# os 'keys' do dicionario hs_copa sao ordenados em ordem crescente
lista_crescente = sorted(hs_copa.keys())
del lista_crescente[0]
# direcao de ondas
dir_copa = sio.loadmat(path + '/dir_copa.mat')
del dir_copa['__header__'], dir_copa['__globals__'], dir_copa[
'__version__'] #, dir_copa['DIR_20160216_210000'] # generalizar esta data!
# converte as variaveis de direcao de graus para componentes u - v
u_componente = {}
v_componente = {}
for keys, values in dir_copa.items():
U, V = intdir2uv(values)
u_componente["u_{0}".format(keys[4:])] = U * (-1)
v_componente["v_{0}".format(keys[4:])] = V * (-1)
u_componente = collections.OrderedDict(sorted(u_componente.items()))
v_componente = collections.OrderedDict(sorted(v_componente.items()))
hs_copa = collections.OrderedDict(sorted(hs_copa.items()))
# gera e salva as imagens no diretorio
for x in range(40):
hs = hs_copa.values()[x]
u = u_componente.values()[x]
v = v_componente.values()[x]
fig = plt.figure()
plt.contourf(lon_bg_laje, lat_bg_laje, hs)
plt.quiver(lon_bg_laje, lat_bg_laje, u, v)
def plot(dst=False, filename=localpath + 'static/tmp_files/Data_month.csv_corrected'):
# dst=True
# filename = localpath + 'static/tmp_files/Data_month.csv_corrected'
window_len = 12
decmag = -22.3
# READING DATA
columns = defaultdict(list)
with open(filename,'rU') as f:
reader = csv.DictReader(f)
for row in reader:
for (k,v) in row.items():
columns[k].append(v)
varlist = ["gust", "wspd", "wdir", "cspd", "cdir", "sst"]
date_window = 7
tlim = -24 * date_window # put date_window as function argument
gust = np.array(map(float, columns.values()[7][tlim:]))
wspd = np.array(map(float, columns.values()[3][tlim:]))
wdir = np.array(map(float, columns.values()[19][tlim:]))
cspd = np.array(map(float, columns.values()[32][tlim:]))/100
cdir = np.array(map(float, columns.values()[6][tlim:]))
sst = np.array(map(float, columns.values()[9][tlim:]))
# loading full temperature measurements
depths = [0, 10, 15, 20, 25, 45]
f = open(filename)
lines = f.readlines()
SST = np.zeros((len(depths), sst.size-1))
c = 0
for t in range(tlim, -1):
SST[0,c] = float(lines[t].split(",")[-11])
SST[1,c] = float(lines[t].split(",")[-10])
SST[2,c] = float(lines[t].split(",")[-9])
SST[3,c] = float(lines[t].split(",")[-8])
SST[4,c] = float(lines[t].split(",")[-7])
SST[5,c] = float(lines[t].split(",")[-5])
c += 1
SST = remove_zeros(SST)
for k in range(len(depths)):
SST[k,:] = smooth(SST[k,:], 5)
# loading full current measurements
depths_c = [2, 10, 16, 20, 26, 30, 36]
f = open(filename)
lines = f.readlines()
CSPD = np.zeros((len(depths_c), cspd.size-1))
CDIR = np.zeros((len(depths_c), cspd.size-1))
c = 0
for t in range(tlim, -1):
CSPD[0,c] = float(lines[t].split(",")[21])
CSPD[1,c] = float(lines[t].split(",")[13])
CSPD[2,c] = float(lines[t].split(",")[14])
CSPD[3,c] = float(lines[t].split(",")[15])
CSPD[4,c] = float(lines[t].split(",")[16])
CSPD[5,c] = float(lines[t].split(",")[17])
CSPD[6,c] = float(lines[t].split(",")[18])
CDIR[0,c] = float(lines[t].split(",")[4])
CDIR[1,c] = float(lines[t].split(",")[5])
CDIR[2,c] = float(lines[t].split(",")[6])
CDIR[3,c] = float(lines[t].split(",")[7])
CDIR[4,c] = float(lines[t].split(",")[8])
CDIR[5,c] = float(lines[t].split(",")[9])
CDIR[6,c] = float(lines[t].split(",")[10])
c += 1
