def proc_trend_x(db_list, fc_dict):
""" サマリーX (↑支持, ↑不支持 グラフ)
"""
args = cfg['args']
fig, ax = plt.subplots(figsize=(8, 5))
fig.subplots_adjust(left=0.16, right=0.8, bottom=0.15)
# 色指定
cy = 'darkorange'
cn = 'skyblue'
# 支持率
tim, avg, sdv, num = tven_buf['APP_RATE'].by_column()
dda = [dt_fm_sn(a) for a in tim]
err = sdv/np.sqrt(num)
ax.fill_between(dda, avg-err, avg+err, color=cy, alpha=0.3)
ax.plot(dda, avg, color=cy, label='支持(平均)', alpha=1)
# 不支持率
tim, avg, sdv, num = tven_buf['NAP_RATE'].by_column()
dda = [dt_fm_sn(a) for a in tim]
err = sdv/np.sqrt(num)
ax.fill_between(dda, avg-err, avg+err, color=cn, alpha=0.3)
ax.plot(dda, avg, color=cn, label='不支持(平均)', alpha=1)
# 支持率の個別データ (感度補正後)
for db in db_list:
yy = [a/fc_dict['APP_RATE'][db.label](b) for a,b in zip(db.db['APP_RATE'], db.db['T'])]
dd = [dt_fm_sn(a) for a in db.db['T']]
ax.plot(dd, yy, db.marker, ms=db.size*0.5, color='orange', alpha=1, label=db.label)
# X 軸
ax.xaxis_date()
ax.set_xlim(dt_fm_sn(tim[0]), dt_fm_sn(30 + tim[-1]))
# ax.set_xlim(datetime(2019,2,1), datetime(2020,4,1)) # 日付埋め込み ★
set_date_tick(ax, (1, 7), '%Y/%m', 30)
# Y 軸
ax.set_yticks(range(0, 100, 5))
ax.set_yticks(range(0, 100, 1), minor=True)
ax.set_ylim([20, 65])
# タイトル/グリッド
ax.set_title('報道 10社の平均')
ax.grid(which='both')
ax.grid(which='minor', alpha=0.1)
# 凡例
ax.legend(loc='upper left', bbox_to_anchor=(1.0, 1.0))
# 注釈
if args.k_days > 0:
fig.text(0.19, 0.16, "平均は指数移動平均(時定数 %d 日)"%args.k_days, fontsize=8) #, bbox=bbox)
else:
fig.text(0.19, 0.16, "平均は日曜前後数日", fontsize=8) #, bbox=bbox)
# 図の出力
if args.gout:
fig.savefig(os.path.join(args.gout_folder, 'Fig%d_%s.png' % (args.gout_ndx + 1, cfg['gout_date'])))
def __call__(self, i):
# 進行状況を画面出力
sys.stdout.write('%s %s\r' %
(i, dt_fm_sn(self.tt[i]).strftime('%Y-%m-%d')))
# クリア
self.ax.cla()
# 描画
for (pp, yc, g) in [(self.ppj, 'brown', 'jnn'),
(self.pp2, 'indigo', 'グループ H'),
(self.pp3, 'green', 'グループ L')]:
if False and cfg['avg']:
if g != 'jnn':
x_ = np.mean(
[p.interp['APP_RATE'](self.tt[i]) for p in pp])
y_ = np.mean(
[p.interp['NAP_RATE'](self.tt[i]) for p in pp])
self.ax.plot(x_, y_, '*', color=yc, label=g)
else:
dt = dt_fm_sn(self.tt[i])
for p in pp:
if True or p.label in ['読売', '毎日', '朝日']:
x = p.interp['APP_RATE'](self.tt[i])
y = p.interp['NAP_RATE'](self.tt[i])
s = '%s %s' % (p.label, dt_fm_sn(
p.db['T'][-1]).strftime('%m/%d'))
if p.label == '毎日':
if dt < datetime(2020, 5, 20):
flg_dsp = True
