def box_line_wsp(wsp=None, output_dir=None, points=None, extra_info=None):
plt.rcParams['font.sans-serif'] = ['SimHei'] # 步骤一（替换sans-serif字体）
plt.rcParams['axes.unicode_minus'] = False # 步骤二（解决坐标轴负数的负号显示问题）
if (sys.platform[0:3] == 'lin'):
locale.setlocale(locale.LC_CTYPE, 'zh_CN.utf8')
if (sys.platform[0:3] == 'win'):
locale.setlocale(locale.LC_CTYPE, 'chinese')
initTime = pd.to_datetime(str(
wsp['forecast_reference_time'].values)).replace(
tzinfo=None).to_pydatetime()
# draw figure
fig = plt.figure(figsize=(16, 4.5))
# draw main figure
#10米风——————————————————————————————————————
ax = plt.axes([0.1, 0.28, .8, .62])
utl.add_public_title_sta(
title=wsp.attrs['model'] + '预报 ' + extra_info['point_name'] + ' [' +
str(points['lon'][0]) + ',' + str(points['lat'][0]) + ']',
initTime=initTime,
fontsize=21)
for ifhour in wsp['forecast_period'].values:
if (ifhour == wsp['forecast_period'].values[0]):
if (ifhour % 12 == 0):
uv_t = (initTime +
timedelta(hours=ifhour)).strftime('%m月%d日%H时')
else:
uv_t = ' '
else:
if (ifhour % 12 == 0):
uv_t = np.append(
uv_t,
(initTime + timedelta(hours=ifhour)).strftime('%m月%d日%H时'))
else:
uv_t = np.append(uv_t, ' ')
labels = uv_t
ax.boxplot(np.transpose(np.squeeze(wsp['data'].values)),
labels=labels,
meanline=True,
showmeans=True,
showfliers=False,
whis=(0, 100))
warning = np.zeros(len(uv_t)) + 20.
warning_t = np.arange(0, len(uv_t)) + 1
ax.plot(warning_t, warning, c='red', label=' ', linewidth=1)
ax.set_ylim(0, math.ceil(wsp['data'].values.max() / 2) * 2)
#plt.xlim(uv_t[0],uv_t[-1])
# add legend
#ax.legend(fontsize=15,loc='upper right')
ax.tick_params(length=7)
ax.tick_params(axis='y', labelsize=100)
for label in ax.get_xticklabels():
label.set_rotation(30)
label.set_horizontalalignment('center')
ax.tick_params(axis='y', labelsize=15)
ax.tick_params(axis='x', labelsize=10)
miloc = mpl.dates.HourLocator(byhour=(8, 11, 14, 17, 20, 23, 2, 5)) #单位是小时
ax.xaxis.set_minor_locator(miloc)
yminorLocator = MultipleLocator(1) #将此y轴次刻度标签设置为1的倍数
ax.yaxis.set_minor_locator(yminorLocator)
ymajorLocator = MultipleLocator(2) #将此y轴次刻度标签设置为1的倍数
ax.yaxis.set_major_locator(ymajorLocator)
ax.grid(axis='x', ls='--')
for label in ax.get_yticklabels():
label.set_fontsize(15)
#ax.axis['left'].major_ticklabels.set_fontsize(15)
t_gap = wsp['forecast_period'].values[1] - wsp['forecast_period'].values[0]
ax.set_ylabel('风速 (m s$^-$$^1$)', fontsize=15)
utl.add_logo_extra_in_axes(pos=[0.87, 0.00, .1, .1],
which='nmc',
size='Xlarge')
#出图——————————————————————————————————————————————————————————
if (output_dir != None):
isExists = os.path.exists(output_dir)
if not isExists:
os.makedirs(output_dir)
output_dir2 = output_dir + wsp.attrs[
'model'] + '_起报时间_' + initTime.strftime("%Y年%m月%d日%H时") + '/'
if (os.path.exists(output_dir2) == False):