# CSPD = remove_zeros(CSPD)
# for k in range(len(depths_c)):
# CSPD[k,:] = smooth(CSPD[k,:], 5)
# CDIR = remove_zeros(CDIR)
# for k in range(len(depths_c)):
# CDIR[k,:] = smooth(CDIR[k,:], 5)
CU, CV = intdir2uv(CSPD, CDIR, decmag, 0)
time = columns.values()[44][tlim:]
year = dt.datetime.now().year
days, months, hours, minutes = [], [], [], []
datetime = []
for d in range(len(time)):
days.append(int(time[d].split()[0].replace('.','')[0:2]))
months.append(int(time[d].split()[0].replace('.','')[2:4]))
hours.append(int(time[d].split()[1].replace(':','')[0:2]))
minutes.append(int(time[d].split()[1].replace(':','')[2:4]))
datetime.append(dt.datetime(year, months[d], days[d], hours[d], minutes[d]))
years = list(np.array(days)*0 + year); del year
dates, datesnum = [], []
for year, month, day, hour, minute in zip(years, months, days, hours, minutes):
d = dt.datetime(year, month, day, hour)
dates.append( d )
datesnum.append( date2num(d) )
datetime = np.array(datetime)
datesnum = np.array(datesnum)
# PRE-PROCESSING DATA
for var in varlist:
if var != "sst":
exec('%s = remove_zeros(%s)' %(var, var))
exec('%s = smooth(%s, window_len)' %(var, var) )
else:
exec('%s = remove_zeros(%s)' %(var, var))
exec('%s = smooth(%s, 5)' %(var, var) )
# PLOTTING
fig = plt.figure(facecolor='w', figsize=(17,10))
plt.suptitle(u'Meteoceanographic Buoy ( SIODOC/IEAPM )\
\n$(lon: -42.18 \ \ lat: -22.99)$', fontsize='large')
#### PLOT WIND & GUST
ax = fig.add_subplot(311)
# print ax.get_position().bounds
plt.title(u'Wind & Gust (m/s)', fontsize='smaller')
# preparing arrays for colorfill
ymin = 0
ymax = 15
gy = np.linspace(ymin, ymax, 100)
gx, gy = np.meshgrid(datesnum, gy)
xlimit = np.linspace(0, gust.size, gust.size )
up = np.linspace(ymax+10, ymax+10, gust.size )
ax.contourf(gx, gy, gy, 100, alpha=1, cmap=plt.cm.hot_r)
ax.plot(datesnum, gust, 'w-')
ax.fill_between(datesnum, up, gust, color='w')
ax.plot(datesnum, wspd, 'k-', linewidth=2)
ax.set_axis_off()
ax.fill_between(datesnum, up, wspd, color='w', alpha=0.6)
# preparing arrays
wu, wv = intdir2uv(wspd, wdir, decmag, 0)
wu2, wv2 = intdir2uv(wspd * 0 + 5, wdir, decmag, 0)
wu2, wv2 = wu2 * -1, wv2 * -1
gust_label, wind_label = map(int,gust), map(int,wspd)
d = 5
for r, gl in enumerate(gust_label[::d]):
ax.annotate(gl, (datesnum[::d][r], gust[::d][r] + 0.5),
fontsize=10, fontstyle='italic', alpha=0.5, ha='center')
for i, wl in enumerate(wind_label[::d]):
ax.annotate(wl, (datesnum[::d][i], wspd[::d][i] - 1.2),
fontsize=10, fontstyle='italic', ha='center')
ax.quiver(datesnum[::5], wspd[::5] - 1.8, wu2[::5], wv2[::5],
width=0.0015, scale=400, pivot='middle')
plt.axis([datesnum.min(), datesnum.max(), 0, ymax])
####### PLOT SURFACE CURRENT
ax = fig.add_subplot(312)
# print ax.get_position().bounds
plt.title(u'Along-shelf surface flow (cm/s)', fontsize='smaller')
# preparing arrays for colorfill
cu, cv = intdir2uv(cspd, cdir, decmag, 0)
ymax = 0.5
cy = np.linspace(ymax*-1, ymax, 100)
x = np.linspace(0, cu.size, cu.size)
zr = np.linspace(0, 0, cu.size)
cx, cy = np.meshgrid(datesnum, cy)
down = np.linspace(ymax*-1 -1, ymax*-1 -1, cu.size)
up = np.linspace(ymax+1, ymax+1, cu.size)
plt.contourf(cx, cy, cy, 100, cmap=plt.cm.PRGn)
plt.plot(datesnum, cu, 'k-', linewidth=2)
uplim, downlim = fill_polygons(cu)
plt.fill_between(datesnum, down, uplim, color='w')