else:
flg_dsp = False
elif p.label == 'SSRC':
if dt > datetime(2020, 4, 1):
flg_dsp = True
else:
flg_dsp = False
else:
flg_dsp = True
if flg_dsp:
self.ax.plot(x,
y,
p.marker,
ms=p.size,
color=yc,
label=s,
alpha=0.5)
else:
pass
x_ = np.mean([p.interp['APP_RATE'](self.tt[i]) for p in self.pp3])
y_ = np.mean([p.interp['NAP_RATE'](self.tt[i]) for p in self.pp3])
self.ax.text(x_ - 8,
y_ - 10,
nen_tsuki(dt_fm_sn(self.tt[i])),
alpha=0.5,
fontsize=16)
self.ax.plot([0, 100], [0, 100], '--', color='gray', alpha=0.3)
self.set_labels()
def proc_yn(pp2, pp3, ppj):
""" 支持と不支持の合計のトレンド
"""
args = cfg['args']
fig, ax = plt.subplots()
fig.subplots_adjust(right=0.8, bottom=0.15)
ax.set_title('内閣支持率と不支持率の合計', fontsize=15)
# ax.set_xlim([datetime(2016,4,1), datetime(2018,10,1)])
for db_list in [ppj, pp2, pp3]:
for db in db_list:
x = [dt_fm_sn(a) for a in db.db['T']]
y = np.array(db.db['APP_RATE']) + np.array(db.db['NAP_RATE'])
ax.plot(x, y, db.marker + '-', ms=db.size * 0.5, label=db.label)
ax.legend(loc='upper left', bbox_to_anchor=(1.0, 1.0))
ax.grid(True)
set_date_tick(ax, (1, 7), '%Y/%m', 30)
ax.set_ylabel('支持率 + 不支持率 [%]', fontsize=14)
if args.gout:
fig.savefig(
os.path.join(
args.gout_folder,
'Fig%d_%s.png' % (args.gout_ndx + 4, cfg['gout_date'])))
def set_labels(self):
self.ax.set_aspect('equal')
xymin, xymax = [int(a) for a in cfg['args'].xy_range.split(':')
] # X軸,Y軸の範囲(X,Y 共通)
self.ax.set_xlim((xymin, xymax))
self.ax.set_ylim((xymin, xymax))
y1, m1 = [int(a) for a in dt_fm_sn(self.t0).strftime('%Y %m').split()]
y2, m2 = [int(a) for a in dt_fm_sn(self.tf).strftime('%Y %m').split()]
self.ax.set_title('内閣支持率(%d年%d月～%d年%d月)' % (y1, m1, y2, m2))
self.ax.set_xlabel('支持する[%]', fontsize=14)
self.ax.set_ylabel('支持しない[%]', fontsize=14)
self.ax.legend(loc='upper left', bbox_to_anchor=(1.0, 1.0))
self.ax.grid(True)
def proc_hilo():
""" HI - LO のトレンド
"""
fig, axes = plt.subplots(2, 1)
fig.subplots_adjust(left=0.16, right=0.86, bottom=0.15)
for (ndx, yn) in enumerate(['APP_RATE', 'NAP_RATE']):
tim2, avg2, _err, _num = tven_buf['H'][yn].by_column()
tim3, avg3, _err, _num = tven_buf['L'][yn].by_column()
f2 = interp(tim2, avg2)
f3 = interp(tim3, avg3)
tmin = max(tim2[0], tim3[0])
tmax = min(tim2[-1], tim3[-1])
t_node = np.arange(tmin, tmax, 1)
d_node = [dt_fm_sn(a) for a in t_node]
y_node = [f2(t) - f3(t) for t in t_node]
axes[ndx].plot(d_node, y_node)
axes[ndx].grid(True)
axes[ndx].set_ylim(-4, 12)