os.makedirs(output_dir2)
plt.savefig(output_dir2 + wsp.attrs['model'] + '_' +
extra_info['point_name'] + '_' +
extra_info['output_head_name'] +
initTime.strftime("%Y%m%d%H") + '00' +
extra_info['output_tail_name'] + '_风速_箱线图' + '.jpg',
dpi=200,
bbox_inches='tight')
else:
plt.show()
def draw_Station_Snow_Synthetical_Forecast_From_Cassandra(
TWC=None,
AT=None,
u10m=None,
v10m=None,
u100m=None,
v100m=None,
gust10m=None,
wsp10m=None,
wsp100m=None,
SNOD1=None,
SNOD2=None,
SDEN=None,
SN06=None,
draw_VIS=False,
VIS=None,
drw_thr=False,
time_all=None,
model=None,
points=None,
output_dir=None,
extra_info={
'output_head_name': ' ',
'output_tail_name': ' ',
'point_name': ' '
}):
#if(sys.platform[0:3] == 'win'):
plt.rcParams['font.sans-serif'] = ['SimHei'] # 步骤一（替换sans-serif字体）
plt.rcParams['axes.unicode_minus'] = False # 步骤二（解决坐标轴负数的负号显示问题）
if (sys.platform[0:3] == 'lin'):
locale.setlocale(locale.LC_CTYPE, 'zh_CN.utf8')
if (sys.platform[0:3] == 'win'):
locale.setlocale(locale.LC_CTYPE, 'chinese')
initTime1 = pd.to_datetime(str(
TWC['forecast_reference_time'].values)).replace(
tzinfo=None).to_pydatetime()
initTime2 = pd.to_datetime(str(
VIS['forecast_reference_time'].values)).replace(
tzinfo=None).to_pydatetime()
# draw figure
fig = plt.figure(figsize=(12, 16))
# draw main figure
#风寒指数 体感温度————————————————————————————————————————————————
ax = plt.axes([0.05, 0.83, .94, .15])
utl.add_public_title_sta(title=model + '预报 ' + extra_info['point_name'] +
' [' + str(points['lon'][0]) + ',' +
str(points['lat'][0]) + ']',
initTime=initTime1,
fontsize=23)
for ifhour in TWC['forecast_period'].values:
if (ifhour == TWC['forecast_period'].values[0]):
TWC_t = (initTime1 + timedelta(hours=ifhour))
else:
TWC_t = np.append(TWC_t, (initTime1 + timedelta(hours=ifhour)))
#开启自适应
xaxis_intaval = mpl.dates.HourLocator(byhour=(8, 20)) #单位是小时
ax.xaxis.set_major_locator(xaxis_intaval)
ax.set_xticklabels([' '])
ax.plot(TWC_t, np.squeeze(TWC), label='风寒指数')
ax.plot(TWC_t, np.squeeze(AT), c='#00796B', label='2米体感温度')
ax.tick_params(length=10)
ax.grid()
ax.grid(axis='x', c='black')
miloc = mpl.dates.HourLocator(byhour=(11, 14, 17, 23, 2, 5)) #单位是小时
ax.xaxis.set_minor_locator(miloc)
ax.grid(axis='x', which='minor')
plt.xlim(time_all[0], time_all[-1])
plt.ylim(min([AT.values.min(), TWC.values.min()]),
max([AT.values.max(), TWC.values.max()]))
ax.legend(fontsize=10, loc='upper right')
ax.set_ylabel('2米体感温度 风寒指数 ($^\circ$C)', fontsize=15)
#10米风——————————————————————————————————————
ax = plt.axes([0.05, 0.66, .94, .15])
for ifhour in u10m['forecast_period'].values:
if (ifhour == u10m['forecast_period'].values[0]):
uv10m_t = (initTime1 + timedelta(hours=ifhour))
else:
uv10m_t = np.append(uv10m_t, (initTime1 + timedelta(hours=ifhour)))
