
#reg = linregress(x, y)
#ax.plot(x, reg.intercept + reg.slope * x)
#ax.plot(x, y)
#ax.set_ylabel("weight")
#ax.set_xlabel("duration")
return plt
[docs]def make_figure_memory(extractors, what):
"""
$ oq plot 'memory?'
"""
# NB: matplotlib is imported inside since it is a costly import
import matplotlib.pyplot as plt
[ex] = extractors
task_info = ex.get('task_info').to_dict()
fig, ax = plt.subplots()
ax.grid(True)
ax.set_xlabel('tasks')
ax.set_ylabel('GB')
start = 0
for task_name in task_info:
mem = task_info[task_name]['mem_gb']
ax.plot(range(start, start + len(mem)), mem, label=task_name)
start += len(mem)
ax.legend()
return plt
[docs]class PolygonPlotter():
"""
Add polygons to a given axis object
"""
def __init__(self, ax):
self.ax = ax
self.minxs = []
self.maxxs = []
self.minys = []
self.maxys = []
[docs] def add(self, poly, **kw):
from openquake.hmtk.plotting.patch import PolygonPatch
minx, miny, maxx, maxy = poly.bounds
self.minxs.append(minx)
self.maxxs.append(maxx)
self.minys.append(miny)
self.maxys.append(maxy)
try:
self.ax.add_patch(PolygonPatch(poly, **kw))
except ValueError: # LINESTRING, not POLYGON
pass
[docs] def set_lim(self, sitecol=None):
if sitecol:
self.minxs.append(min(sitecol['lon']))
self.maxxs.append(max(sitecol['lon']))
self.minys.append(min(sitecol['lat']))
self.maxys.append(max(sitecol['lat']))
if self.minxs and self.maxxs:
self.ax.set_xlim(min(self.minxs), max(self.maxxs))
if self.minys and self.maxys:
self.ax.set_ylim(min(self.minys), max(self.maxys))
[docs]def make_figure_sources(extractors, what):
"""
$ oq plot sources?limit=100
$ oq plot sources?source_id=1&source_id=2
$ oq plot sources?code=A&code=N
"""
# NB: matplotlib is imported inside since it is a costly import
import matplotlib.pyplot as plt
[ex] = extractors
info = ex.get(what)
wkts = gzip.decompress(info.wkt_gz).decode('utf8').split(';')
srcs = gzip.decompress(info.src_gz).decode('utf8').split(';')
fig, ax = plt.subplots()
ax.grid(True)
sitecol = ex.get('sitecol')
ax.plot(sitecol['lon'], sitecol['lat'], '+')
pp = PolygonPlotter(ax)
n = 0
tot = 0
for rec, srcid, wkt in zip(info, srcs, wkts):
if not wkt:
logging.warning('No geometries for source id %s', srcid)
continue
if rec['eff_ruptures']: # not filtered out
color = 'green'
alpha = .3
n += 1
else:
color = 'yellow'
alpha = .1
pp.add(shapely.wkt.loads(wkt), alpha=alpha, color=color)
tot += 1
pp.set_lim(sitecol)
ax.set_title('%d/%d sources' % (n, tot))
return plt
[docs]def make_figure_rupture_info(extractors, what):
"""
$ oq plot rupture_info?min_mag=6
"""
# NB: matplotlib is imported inside since it is a costly import
import matplotlib.pyplot as plt
[ex] = extractors
info = ex.get(what)
fig, ax = plt.subplots()
ax.grid(True)
n = 0
tot = 0
pp = PolygonPlotter(ax)
geoms = gzip.decompress(info['boundaries']).decode('utf8').split('\n')
for rec, wkt in zip(info, geoms):
poly = shapely.wkt.loads(wkt)
if poly.is_valid:
pp.add(poly)
n += 1
else:
print('Invalid %s' % wkt)
tot += 1
pp.set_lim()
ax.set_title('%d/%d valid ruptures' % (n, tot))
if tot == 1:
# print the full geometry
print(ex.get('rupture/%d' % rec['rupid']).toml())
return plt
[docs]def make_figure_effect(extractors, what):
"""
$ oq plot 'effect?'