if ndx == 0:
set_date_tick(axes[ndx], (1, 4, 7, 10), '%m', 0)
else:
set_date_tick(axes[ndx], (1, 7), '%Y/%m', 30)
def proc_fc(fc_dict, pp2, pp3, ppj):
""" 感度係数 H, L 別
"""
fig, axes = plt.subplots(4, 1, figsize=(6, 8))
fig.subplots_adjust(left=0.1, bottom=0.1, right=0.85, top=0.95, hspace=0.3)
for j, (yn, db_list) in enumerate([('APP_RATE', pp2), ('NAP_RATE', pp2),
('APP_RATE', pp3), ('NAP_RATE', pp3)]):
ax = axes[j]
for db in db_list:
fc = fc_dict[yn][db.label]
t = db.db['T']
d = [dt_fm_sn(a) for a in t]
f = [fc(a) for a in t]
ax.plot(d, f, label=db.label)
ax.set_ylim(0.9, 1.2)
ax.grid(True)
if (j % 2) == 0:
ax.legend(loc='upper left', bbox_to_anchor=(1.0, 1.0))
else:
pass
if j == 3:
set_date_tick(ax, (1, 7), '%Y/%m', 30)
else:
set_date_tick(ax, (1, 4, 7, 10), '%m', 0)
def proc_last(pp2, pp3, ppj):
""" 作図 支持率 -- 不支持率 最新値(２次元プロット)
最新値と前回からの差分を 支持率--不支持率 グラフ(２次元)にプロットする。
オプションで古い最新値を無視する (-t 14 など)。
オプションでイメージファイル Fig?_yymmdd.png を出力する。
Parameters
----------
pp2, pp3, ppj : グループ毎の DB() リスト.
"""
args = cfg['args']
xymin, xymax = [int(a)
for a in args.xy_range.split(':')] # X軸,Y軸の範囲(X,Y 共通)
xoff, yoff = [float(a) for a in args.label_offset.split(':')] # ラベルのオフセット
fig = plt.figure(figsize=(4.8 * (1800 / 1012), 4.8))
fig.subplots_adjust(left=0.02, bottom=0.13, right=0.9, top=0.88)
ax = fig.add_subplot(1, 1, 1)
ax.set_aspect('equal')
fig.text(
0.50,
0.847,
'線分は前回からの変化',
fontsize=10,
#fig.text(0.4, 0.14, '各社の最新(線分は前回からの変化)', fontsize=10,
bbox=dict(facecolor='gray', edgecolor='none', alpha=0.2))
ax.set_xlabel('内閣を支持する [%]', fontsize=14)
ax.set_ylabel('内閣を支持しない [%]', fontsize=14)
ax.set_xlim(xymin, xymax)
ax.set_ylim(xymin, xymax)
ax.set_xticks(range(xymin, xymax + 1, 5))
ax.set_yticks(range(xymin, xymax + 1, 5))
ax.grid(True)
# 各社最新
cm = plt.get_cmap('tab10')
cn = 0
flg_old = False
for (pp, col, ab) in [(ppj, 'brown', 'C'), (pp2, 'indigo', 'グループH'),
(pp3, 'green', 'グループL')]:
for p in pp:
tref = max(t_max(ppj), t_max(pp2), t_max(pp3))
# DB の終端からの日にちで絞る(オプショナル)
if args.trimday and (p.db['T'][-1] < (tref - int(args.trimday))):
continue
if p.db['T'][-1] > tref - 42:
alp_mark, alp_line, alp_text = 1.0, 0.8, 0.8
else:
alp_mark, alp_line, alp_text = 0.2, 0.2, 0.2
flg_old = True
xx = p.db['APP_RATE'][-2:]
yy = p.db['NAP_RATE'][-2:]
st1 = dt_fm_sn(p.db['T'][-1]).strftime('%m/%d')
st2 = dt_fm_sn(p.db['T'][-2]).strftime('%m/%d')
s = '%s %s (%s)' % (p.label, st1, st2)