plt.fill_between(datesnum, up, downlim, color='w')
ax.set_axis_off()
yoffset = ymax*0.1
curr_label = []
uan = np.abs(cu*100)
for l in range(len(cu)):
curr_label.append("%2d" %uan[l])
d = 5
for r, cl in enumerate(curr_label[::d]):
if cu[::d][r] >= 0:
off = yoffset
else:
off = yoffset*-2
ax.annotate(cl, (datesnum[::d][r], cu[::d][r]+off),
fontsize=10, fontstyle='italic', ha='center')
# preparing arrays
ux = cu*0
ux[np.where(ux > 0)] = 1
ux[np.where(ux < 0)] = -1
cu2, cv2 = intdir2uv(cspd*0 + 0.5, cdir, decmag, 0)
for r in np.arange(0, cu.size, d):
if cu[r] <= 0:
off = yoffset*2
else:
off = yoffset*-2
plt.quiver(datesnum[r], cu[r]+off, cu2[r], cv2[r],
width=0.0015, scale=40, pivot='middle')
plt.axis([datesnum.min(), datesnum.max(), ymax*-1, ymax])
######## PLOT TEMP
ax = fig.add_subplot(313)
# print ax.get_position().bounds
plt.title(u'Sea surface temperature ($^\circ$C)', fontsize='smaller')
# preparing arrays for colorfill
ymin = 12
ymax = 28
tempy = np.linspace(ymin, ymax, 100)
tempx, tempy = np.meshgrid(datesnum, tempy)
uplim = np.linspace(ymax+2, ymax+2, sst.size)
ax.contourf(tempx, tempy, tempy, 60, cmap=plt.cm.RdBu_r)
plt.plot(datesnum, sst, 'k-', linewidth=2)
plt.fill_between(datesnum, uplim, sst, color= 'w')
d = 5
yoffset = ymax*0.03
temp_label = map(int, sst)
for i, tl in enumerate(temp_label[::d]):
ax.annotate(tl, (datesnum[::d][i], sst[::d][i]+yoffset),
fontsize=10, fontstyle='italic', ha='center')
ax.set_axis_off()
# plotting dates
ax = fig.add_axes([0.125, 0.04, 0.775, 0.05])
ax.plot(datesnum, sst*0, 'w')
ax.set_axis_off()
for d in np.arange(0, datesnum.size, 24):
label = dates[d].strftime('%d/%b')
ax.annotate(label, (datesnum[d], -0.8),
fontweight='bold', ha='center')
for d in np.arange(0, datesnum.size, 4):
label = dates[d].strftime('%Hh')
ax.annotate(label, (datesnum[d], 0.6), ha='center', fontsize=8)
plt.axis([datesnum[0], datesnum[-1], -1, 1])
# plotting rise and set shades
rise_and_set = []
for i in np.arange(0, datesnum.size, 24):
day = dt.date(years[i], months[i], days[i])
rise, sett = get_rise_set(day, dst)
rise, sett = date2num(rise), date2num(sett)
rise_and_set.append([rise, sett])
ax = fig.add_axes([0.125, 0.07, 0.781, 0.8])
night_fill(ax, rise_and_set, datesnum, ymin, ymax)
ax.set_axis_off()
plt.savefig(localpath + 'static/images/siodoc_tmp.png', dpi=96)
########################################################################
fig = plt.figure(facecolor='w', figsize=(17,10))
plt.suptitle(u'Meteoceanographic Buoy ( SIODOC/IEAPM )\
\n$(lon: -42.18 \ \ lat: -22.99)$', fontsize='large')
# preparing arrays
x, z = np.meshgrid(datesnum[:-1], np.array(depths))
ax = fig.add_subplot(311)
plt.plot_date(datesnum[:-1], wspd[:-1]*0 + 17, 'w')
plt.title(u'Temperature ($^\circ$C)', fontsize='smaller')
plt.contourf(x, -z, SST, np.arange(10, 25, 0.1))
plt.colorbar(orientation='horizontal', aspect=40, shrink=0.5)
plt.contour(x, -z, SST, [20, 20], colors='k')
plt.ylabel("Depth [m]")
plt.axis([datesnum[0], datesnum[-1], -45, 0])
ax = fig.add_axes([0.125, 0.1, 0.775, 0.5])
plt.title(u'Velocity (cm/s)', fontsize='smaller')
plt.ylabel("Depth [m]")
c = 0
j = 2
for d in depths_c:
plt.quiver(datesnum[::j], datesnum[::j]*0-d,
CU[c,::j], CV[c,::j], width=0.001, scale=1200)
c += 1
plt.quiver(datesnum[-10], -5, -50, 0, width=0.003, scale=1200)