for ifhour in u100m['forecast_period'].values:
if (ifhour == u100m['forecast_period'].values[0]):
uv100m_t = (initTime1 + timedelta(hours=ifhour))
else:
uv100m_t = np.append(uv100m_t,
(initTime1 + timedelta(hours=ifhour)))
for ifhour in gust10m['forecast_period'].values:
if (ifhour == gust10m['forecast_period'].values[0]):
gust10m_t = (initTime1 + timedelta(hours=ifhour))
else:
gust10m_t = np.append(gust10m_t,
(initTime1 + timedelta(hours=ifhour)))
ax.plot(uv10m_t,
np.squeeze(wsp10m),
c='#40C4FF',
label='10米风',
linewidth=3)
ax.plot(uv100m_t,
np.squeeze(wsp100m),
c='#FF6F00',
label='100米风',
linewidth=3)
ax.plot(gust10m_t,
np.squeeze(gust10m['data']),
c='#7C4DFF',
label='10米阵风',
linewidth=3)
if (drw_thr == True):
ax.plot([uv10m_t[0], uv10m_t[-1]], [5.5, 5.5],
c='#4CAE50',
label='10米平均风一般影响',
linewidth=1)
ax.plot([uv10m_t[0], uv10m_t[-1]], [8, 8],
c='#FFEB3B',
label='10米平均风较大影响',
linewidth=1)
ax.plot([uv10m_t[0], uv10m_t[-1]], [10.8, 10.8],
c='#F44336',
label='10米平均风高影响',
linewidth=1)
ax.plot([gust10m_t[0], gust10m_t[-1]], [10.8, 10.8],
c='#4CAE50',
label='10米阵风一般影响',
dashes=[6, 2],
linewidth=1)
ax.plot([gust10m_t[0], gust10m_t[-1]], [13.9, 13.9],
c='#FFEB3B',
label='10米阵风较大影响',
dashes=[6, 2],
linewidth=1)
ax.plot([gust10m_t[0], gust10m_t[-1]], [17.2, 17.2],
c='#F44336',
label='10米阵风高影响',
dashes=[6, 2],
linewidth=1)
ax.barbs(uv10m_t[0:-1],
wsp10m[0:-1],
np.squeeze(u10m['data'])[0:-1],
np.squeeze(v10m['data'])[0:-1],
fill_empty=True,
color='gray',
barb_increments={
'half': 2,
'full': 4,
'flag': 20
})
ax.barbs(uv100m_t[0:-1],
wsp100m[0:-1],
np.squeeze(u100m['data'])[0:-1],
np.squeeze(v100m['data'])[0:-1],
fill_empty=True,
color='gray',
barb_increments={
'half': 2,
'full': 4,
'flag': 20
})
xaxis_intaval = mpl.dates.HourLocator(byhour=(8, 20)) #单位是小时
ax.xaxis.set_major_locator(xaxis_intaval)
ax.set_xticklabels([' '])
plt.xlim(time_all[0], time_all[-1])
# add legend
ax.legend(fontsize=10, loc='upper right')
ax.tick_params(length=10)
ax.grid()
ax.grid(axis='x', c='black')
miloc = mpl.dates.HourLocator(byhour=(11, 14, 17, 23, 2, 5)) #单位是小时
ax.xaxis.set_minor_locator(miloc)
ax.grid(axis='x', which='minor')
ax.set_ylabel('10米风 100米 风\n' + '风速 (m/s)', fontsize=15)
#雪密度——————————————————————————————————————
# draw main figure
ax = plt.axes([0.05, 0.49, .94, .15])
for ifhour in SDEN['forecast_period'].values:
if (ifhour == SDEN['forecast_period'].values[0]):
SDEN_t = (initTime1 + timedelta(hours=ifhour))
else:
SDEN_t = np.append(SDEN_t, (initTime1 + timedelta(hours=ifhour)))
#开启自适应
xaxis_intaval = mpl.dates.HourLocator(byhour=(8, 20)) #单位是小时
ax.xaxis.set_major_locator(xaxis_intaval)
ax.set_xticklabels([' '])
ax.plot(SDEN_t, np.squeeze(SDEN['data']), color='#1E88E5', label='雪密度')
#ax.bar(SDEN_t,np.squeeze(SDEN['data']),width=0.12,color='#1E88E5')