ax.plot(xx, yy, '-', lw=1, color=cm(cn), alpha=alp_line)
ax.plot(xx[-1],
yy[-1],
p.marker,
ms=p.size,
color=cm(cn),
alpha=alp_mark,
label=s)
ax.text(xx[-1] + xoff,
yy[-1] + yoff,
p.label,
fontsize=10,
alpha=alp_text)
cn = (cn + 1) % 10
ax.plot([0, 100], [0, 100], '--', alpha=0.5)
ax.legend(loc='upper left', bbox_to_anchor=(1.02, 1.02))
if flg_old:
fig.text(0.7, 0.3, '薄い表示は古い調査(6 週間経過)', fontsize=10)
if args.gout:
fn = 'Fig%s_%s.png' % (args.gout_ndx, cfg['gout_date'])
fig.savefig(os.path.join(args.gout_folder, fn))
def proc_trend():
""" サマリー (↑支持, ↓不支持 グラフ)
"""
args = cfg['args']
fig, ax1 = plt.subplots(figsize=(8, 5))
ax2 = ax1.twinx()
fig.subplots_adjust(left=0.16, right=0.8, bottom=0.15)
# 色指定
cy = 'darkorange'
cy2 = 'orangered'
cn = 'skyblue'
cn2 = 'darkcyan'
# ---< 支持率 >---
tta, ppa_buf, sdv_buf, num_buf = tven_buf['APP_RATE'].by_column()
dda = [dt_fm_sn(a) for a in tta]
ax = ax1
err = sdv_buf/np.sqrt(num_buf)
ax.fill_between(dda, ppa_buf-err, ppa_buf+err, color=cy, linestyle='dashed', alpha=0.3)
ax.plot(dda, ppa_buf, color=cy, label='報道10社平均', alpha=1)
# Y 軸
ax.set_ylim([0, 100])
ax.tick_params(axis='y', colors=cy2)
ax.set_yticks(range(0, 51, 10))
ax.text(datetime(2016, 9, 1), 30, '支持する', color=cy2, fontsize=20)
ax.set_ylabel('内閣を支持する [%]', color=cy2, fontsize=14)
ax.yaxis.set_label_coords(-0.08, 0.3)
# ---< 不支持率 >---
tta, ppa_buf, sdv_buf, num_buf = tven_buf['NAP_RATE'].by_column()
dda = [dt_fm_sn(a) for a in tta]
ax = ax2
err = sdv_buf/np.sqrt(num_buf)
ax.fill_between(dda, ppa_buf-err, ppa_buf+err, color=cn, linestyle='dashed', alpha=0.3)
ax.plot(dda, ppa_buf, color=cn, label='報道10社平均', alpha=1)
# Y2 軸
ax.set_ylim([100, 0])
ax.tick_params(axis='y', colors=cn2)
ax.set_yticks(range(0, 51, 10))
ax.text(datetime(2016, 8, 1), 20, '支持しない', color=cn2, fontsize=20)
ax.set_ylabel('内閣を支持しない [%]', color=cn2, fontsize=14)
ax.yaxis.set_label_coords(1.08, 0.7)
# X 軸
ax = ax1
ax.xaxis_date()
ax.set_xlim(dt_fm_sn(tta[0]), dt_fm_sn(30 + tta[-1]))
set_date_tick(ax, (1, 7), '%Y/%m', 30)
# タイトル/グリッド
ax1.set_title('報道 10社の平均')
ax1.grid(which='both')
ax2.grid(which='both')
ax1.grid(which='minor', alpha=0.1)
ax2.grid(which='minor', alpha=0.1)
# 注釈
# bbox=dict(facecolor='white', edgecolor='none', alpha=0.7)
if args.k_days > 0:
fig.text(0.19, 0.16, "平均は指数移動平均(時定数 %d 日)"%args.k_days, fontsize=8) #, bbox=bbox)
else:
fig.text(0.19, 0.16, "平均は日曜前後数日", fontsize=8) #, bbox=bbox)
if args.gout:
fig.savefig(os.path.join(args.gout_folder, 'Fig%d_%s.png' % (args.gout_ndx + 0, cfg['gout_date'])))
def proc_raw_cal_sdv(fc_dict, axes, k_app_nap, db_list):
""" 発表値、補正値、補正値の残差のグラフ
"""
args = cfg['args']
if args.rainbow:
cm = plt.get_cmap('rainbow')
def _c(j):
return cm(1.0 - j/len(db_list))
else:
cm = plt.get_cmap('tab10')
def _c(j):
return cm(j)
tim, val, err, num = tven_buf[k_app_nap].by_column()
ax =axes[0]
ax.set_ylim(20, 70)
ax.set_ylabel('調査結果(発表値) %')
for (j, db) in enumerate(db_list):
dd = [dt_fm_sn(a) for a in db.db['T']]
if db.label != 'SSRC':
ax.plot(dd, db.db[k_app_nap], db.marker+'-', ms=db.size*0.5, color=_c(j), label=db.label, alpha=0.5)
else:
ddvv = [a for a in zip(dd, db.db[k_app_nap]) if a[0] > datetime(2020, 4, 1)]
dd, vv = [a for a in zip(*ddvv)]
ax.plot(dd, vv, db.marker+'-', ms=db.size*0.5, color=_c(j), label=db.label, alpha=0.5)
set_date_tick(ax, (1,4,7,10), '%m', 0)
ax.grid(True)
ax.legend(loc='upper left', bbox_to_anchor=(1.0, 1.0))
ax =axes[1]
ax.set_ylim(20, 70)
ax.set_ylabel('感度補正後(曲線は平均値) %')
ax.set_ylabel('感度補正後 %')
for (j, db) in enumerate(db_list):
dd = [dt_fm_sn(a) for a in db.db['T']]
vv = [a/fc_dict[k_app_nap][db.label](b) for a, b in zip(db.db[k_app_nap], db.db['T'])]
if db.label != 'SSRC':
ax.plot(dd, vv, db.marker, ms=db.size*0.5, color=_c(j), label=db.label, alpha=0.5)
else:
ddvv = [a for a in zip(dd, vv) if a[0] > datetime(2020, 4, 1)]
dd, vv = [a for a in zip(*ddvv)]
ax.plot(dd, vv, db.marker+'-', ms=db.size*0.5, color=_c(j), label=db.label, alpha=0.5)
dd = [dt_fm_sn(a) for a in tim]
ee = err/np.sqrt(num)
ax.fill_between(dd, val-ee, val+ee, color='blue', alpha=0.1)
ax.plot(dd, val,'-', color='blue', lw=1, alpha=1)
set_date_tick(ax, (1,4,7,10), '%m', 0)
ax.grid(True)
ax =axes[2]
ax.set_ylim(-8, 8)
ax.set_ylabel('感度補正後の残差 %')
for (j, db) in enumerate(db_list):
vv = [a/fc_dict[k_app_nap][db.label](b) for a, b in zip(db.db[k_app_nap], db.db['T'])]
dv, sd = deviation(db.db['T'], vv, interp(tim, val))
dd = [dt_fm_sn(a) for a in db.db['T']]
ax.plot(dd, dv, '-', color=_c(j), label=db.label, alpha=0.5)
set_date_tick(ax, (1, 7), '%Y/%m', 30)
ax.grid(True)
ax.legend(loc='upper left', bbox_to_anchor=(1.0, 1.0))
def proc_factor(db_list, k_app_nap, k_title, fc_dict, gn_rel):
""" 報道10 社の支持率/不支持率の調査感度の時系列比較
Parameters
----------
db_list, list of DB()
k_app_nap, string : 分析データキー ('APP_RATE' or 'NAP_RATE')
k_title, string : グラフタイトル
fc_dict, - : 他の分析で使っている感度係数補間関数の辞書