plt.text(datesnum[-19], -7, "50 cm/s")
plt.axis([datesnum[0], datesnum[-1], -45, 5])
# ax.set_axis_off()
ax.set_xticklabels([])
ax = fig.add_axes([0.125, 0.07, 0.781, 0.83])
night_fill(ax, rise_and_set, datesnum, ymin, ymax)
ax.set_axis_off()
# plotting dates
ax = fig.add_axes([0.125, 0.04, 0.775, 0.05])
ax.plot(datesnum, sst*0, 'w')
ax.set_axis_off()
for d in np.arange(0, datesnum.size, 24):
label = dates[d].strftime('%d/%b')
ax.annotate(label, (datesnum[d], -0.8),
fontweight='bold', ha='center')
for d in np.arange(0, datesnum.size, 4):
label = dates[d].strftime('%Hh')
ax.annotate(label, (datesnum[d], 0.6), ha='center', fontsize=8)
plt.axis([datesnum[0], datesnum[-1], -1, 1])
plt.savefig(localpath + 'static/images/siodoc_full.png', dpi=96)
plt.close('all')
def plot(filename=localpath + 'static/tmp_files/Data_month.csv_corrected'):
columns = defaultdict(list)
with open(filename,'rU') as f:
reader = csv.DictReader(f)
for row in reader:
for (k,v) in row.items():
columns[k].append(v)
varlist = ["gust", "wspd", "wdir", "cspd", "cdir", "sst"]
date_window = 7
tlim = -24 * date_window # put date_window as function argument
gust = np.array(map(float, columns.values()[7][tlim:]))
wspd = np.array(map(float, columns.values()[3][tlim:]))
wdir = np.array(map(float, columns.values()[19][tlim:]))
cspd = np.array(map(float, columns.values()[32][tlim:]))/100
cdir = np.array(map(float, columns.values()[6][tlim:]))
sst = np.array(map(float, columns.values()[9][tlim:]))
time = columns.values()[44][tlim:]
year = dt.datetime.now().year
days, months, hours, minutes = [], [], [], []
datetime = []
for d in range(len(time)):
days.append(int(time[d].split()[0].replace('.','')[0:2]))
months.append(int(time[d].split()[0].replace('.','')[2:4]))
hours.append(int(time[d].split()[1].replace(':','')[0:2]))
minutes.append(int(time[d].split()[1].replace(':','')[2:4]))
datetime.append(dt.datetime(year, months[d], days[d], hours[d], minutes[d]))
datetime = np.array(datetime)
window_len = 12
decmag = -22.3
for var in varlist:
if var != "sst":
exec('%s = remove_zeros(%s)' %(var, var))
exec('%s = smooth(%s, window_len)' %(var, var) )
else:
exec('%s = remove_zeros(%s)' %(var, var))
exec('%s = smooth(%s, 5)' %(var, var) )
#### PLOT WIND & GUST
fig = plt.figure(facecolor='w', figsize=(17,10))
plt.suptitle(u'Meteoceanographic Buoy ( SIODOC/IEAPM )\
\n$(lon: -42.18 \ \ lat: -22.99)$', fontsize='large')
ax = fig.add_subplot(311)
plt.title(u'Wind & Gust (m/s)', fontsize='smaller')
gx = np.linspace(min(gust), max(gust), len(gust))
gy = np.linspace(min(gust), max(gust), round(max(gust) + 2 ))
gx, gy = np.meshgrid(gx, gy)
xlimit = np.linspace(0, len(gust), len(gust) )
ylimit = gx[0,-1]
up = np.linspace(ylimit, ylimit, len(gust))
ax.contourf(gy, 100, alpha=1, cmap=plt.cm.hot_r)
ax.plot(xlimit, gust, 'w-')
ax.set_axis_off()
ax.fill_between(xlimit, up, gust, color='w')
ax.plot(xlimit, wspd, 'k-', linewidth=2)
ax.set_axis_off()
ax.fill_between(xlimit, up, wspd, color='w', alpha=0.6)
wu, wv = intdir2uv(wspd, wdir, decmag, 0)
wu2, wv2 = intdir2uv(wspd * 0 + 5, wdir, decmag, 0)
wu2, wv2 = wu2 * -1, wv2 * -1
gust_label, wind_label = map(int,gust), map(int,wspd)
for r, gust_txt in enumerate(gust_label[::5]):
ax.annotate(gust_txt, (xlimit[::5][r] - 0.4, gust[::5][r] + 0.5),