gap_hour_SDEN = int(SDEN['forecast_period'].values[1] -
SDEN['forecast_period'].values[0])
if (drw_thr == True):
ax.plot([SDEN_t[0], SDEN_t[-1]],
[1 * gap_hour_SDEN, 1 * gap_hour_SDEN],
c='#FFEB3B',
label=str(gap_hour_SDEN) + '小时降水较大影响',
linewidth=1)
ax.plot([SDEN_t[0], SDEN_t[-1]],
[10 * gap_hour_SDEN, 10 * gap_hour_SDEN],
c='#F44336',
label=str(gap_hour_SDEN) + '小时降水高影响',
linewidth=1)
ax.legend(fontsize=10, loc='upper right')
ax.tick_params(length=10)
ax.grid()
ax.grid(axis='x', c='black')
miloc = mpl.dates.HourLocator(byhour=(11, 14, 17, 23, 2, 5)) #单位是小时
ax.xaxis.set_minor_locator(miloc)
ax.grid(axis='x', which='minor')
plt.xlim(time_all[0], time_all[-1])
plt.ylim([
np.squeeze(SDEN['data']).values.min(),
np.squeeze(SDEN['data'].values.max()) + 2
])
ax.set_ylabel('雪密度 (kg m-3)', fontsize=15)
#积雪深度——————————————————————————————————————
# draw main figure
ax = plt.axes([0.05, 0.32, .94, .15])
for ifhour in SNOD1['forecast_period'].values:
if (ifhour == SNOD1['forecast_period'].values[0]):
SNOD1_t = (initTime1 + timedelta(hours=ifhour))
else:
SNOD1_t = np.append(SNOD1_t, (initTime1 + timedelta(hours=ifhour)))
# draw main figure
for ifhour in SNOD2['forecast_period'].values:
if (ifhour == SNOD2['forecast_period'].values[0]):
SNOD2_t = (initTime1 + timedelta(hours=ifhour))
else:
SNOD2_t = np.append(SNOD2_t, (initTime1 + timedelta(hours=ifhour)))
for ifhour in SN06['forecast_period'].values:
if (ifhour == SN06['forecast_period'].values[0]):
SN06_t = (initTime1 + timedelta(hours=ifhour))
else:
SN06_t = np.append(SN06_t, (initTime1 + timedelta(hours=ifhour)))
#开启自适应
xaxis_intaval = mpl.dates.HourLocator(byhour=(8, 20)) #单位是小时
ax.xaxis.set_major_locator(xaxis_intaval)
ax.set_xticklabels([' '])
#ax.bar(SNOD1_t,np.squeeze(SNOD1['data']),width=0.20,color='#82B1FF',label='EC预报积雪深度')
#ax.bar(SNOD2_t,np.squeeze(SNOD2['data']),width=0.125,color='#2962FF',label='NCEP预报积雪深度')
ax.plot(SNOD1_t,
np.squeeze(SNOD1['data']),
dashes=[6, 2],
color='#4B4B4B',
linewidth=3,
label='EC预报积雪深度')
ax.plot(SNOD2_t,
np.squeeze(SNOD2['data']),
dashes=[6, 2],
color='#969696',
linewidth=3,
label='NCEP预报积雪深度')
ax.plot(SN06_t,
np.squeeze(SN06['data']),
color='#82B1FF',
linewidth=2,
label='EC预报降雪量')
ax.tick_params(length=10)
ax.grid()
ax.grid(axis='x', c='black')
miloc = mpl.dates.HourLocator(byhour=(11, 14, 17, 23, 2, 5)) #单位是小时
ax.xaxis.set_minor_locator(miloc)
ax.grid(axis='x', which='minor')
plt.xlim(time_all[0], time_all[-1])
plt.ylim(0, 100)
ax.legend(fontsize=10, loc='upper right')
plt.ylim(
min([
np.squeeze(SNOD1['data']).values.min(),
np.squeeze(SNOD2['data']).values.min()
]),
max([
np.squeeze(SNOD1['data']).values.max(),
np.squeeze(SNOD2['data']).values.max()
]) + 5)
ax.set_ylabel('积雪深度 (cm)\n' + '6小时降雪量(mm)', fontsize=15)
if (draw_VIS == False):