"""
# NB: matplotlib is imported inside since it is a costly import
import matplotlib.pyplot as plt
from matplotlib import cm
[ex] = extractors
effect = ex.get(what)
trts = ex.get('full_lt').trts
mag_ticks = effect.mags[::-5]
fig = plt.figure()
cmap = cm.get_cmap('jet', 100)
axes = []
vmin = numpy.log10(effect.array.min())
vmax = numpy.log10(effect.array.max())
for trti, trt in enumerate(trts):
ax = fig.add_subplot(len(trts), 1, trti + 1)
axes.append(ax)
ax.set_xticks(mag_ticks)
ax.set_xlabel('Mag')
dist_ticks = effect.dist_bins[trt][::10]
ax.set_yticks(dist_ticks)
ax.set_ylabel(trt)
extent = mag_ticks[0], mag_ticks[-1], dist_ticks[0], dist_ticks[-1]
im = ax.imshow(numpy.log10(effect[:, :, trti]), cmap=cmap,
extent=extent, aspect='auto', vmin=vmin, vmax=vmax)
fig.colorbar(im, ax=axes)
return plt
[docs]def make_figure_rups_by_mag_dist(extractors, what):
"""
$ oq plot 'rups_by_mag_dist?'
"""
# NB: matplotlib is imported inside since it is a costly import
import matplotlib.pyplot as plt
from matplotlib import cm
[ex] = extractors
counts = ex.get(what)
counts.array = numpy.log10(counts.array + 1)
trts = ex.get('full_lt').trts
mag_ticks = counts.mags[::-5]
fig = plt.figure()
cmap = cm.get_cmap('jet', 100)
axes = []
vmax = counts.array.max()
for trti, trt in enumerate(trts):
ax = fig.add_subplot(len(trts), 1, trti + 1)
axes.append(ax)
ax.set_xticks(mag_ticks)
ax.set_xlabel('Mag')
dist_ticks = counts.dist_bins[trt][::10]
ax.set_yticks(dist_ticks)
ax.set_ylabel(trt)
extent = mag_ticks[0], mag_ticks[-1], dist_ticks[0], dist_ticks[-1]
im = ax.imshow(counts[:, :, trti], cmap=cmap,
extent=extent, aspect='auto', vmin=0, vmax=vmax)
fig.colorbar(im, ax=axes)
return plt
[docs]def make_figure_dist_by_mag(extractors, what):
"""
$ oq plot 'dist_by_mag?'
"""
# NB: matplotlib is imported inside since it is a costly import
import matplotlib.pyplot as plt
[ex] = extractors
effect = ex.get('effect')
mags = ['%.2f' % mag for mag in effect.mags]
fig, ax = plt.subplots()
trti = 0
for trt, dists in effect.dist_bins.items():
dic = dict(zip(mags, effect[:, :, trti]))
if ex.oqparam.pointsource_distance:
pdist = getdefault(ex.oqparam.pointsource_distance, trt)
else:
pdist = None
eff = Effect(dic, dists, pdist)
dist_by_mag = eff.dist_by_mag()
ax.plot(effect.mags, list(dist_by_mag.values()), label=trt,
color='red')
if pdist:
dist_by_mag = eff.dist_by_mag(eff.collapse_value)
ax.plot(effect.mags, list(dist_by_mag.values()), label=trt,
color='green')
ax.set_xlabel('Mag')
ax.set_ylabel('Dist')
ax.set_title('Integration Distance at intensity=%s' % eff.zero_value)
trti += 1
ax.legend()
return plt
[docs]def make_figure_effect_by_mag(extractors, what):
"""
$ oq plot 'effect_by_mag?'