fontsize=10, fontstyle='italic', alpha=0.5, ha='center')
for i, wind_txt in enumerate(wind_label[::5]):
ax.annotate(wind_txt, (xlimit[::5][i] - 0.6, wspd[::5][i] - 1.2),
fontsize=10, fontstyle='italic', ha='center')
ax.quiver(xlimit[::5], wspd[::5] - 2.2, wu2[::5], wv2[::5],width=0.0015, scale=400)
plt.axis([xlimit.min(), xlimit.max(), 0, gust.max()])
####### PLOT CORRENTE
ax = fig.add_subplot(312)
plt.title(u'Along-shelf surface flow (cm/s)', fontsize='smaller')
cu, cv = intdir2uv(cspd, cdir, decmag, 0)
cx = np.linspace(min(cu), max(cu), len(cu))
cy = np.linspace(round(min(cu))-0.1, round(max(cu))+0.1, 2)
x = np.linspace(0, len(cu), len(cu))
zr = np.linspace(0, 0, len(cu))
curr_cf = np.meshgrid(cx, cy)
down = np.linspace(min(cu)-0.5, min(cu)-0.5, len(cu))
up = np.linspace(max(cu)+1, max(cu)+1, len(cu))
if np.all([cu > 0]):
plt.contourf(x, cy, curr_cf[1],100,alpha=0.5, cmap=plt.cm.Greens)
elif np.all([cu < 0]):
plt.contourf(x, cy, curr_cf[1],100,alpha=0.5, cmap=plt.cm.Purples_r)
else:
plt.contourf(x, cy, curr_cf[1],100,alpha=0.5, cmap=plt.cm.PRGn)
plt.plot_date(x, cu, 'k-', linewidth=2)
uplim, downlim = fill_polygons(cu)
plt.fill_between(x, down, uplim,color='w')
plt.fill_between(x, up, downlim,color='w')
ax.set_axis_off()
curr_label = []
uan = np.abs(cu*100)
for l in range(len(cu)):
curr_label.append("%2d" %uan[l])
for r, txt_curr in enumerate(curr_label[::10]):
ax.annotate(txt_curr, (x[::10][r], cu[::10][r] + 0.15),
fontsize=10, fontstyle='italic', ha='center')
ux = cu*0
ux[np.where(ux > 0)] = 1
ux[np.where(ux < 0)] = -1
cu2, cv2 = intdir2uv(cspd*0 + 0.5, cdir, decmag, 0)
plt.quiver(x[::5], cu[::5]-0.2, cu2[::5], cv2[::5], width=0.0015, scale=40)
######## PLOT TEMP
ax = fig.add_subplot(313)
plt.title(u'Sea surface temperature ($^\circ$C)', fontsize='smaller')
tempx = np.linspace(min(sst), max(sst), len(sst))
tempy = np.linspace(round(min(sst))-0.5, round(max(sst)) + 0.5, 24) #round(min(sst))
x = np.linspace(0, len(sst), len(sst))
temp_cf = np.meshgrid(tempx, tempy)
uplim = np.linspace(round(max(sst)) + 1, round(max(sst)) + 1, len(sst))
if np.all([ sst > 20]):
plt.contourf(x, tempy, temp_cf[1], 60, alpha=0.8, cmap=plt.cm.Reds)
elif np.all([sst <= 20]):
plt.contourf(x, tempy, temp_cf[1], 60, alpha=0.8, cmap=plt.cm.Blues_r)
else:
plt.contourf(x, tempy, temp_cf[1], 60, alpha=0.8, cmap=plt.cm.RdBu_r)
plt.plot(x, sst,'k-', linewidth=2)
plt.fill_between(x, uplim, sst, color= 'w')
temp_label = map(int, sst)
for i, txt_temp in enumerate(temp_label[::10]):
ax.annotate(txt_temp, (x[::10][i]-0.4, sst[::10][i]+0.5),
fontsize=10, fontstyle='italic', ha='center')
nbs = 60
plt.locator_params(axis='x', nbins=nbs)
fig.canvas.draw()
# index = [item.get_text() for item in ax.get_xticklabels()]
# index = map(int, index)
# index[-1] = index[-1]-1
# lab = [datetime[i] for i in index]
# label = [l.strftime('%d') for l in lab]
# labels = map(int, np.ones((61)))
# for c in np.arange(0,61,3):
# labels[c] = label[c]
# try:
# labels[c+1] = ''
# labels[c+2] = ''
# except:
# 'IndexError'
# ax.set_yticklabels("")
# ax.set_xticklabels(labels, fontsize='smaller', fontweight='bold')
# ax.set_xlabel('\nNov/Dez 2013', fontsize='smaller', fontweight='semibold')
ax.set_frame_on(False)
plt.savefig(localpath + 'static/images/siodoc_tmp.png', dpi=96)
plt.close('all')