xstklbls = mpl.dates.DateFormatter('%m月%d日%H时')
ax.xaxis.set_major_formatter(xstklbls)
for label in ax.get_xticklabels():
label.set_rotation(30)
label.set_horizontalalignment('center')
#发布信息————————————————————————————————————————————————
ax = plt.axes([0.05, 0.08, .94, .05])
ax.axis([0, 10, 0, 10])
ax.axis('off')
utl.add_logo_extra_in_axes(pos=[0.7, 0.23, .05, .05],
which='nmc',
size='Xlarge')
ax.text(7.5,
33, (initTime1 - timedelta(hours=2)).strftime("%Y年%m月%d日%H时") +
'发布',
size=15)
if (draw_VIS == True):
#能见度——————————————————————————————————————
# draw main figure
ax = plt.axes([0.05, 0.15, .94, .15])
#VIS=pd.read_csv(dir_all['VIS_SC']+last_file[model])
for ifhour in VIS['forecast_period'].values:
if (ifhour == VIS['forecast_period'].values[0]):
VIS_t = (initTime2 + timedelta(hours=ifhour))
else:
VIS_t = np.append(VIS_t, (initTime2 + timedelta(hours=ifhour)))
#开启自适应
xaxis_intaval = mpl.dates.HourLocator(byhour=(8, 20)) #单位是小时
ax.xaxis.set_major_locator(xaxis_intaval)
ax.fill_between(VIS_t,
np.squeeze(VIS['data']),
-100,
facecolor='#B3E5FC')
ax.fill_between(VIS_t, np.squeeze(VIS['data']), 1, facecolor='#81D4FA')
ax.fill_between(VIS_t, np.squeeze(VIS['data']), 3, facecolor='#4FC3F7')
ax.fill_between(VIS_t, np.squeeze(VIS['data']), 5, facecolor='#29B6F6')
ax.fill_between(VIS_t,
np.squeeze(VIS['data']),
10,
facecolor='#03A9F4')
ax.fill_between(VIS_t,
np.squeeze(VIS['data']),
15,
facecolor='#039BE5')
ax.fill_between(VIS_t,
np.squeeze(VIS['data']),
20,
facecolor='#0288D1')
ax.fill_between(VIS_t,
np.squeeze(VIS['data']),
25,
facecolor='#0277BD')
ax.fill_between(VIS_t,
np.squeeze(VIS['data']),
30,
facecolor='#01579B')
ax.fill_between(VIS_t,
np.squeeze(VIS['data']),
100,
facecolor='#FFFFFF')
ax.plot(VIS_t, np.squeeze(VIS['data']))
if (drw_thr == True):
ax.plot([VIS_t[0], VIS_t[-1]], [5, 5],
c='#4CAF50',
label='能见度一般影响',
linewidth=1)
ax.plot([VIS_t[0], VIS_t[-1]], [3, 3],
c='#FFEB3B',
label='能见度较大影响',
linewidth=1)
ax.plot([VIS_t[0], VIS_t[-1]], [1, 1],
c='#F44336',
label='能见度高影响',
linewidth=1)
ax.legend(fontsize=10, loc='upper right')
xstklbls = mpl.dates.DateFormatter('%m月%d日%H时')
ax.xaxis.set_major_formatter(xstklbls)
for label in ax.get_xticklabels():
label.set_rotation(30)
label.set_horizontalalignment('center')
ax.tick_params(length=10)
ax.grid()
ax.grid(axis='x', c='black')
miloc = mpl.dates.HourLocator(byhour=(11, 14, 17, 23, 2, 5)) #单位是小时
ax.xaxis.set_minor_locator(miloc)
ax.grid(axis='x', which='minor')
plt.xlim(time_all[0], time_all[-1])
plt.ylim(0, 25)
ax.set_ylabel('能见度 （km）', fontsize=15)
#发布信息————————————————————————————————————————————————
ax = plt.axes([0.05, 0.08, .94, .05])
ax.axis([0, 10, 0, 10])
ax.axis('off')
utl.add_logo_extra_in_axes(pos=[0.7, 0.06, .05, .05],
which='nmc',
size='Xlarge')
ax.text(7.5,
0.1,