"""
# NB: matplotlib is imported inside since it is a costly import
import matplotlib.pyplot as plt
[ex] = extractors
gsims_by_trt = ex.get('gsims_by_trt', asdict=True)
mags = ex.get('source_mags').array
try:
effect = ex.get('effect')
except KeyError:
onesite = ex.get('sitecol').one()
maximum_distance = MagDepDistance(ex.oqparam.maximum_distance)
imtls = ex.oqparam.imtls
ebm = get_effect_by_mag(
mags, onesite, gsims_by_trt, maximum_distance, imtls)
effect = numpy.array(list(ebm.values()))
fig, ax = plt.subplots()
trti = 0
for trt in gsims_by_trt:
ax.plot(mags, effect[:, -1, trti], label=trt)
ax.set_xlabel('Mag')
ax.set_ylabel('Intensity')
ax.set_title('Effect at maximum distance')
trti += 1
ax.legend()
return plt
[docs]def make_figure_agg_curves(extractors, what):
"""
$ oq plot 'agg_curves?kind=mean&loss_type=structural' -1
"""
import matplotlib.pyplot as plt
fig = plt.figure()
got = {} # (calc_id, kind) -> curves
for i, ex in enumerate(extractors):
aw = ex.get(what + '&absolute=1')
agg_curve = aw.array.squeeze()
got[ex.calc_id, aw.kind[0]] = agg_curve
oq = ex.oqparam
periods = aw.return_period
ax = fig.add_subplot(1, 1, 1)
ax.set_xlabel('risk_inv_time=%dy' % oq.risk_investigation_time)
ax.set_ylabel('PoE')
for ck, arr in got.items():
ax.loglog(periods, agg_curve, '-', label='%s_%s' % ck)
ax.loglog(periods, agg_curve, '.')
ax.grid(True)
ax.legend()
return plt
[docs]def make_figure_tot_curves(extractors, what):
"""
$ oq plot 'tot_curves?loss_type=structural&kind=rlz-000&absolute=1'
"""
import matplotlib.pyplot as plt
fig = plt.figure()
[ex] = extractors
tot = ex.get(what)
app = ex.get(what.replace('tot_', 'app_'))
ax = fig.add_subplot(1, 1, 1)
ax.set_xlabel('return periods')
ax.set_ylabel('PoE')
ax.loglog(tot.return_period, tot[:, 0], '-', label='tot_curves')
ax.loglog(app.return_period, app[:, 0], '-', label='app_curves')
ax.grid(True)
ax.legend()
return plt
[docs]@sap.script
def plot(what='examples', calc_id=-1, other_id=None, webapi=False,
local=False):
"""
Generic plotter for local and remote calculations.
"""
if what == 'examples':
help_msg = ['Examples of possible plots:']
for k, v in globals().items():
if k.startswith('make_figure_'):
help_msg.append(v.__doc__)
raise SystemExit(''.join(help_msg))
if '?' not in what:
raise SystemExit('Missing ? in %r' % what)
prefix, rest = what.split('?', 1)
if prefix in 'hcurves hmaps' and 'imt=' not in rest:
raise SystemExit('Missing imt= in %r' % what)
elif prefix == 'uhs' and 'imt=' in rest:
raise SystemExit('Invalid IMT in %r' % what)
elif prefix in 'hcurves uhs disagg' and 'site_id=' not in rest:
what += '&site_id=0'
if prefix == 'disagg' and 'poe_id=' not in rest:
what += '&poe_id=0'
if local:
xs = [WebExtractor(calc_id, 'http://localhost:8800', '')]
if other_id:
xs.append(WebExtractor(other_id), 'http://localhost:8800', '')
elif webapi:
xs = [WebExtractor(calc_id)]
if other_id:
xs.append(WebExtractor(other_id))
else:
xs = [Extractor(calc_id)]
if other_id:
xs.append(Extractor(other_id))
make_figure = globals()['make_figure_' + prefix]
plt = make_figure(xs, what)
plt.show()
plot.arg('what', 'what to extract')
plot.arg('calc_id', 'computation ID', type=int)
plot.arg('other_id', 'ID of another computation', type=int)
plot.flg('webapi', 'if given, pass through the WebAPI')
plot.flg('local', 'if passed, use the local WebAPI')