gn_rel, : 出力図番の相対
"""
args = cfg['args']
# 図の準備
nr = 6
fig, axes = plt.subplots(nr, 2, figsize=(10, 7))
fig.text(0.10, 0.97, k_title, fontsize=16)
fig.text(0.60, 0.97, '(オレンジ:3ヵ月移動平均 ブルー:6ヵ月移動平均)', fontsize=12)
fig.subplots_adjust(left=0.1, bottom=0.1, right=0.95, top=0.95, wspace=0.25, hspace=0.25)
# 分析期間
t0 = sn_fm_dt(_d(cfg['args'].db_begin))
tf = t_max(db_list)
# 移動平均の窓幅をいくつか選んで感度のトレンドを描画(調査会社毎)
for ndx, m in enumerate([3, 6]): # window size (m-month)
tt = np.arange(t0 + 6*30, tf, 7)
ff = calc_fact(db_list, k_app_nap, tt, m*30)
dd = [dt_fm_sn(a) for a in tt]
for j, (f, db) in enumerate(zip(ff, db_list)):
c, r = divmod(j, nr)
if ndx == 0:
axes[r,c].plot(dd, f, color='orange', lw=2, alpha=0.8)
else:
axes[r,c].plot(dd, f, color='blue')
fc = [fc_dict[k_app_nap][db.label](t) for t in tt]
axes[r,c].plot(dd, fc, '-', color='green', alpha=0.5)
axes[r,c].set_xlim(dd[0], dd[-1]+timedelta(days=30))
# タイトルや軸の設定
db_list_ax = db_list + ['']*(nr*2 - len(db_list))
print('db_list_ax', len(db_list_ax))
for j, db in enumerate(db_list_ax):
c, r = divmod(j, nr)
axes[r,c].set_xlim(dd[0], dd[-1]+timedelta(days=30))
if db != '':
axes[r, c].set_ylabel(db.label)
axes[r, c].set_ylim(0.8, 1.3)
axes[r, c].grid(which='both')
axes[r, c].grid(which='minor', alpha=0.1)
if r == (nr - 1):
print(r, c)
set_date_tick(axes[r,c], (1, 7), '%Y/%m', 30)
else:
set_date_tick(axes[r,c], (1, 7), '%m', 0)
# 調査が実施された日付をプロット
if db != '':
dd_org = [dt_fm_sn(a) for a in db.db['T']]
oo_org = np.ones_like(dd_org)
axes[r,c].plot(dd_org, oo_org, 'o', ms=4, alpha=0.2)
if args.gout:
fig.savefig(os.path.join(args.gout_folder, 'Fig%d_%s.png' % (args.gout_ndx + gn_rel, cfg['gout_date'])))
def test_dt_fm_sn():
eq_(dt_fm_sn(61), datetime(1900, 3, 1))
def proc_raw_cal_sdv(fc_dict, axes, yn, db_list, tim, avg):
ax = axes[0]
ax.set_ylim(20, 70)
ax.set_ylabel('調査結果(発表値) %')
for db in db_list:
dd = [dt_fm_sn(a) for a in db.db['T']]
if db.label != 'SSRC':
ax.plot(dd,
db.db[yn],
db.marker,
ms=db.size * 0.5,
label=db.label,
alpha=0.5)
else:
ddvv = [
a for a in zip(dd, db.db[yn]) if a[0] > datetime(2020, 4, 1)
]
dd, vv = [a for a in zip(*ddvv)]
ax.plot(dd,
vv,
db.marker + '-',
ms=db.size * 0.5,
label=db.label,
alpha=0.5)
set_date_tick(ax, (1, 4, 7, 10), '%m', 0)
ax.grid(True)
ax.legend(loc='upper left', bbox_to_anchor=(1.0, 1.0))
ax = axes[1]
ax.set_ylim(20, 70)
ax.set_ylabel('感度補正後(線は平均値) %')
for db in db_list:
dd = [dt_fm_sn(a) for a in db.db['T']]