(initTime2 - timedelta(hours=2)).strftime("%Y年%m月%d日%H时") +
'发布',
size=15)
#出图——————————————————————————————————————————————————————————
if (output_dir != None):
isExists = os.path.exists(output_dir)
if not isExists:
os.makedirs(output_dir)
plt.savefig(output_dir + extra_info['output_head_name'] +
initTime1.strftime("%Y%m%d%H") + '00' +
extra_info['output_tail_name'] + '.jpg',
dpi=200,
bbox_inches='tight')
else:
plt.show()
def draw_point_wind(U=None,
V=None,
model=None,
output_dir=None,
points=None,
time_info=None,
extra_info=None):
plt.rcParams['font.sans-serif'] = ['SimHei'] # 步骤一（替换sans-serif字体）
plt.rcParams['axes.unicode_minus'] = False # 步骤二（解决坐标轴负数的负号显示问题）
if (sys.platform[0:3] == 'lin'):
locale.setlocale(locale.LC_CTYPE, 'zh_CN.utf8')
if (sys.platform[0:3] == 'win'):
locale.setlocale(locale.LC_CTYPE, 'chinese')
initTime = pd.to_datetime(str(
time_info['forecast_reference_time'].values)).replace(
tzinfo=None).to_pydatetime()
# draw figure
fig = plt.figure(figsize=(12, 12))
# draw main figure
#10米风——————————————————————————————————————
ax = plt.axes([0.1, 0.2, .8, .7])
utl.add_public_title_sta(title=model + '预报 ' + extra_info['point_name'] +
' [' + str(points['lon'][0]) + ',' +
str(points['lat'][0]) + ']',
initTime=initTime,
fontsize=21)
for ifhour in time_info['forecast_period'].values:
if (ifhour == time_info['forecast_period'].values[0]):
uv_t = (initTime + timedelta(hours=ifhour))
else:
uv_t = np.append(uv_t, (initTime + timedelta(hours=ifhour)))
wsp = (U**2 + V**2)**0.5
ax.plot(uv_t, np.squeeze(wsp), c='#40C4FF', linewidth=3)
if (extra_info['drw_thr'] == True):
ax.plot([uv_t[0], uv_t[-1]], [11, 11],
c='red',
label='警戒风速',
linewidth=1)
ax.barbs(uv_t,
wsp,
U,
V,
fill_empty=True,
color='gray',
barb_increments={
'half': 2,
'full': 4,
'flag': 20
})
xaxis_intaval = mpl.dates.HourLocator(byhour=(8, 20)) #单位是小时
ax.xaxis.set_major_locator(xaxis_intaval)
plt.xlim(uv_t[0], uv_t[-1])
# add legend
ax.legend(fontsize=15, loc='upper right')
ax.tick_params(length=10)
xstklbls = mpl.dates.DateFormatter('%m月%d日%H时')
for label in ax.get_xticklabels():
label.set_rotation(30)
label.set_horizontalalignment('center')
ax.tick_params(axis='y', labelsize=15)
ax.tick_params(axis='x', labelsize=15)
ax.grid()
ax.grid(axis='x', c='black')
miloc = mpl.dates.HourLocator(byhour=(11, 14, 17, 23, 2, 5)) #单位是小时
ax.xaxis.set_minor_locator(miloc)
ax.grid(axis='x', which='minor')
ax.set_ylabel('风速 (m/s)', fontsize=15)
utl.add_logo_extra_in_axes(pos=[0.1, 0.8, .1, .1],
which='nmc',
size='Xlarge')
#出图——————————————————————————————————————————————————————————
if (output_dir != None):
isExists = os.path.exists(output_dir)
if not isExists:
os.makedirs(output_dir)
output_dir2 = output_dir + model + '_起报时间_' + initTime.strftime(
"%Y年%m月%d日%H时") + '/'
if (os.path.exists(output_dir2) == False):
os.makedirs(output_dir2)
plt.savefig(output_dir2 + model + '_' + extra_info['point_name'] +
'_' + extra_info['output_head_name'] +
initTime.strftime("%Y%m%d%H") + '00' +
extra_info['output_tail_name'] + '.jpg',
dpi=200,
bbox_inches='tight')
else:
plt.show()
def draw_point_fcst(t2m=None,
u10m=None,
v10m=None,
rn=None,
model=None,
output_dir=None,
points=None,
extra_info=None):
plt.rcParams['font.sans-serif'] = ['SimHei'] # 步骤一（替换sans-serif字体）
plt.rcParams['axes.unicode_minus'] = False # 步骤二（解决坐标轴负数的负号显示问题）
if (sys.platform[0:3] == 'lin'):
locale.setlocale(locale.LC_CTYPE, 'zh_CN.utf8')
if (sys.platform[0:3] == 'win'):
locale.setlocale(locale.LC_CTYPE, 'chinese')
initTime = pd.to_datetime(str(
t2m['forecast_reference_time'].values)).replace(
tzinfo=None).to_pydatetime()
# draw figure
fig = plt.figure(figsize=(16, 4.5))
ax_t2m = HostAxes(fig, [0.1, 0.28, .8, .62])
ax_rn = ParasiteAxes(ax_t2m, sharex=ax_t2m)
#其他信息
#append axes
ax_t2m.parasites.append(ax_rn)
#invisible right axis of ax
ax_t2m.axis['right'].set_visible(False)
ax_t2m.axis['right'].set_visible(False)
ax_rn.axis['right'].set_visible(True)
ax_rn.axis['right'].major_ticklabels.set_visible(True)
ax_rn.axis['right'].label.set_visible(True)
#set label for axis
ax_t2m.set_ylabel('温度($^\circ$C)', fontsize=100)
ax_rn.set_ylabel('降水(mm)', fontsize=100)
fig.add_axes(ax_t2m)
# draw main figure
#2米温度——————————————————————————————————————
if (model == '中央台指导'):
model = '智能网格'
utl.add_public_title_sta(title=model + '预报 ' + extra_info['point_name'] +
' [' + str(points['lon'][0]) + ',' +
str(points['lat'][0]) + ']',
initTime=initTime,
fontsize=21)
for ifhour in t2m['forecast_period'].values:
if (ifhour == t2m['forecast_period'].values[0]):
t2m_t = (initTime + timedelta(hours=ifhour))
else:
t2m_t = np.append(t2m_t, (initTime + timedelta(hours=ifhour)))
curve_t2m = ax_t2m.plot(t2m_t,
np.squeeze(t2m['data'].values),
c='#FF6600',
linewidth=3,
label='2m温度')
ax_t2m.set_xlim(t2m_t[0], t2m_t[-1])
ax_t2m.set_ylim(
math.floor(t2m['data'].values.min() / 5) * 5 - 2,
math.ceil(t2m['data'].values.max() / 5) * 5)
#降水——————————————————————————————————————
for ifhour in rn['forecast_period'].values:
if (ifhour == rn['forecast_period'].values[0]):
rn_t = (initTime + timedelta(hours=ifhour))
else:
rn_t = np.append(rn_t, (initTime + timedelta(hours=ifhour)))
mask = (rn['data'] < 999)
rn = rn['data'].where(mask)
ax_rn.bar(rn_t,
np.squeeze(rn.values),
width=0.1,
color='#00008B',
label=str(
int(rn['forecast_period'].values[1] -
rn['forecast_period'].values[0])) + '小时降水',
alpha=0.5)
#curve_rn=ax_rn.plot(rn_t, np.squeeze(rn['data'].values), c='#40C4FF',linewidth=3)
ax_rn.set_ylim(0, np.nanmax(np.append(10, np.squeeze(rn.values))))