ff = [fc_dict[yn][db.label](t) for t in db.db['T']]
vv = [a / b for a, b in zip(db.db[yn], ff)]
if db.label != 'SSRC':
ax.plot(dd,
vv,
db.marker,
ms=db.size * 0.5,
label=db.label,
alpha=0.5)
else:
ddvv = [a for a in zip(dd, vv) if a[0] > datetime(2020, 4, 1)]
dd, vv = [a for a in zip(*ddvv)]
ax.plot(dd,
vv,
db.marker + '-',
ms=db.size * 0.5,
label=db.label,
alpha=0.5)
dd = [dt_fm_sn(a) for a in tim]
ax.plot(dd, avg, '-', color='royalblue', lw=2) #, alpha=0.1)
set_date_tick(ax, (1, 4, 7, 10), '%m', 0)
ax.grid(True)
ax.legend(loc='upper left', bbox_to_anchor=(1.0, 1.0))
ax = axes[2]
ax.set_ylim(-8, 8)
ax.set_ylabel('感度補正後の残差 %')
for db in db_list:
vv = [
a / fc_dict[yn][db.label](b)
for (a, b) in zip(db.db[yn], db.db['T'])
]
ss, sd = deviation(db.db['T'], vv, interp(tim, avg))
dd = [dt_fm_sn(a) for a in db.db['T']]
ax.plot(dd, ss, '-', label=db.label, alpha=0.5)
set_date_tick(ax, (1, 7), '%Y/%m', 30)
ax.grid(True)
ax.legend(loc='upper left', bbox_to_anchor=(1.0, 1.0))
def proc_trend():
""" サマリー (↑支持, ↓不支持) + 円グラフ
"""
args = cfg['args']
flg_jnn = False
tt2, app_hi, err_, num_ = tven_buf['H']['APP_RATE'].by_column()
tt2, nap_hi, err_, num_ = tven_buf['H']['NAP_RATE'].by_column()
tt3, app_lo, err_, num_ = tven_buf['L']['APP_RATE'].by_column()
tt3, nap_lo, err_, num_ = tven_buf['L']['NAP_RATE'].by_column()
ttj, app_j, err_, num_ = tven_buf['J']['APP_RATE'].by_column()
ttj, nap_j, err_, num_ = tven_buf['J']['NAP_RATE'].by_column()
dd2 = [dt_fm_sn(a) for a in tt2]
dd3 = [dt_fm_sn(a) for a in tt3]
ddj = [dt_fm_sn(a) for a in ttj]
fig, ax1 = plt.subplots()
fig.subplots_adjust(left=0.16, right=0.86, bottom=0.15)
# 色指定
cy = 'darkorange'
cy2 = 'orangered'
cn = 'skyblue'
cn2 = 'darkcyan'
ax = ax1
ax.fill_between(dd3, 0, app_lo, color=cy, label='グループL', alpha=0.5)
ax.plot(dd3, app_lo, lw=1, color=cy, alpha=1.0)
if flg_jnn:
ax.plot(ddj, app_j, '--', lw=1, color=cy, label='JNN', alpha=1.0)
ax.plot(dd2, app_hi, '-', lw=1, color='tomato', label='グループH')
# Y 凡例
ax.legend(loc='upper left', bbox_to_anchor=(0.65, 0.25))
# Y 軸
ax.set_ylim([0, 100])
ax.tick_params(axis='y', colors=cy2)
ax.set_yticks(range(0, 51, 10))
ax.text(datetime(2016, 9, 1), 22, '支持する', color=cy2, fontsize=20)
ax.set_ylabel('内閣を支持する [%]', color=cy2, fontsize=14)
ax.yaxis.set_label_coords(-0.08, 0.3)
# ---< 不支持率 >---
ax2 = ax1.twinx()
ax = ax2
ax.fill_between(dd3, 0, nap_lo, color=cn, label='グループL', alpha=0.5)