###
xaxis_intaval = mpl.dates.HourLocator(byhour=(8, 20)) #单位是小时
ax_t2m.xaxis.set_major_locator(xaxis_intaval)
# add legend
ax_t2m.legend(fontsize=15, loc='upper right')
ax_t2m.tick_params(length=10)
ax_t2m.tick_params(axis='y', labelsize=100)
ax_t2m.set_xticklabels([' '])
miloc = mpl.dates.HourLocator(byhour=(8, 11, 14, 17, 20, 23, 2, 5)) #单位是小时
ax_t2m.xaxis.set_minor_locator(miloc)
yminorLocator = MultipleLocator(1) #将此y轴次刻度标签设置为1的倍数
ax_t2m.yaxis.set_minor_locator(yminorLocator)
ymajorLocator = MultipleLocator(5) #将此y轴次刻度标签设置为1的倍数
ax_t2m.yaxis.set_major_locator(ymajorLocator)
ax_t2m.grid(axis='x', which='minor', ls='--')
ax_t2m.axis['left'].label.set_fontsize(15)
ax_t2m.axis['left'].major_ticklabels.set_fontsize(15)
ax_rn.axis['right'].label.set_fontsize(15)
ax_rn.axis['right'].major_ticklabels.set_fontsize(15)
#10米风——————————————————————————————————————
ax_uv = plt.axes([0.1, 0.16, .8, .12])
for ifhour in u10m['forecast_period'].values:
if (ifhour == u10m['forecast_period'].values[0]):
uv_t = (initTime + timedelta(hours=ifhour))
else:
uv_t = np.append(uv_t, (initTime + timedelta(hours=ifhour)))
wsp = (u10m**2 + v10m**2)**0.5
#curve_uv=ax_uv.plot(uv_t, np.squeeze(wsp['data'].values), c='#696969',linewidth=3,label='10m风')
ax_uv.barbs(uv_t,
np.zeros(len(uv_t)),
np.squeeze(u10m['data'].values),
np.squeeze(v10m['data'].values),
fill_empty=True,
color='gray',
barb_increments={
'half': 2,
'full': 4,
'flag': 20
},
length=5.8,
linewidth=1.5,
zorder=100)
ax_uv.set_ylim(-1, 1)
ax_uv.set_xlim(uv_t[0], uv_t[-1])
#ax_uv.axis('off')
ax_uv.set_yticklabels([' '])
#logo
utl.add_logo_extra_in_axes(pos=[0.87, 0.00, .1, .1],
which='nmc',
size='Xlarge')
#开启自适应
xaxis_intaval = mpl.dates.HourLocator(byhour=(8, 20)) #单位是小时
ax_uv.xaxis.set_major_locator(xaxis_intaval)
ax_uv.tick_params(length=5, axis='x')
ax_uv.tick_params(length=0, axis='y')
miloc = mpl.dates.HourLocator(byhour=(8, 11, 14, 17, 20, 23, 2, 5)) #单位是小时
ax_uv.xaxis.set_minor_locator(miloc)
ax_uv.grid(axis='x', which='both', ls='--')
ax_uv.set_ylabel('10m风', fontsize=15)
xstklbls = mpl.dates.DateFormatter('%m月%d日%H时')
for label in ax_uv.get_xticklabels():
label.set_rotation(30)
label.set_horizontalalignment('center')
ax_uv.tick_params(axis='x', labelsize=15)
#出图——————————————————————————————————————————————————————————
if (output_dir != None):
isExists = os.path.exists(output_dir)
if not isExists:
os.makedirs(output_dir)
output_dir2 = output_dir + model + '_起报时间_' + initTime.strftime(
"%Y年%m月%d日%H时") + '/'
if (os.path.exists(output_dir2) == False):
os.makedirs(output_dir2)
plt.savefig(output_dir2 + model + '_' + extra_info['point_name'] +
'_' + extra_info['output_head_name'] +
initTime.strftime("%Y%m%d%H") + '00' +
extra_info['output_tail_name'] + '.jpg',
dpi=200,
bbox_inches='tight')
else:
plt.show()