ax.plot(dd3, nap_lo, lw=1, color=cn, alpha=1.0)
if flg_jnn:
ax.plot(ddj, nap_j, '--', lw=1, color=cn, label='JNN', alpha=1.0)
ax.plot(dd2, nap_hi, '-', lw=1, color='royalblue', label='グループH')
# Y2 凡例 (順序を逆転)
hh, ll = ax.get_legend_handles_labels()
hh, ll = reverse_legend(hh, ll)
ax.legend(hh, ll, loc='upper left', bbox_to_anchor=(0.65, 0.9))
# Y2 軸
ax.set_ylim([100, 0])
ax.tick_params(axis='y', colors=cn2)
ax.set_yticks(range(0, 51, 10))
ax.text(datetime(2016, 8, 1), 18, '支持しない', color=cn2, fontsize=20)
ax.set_ylabel('内閣を支持しない [%]', color=cn2, fontsize=14)
ax.yaxis.set_label_coords(1.08, 0.7)
# X 軸
ax.xaxis_date()
ax.set_xlim(dt_fm_sn(min(tt2[0], tt3[0])),
dt_fm_sn(30 + max(tt2[-1], tt3[-1])))
set_date_tick(ax1, (1, 7), '%Y/%m', 30)
# タイトル/グリッド
ax1.grid(which='both')
ax2.grid(which='both')
ax1.grid(which='minor', alpha=0.1)
ax2.grid(which='minor', alpha=0.1)
# 注釈
# bbox=dict(facecolor='white', edgecolor='none', alpha=0.7)
fig.text(0.19, 0.23, "グループ H: 読売/日経/共同 の平均", fontsize=8) #, bbox=bbox)
fig.text(0.19, 0.19, "グループ L: 毎日/朝日/時事/ANN/NHK の平均",
fontsize=8) #, bbox=bbox)
if args.k_days > 0:
fig.text(0.19, 0.16, "平均は指数移動平均(時定数 %d 日)" % args.k_days,
fontsize=8) #, bbox=bbox)
else:
fig.text(0.19, 0.16, "平均は日曜前後数日", fontsize=8) #, bbox=bbox)
if args.gout:
fig.savefig(
os.path.join(
args.gout_folder,
'Fig%d_%s.png' % (args.gout_ndx + 0, cfg['gout_date'])))
# ---< 円グラフ >---
fig = plt.figure(figsize=(4, 4))
fig.subplots_adjust(left=0, bottom=0, right=1, top=1)
ax = fig.add_subplot(1, 1, 1)
n3 = nap_lo[-1]
n2 = nap_hi[-1]
y3 = app_lo[-1]
y2 = app_hi[-1]
if n2 < n3:
n2 = n3
if y2 < y3:
y2 = y3
dd = [n3, n2 - n3, 100 - n2 - y2, y2 - y3, y3]
# cc = [cn, 'royalblue', '0.3', 'tomato', cy]
# cc = [cn, 'deepskyblue', '0.3', 'orange', cy]
cc = [cn, 'royalblue', '0.7', 'tomato', cy]
ll = ['支持しない', 'やや', '他', 'やや', '支持する']
ll = ['', 'やや', '他', 'やや', '']
patches, texts = ax.pie(dd,
labels=ll,
counterclock=False,
startangle=90,
colors=cc,
labeldistance=0.7,
textprops={'color': 'white'},
radius=1.23)
ax.text(0.6,
0.22,
'支持しない',
fontsize=20,
color='white',
horizontalalignment='center')
ax.text(-0.6,
0.22,
'支持する',
fontsize=20,
color='white',
horizontalalignment='center')
for t in texts:
t.set_horizontalalignment('center')
t.set_size(14)
if args.gout:
fig.savefig(
os.path.join(args.gout_folder,
'Fig%d_%s.png' % (args.gout + 1, cfg['gout_date'])))
print('L (3)', y3, n3)
print('H (2)', y2, n2)
