def draw(self, fig):
""" Draw windrose plot of current data on figure """
try:
axes = WindroseAxes(fig, rect=[0.1, 0.1, 0.8, 0.8])
fig.add_axes(axes)
axes.bar(self.direction, self.windspeed, normed=True)
axes.set_title("Windrose (by % in 6 bins)")
legend = axes.legend(borderaxespad=-0.10, fontsize=8, bbox_to_anchor=(-0.2, 0))
legend_title = "Wind Speed"
try:
#Try adding a unit to the legend title
units = self.configmanager.get_units() # Get unit strings from config
legend_title = legend_title + " " + units["Wind Speed"].strip()
except (KeyError, ValueError):
pass # If no units exists, or the config isn't valid, just use title without units
legend.set_title(legend_title, prop={"size":8})
except:
raise
def all_sta_wind_rose():
fig = plt.figure(figsize=(16, 16))
rect = [[0.05, 0.55, 0.35, 0.35], [0.55, 0.55, 0.35, 0.35], [0.05, 0.05, 0.35, 0.35], [0.55, 0.05,0.35, 0.35]]
plot = 0
for station in station_dict.keys():
wa = WindroseAxes(fig, rect[plot])
fig.add_axes(wa)
ANN, DJF, MAM, JJA, SON = load_AWS(station)
# define data limits
max_mod = max(ANN['FF_10m'])
wa.set_title(station_dict[station], fontsize=28, color='dimgrey', pad=50)
wa.axes.spines['polar'].set_visible(False)
wa.tick_params(axis='both', which='both', labelsize=20, tick1On=False, tick2On=False, labelcolor='dimgrey', pad=10)
wa.bar(ANN['WD'], ANN['FF_10m'], bins=np.arange(0, 20, 4), cmap=plt.get_cmap('viridis'), normed=True, opening=0.8, edgecolor='white')
wa.set_yticks([5,10,15])
wa.set_yticklabels([ '', '10%', '15%'])
plot = plot + 1
lgd = wa.set_legend(bbox_to_anchor=(-0.45, 1.))
frame = lgd.get_frame()
frame.set_facecolor('white')
for ln in lgd.get_texts():
plt.setp(ln, color='dimgrey', fontsize=24)
lgd.get_frame().set_linewidth(0.0)
if host == 'bsl':
plt.savefig('/users/ellgil82/figures/Hindcast/Validation/wind_rose_all_stations_all_years.png')
plt.savefig('/users/ellgil82/figures/Hindcast/Validation/wind_rose_all_stations_all_years.eps')
elif host == 'jasmin':
plt.savefig('/gws/nopw/j04/bas_climate/users/ellgil82/hindcast/figures/wind_rose_all_stations_all_years.png')
plt.savefig('/gws/nopw/j04/bas_climate/users/ellgil82/hindcast/figures/wind_rose_all_stations_all_years.eps')
plt.show()
def plotter(fdict):
""" Go """
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
from windrose import WindroseAxes
from matplotlib.patches import Rectangle
ctx = get_context(fdict)
fig = plt.figure(figsize=(6, 7.2), facecolor='w', edgecolor='w')
rect = [0.08, 0.1, 0.8, 0.8]
ax = WindroseAxes(fig, rect, axisbg='w')
fig.add_axes(ax)
ax.bar(ctx['df']['drct'].values, ctx['df']['smph'].values,
normed=True, bins=[0, 2, 5, 7, 10, 15, 20], opening=0.8,
edgecolor='white', nsector=18)
handles = []
for p in ax.patches_list:
color = p.get_facecolor()
handles.append(Rectangle((0, 0), 0.1, 0.3,
facecolor=color, edgecolor='black'))
legend = fig.legend(handles,
('2-5', '5-7', '7-10', '10-15', '15-20', '20+'),
loc=(0.01, 0.03), ncol=6,
title='Wind Speed [%s]' % ('mph',),
mode=None, columnspacing=0.9, handletextpad=0.45)
plt.setp(legend.get_texts(), fontsize=10)
plt.gcf().text(0.5, 0.99, ctx['plottitle'],
fontsize=16, ha='center', va='top')
plt.gcf().text(0.95, 0.12, "n=%s" % (len(ctx['df'].index),),
verticalalignment="bottom", ha='right')
return fig, ctx['df']
def wind_rose(station, AWS_var, model_var):
fig = plt.figure(figsize = (16,8))
rect = [0.05, 0.1, 0.45, 0.6]
wa = WindroseAxes(fig, rect)
fig.add_axes(wa)
# define data limits
max_mod = max(np.mean(vars_yr['FF_10m'][:,lat_index14-1:lat_index14+1, lon_index14-1:lon_index14+1].data, axis = (1,2)))
max_obs = max(AWS_var['FF'])
wa.set_title('Observed', fontsize = 28, color = 'dimgrey', pad = 50)
wa.axes.spines['polar'].set_visible(False)
wa.tick_params(axis='both', which='both', labelsize=24, tick1On=False, tick2On=False, labelcolor='dimgrey', pad=10)
wa.bar(AWS_var['WD'], AWS_var['FF'], bins = np.arange(0, max(max_mod, max_obs),4), cmap = plt.get_cmap('viridis'), normed = True,opening=0.8, edgecolor='white')
wa.set_yticklabels([])
rect = [0.55, 0.1, 0.45, 0.6]
wa = WindroseAxes(fig, rect)
fig.add_axes(wa)
wa.set_title('Modelled', fontsize=28, color='dimgrey', pad = 50)
wa.bar(np.mean(vars_yr['WD'][:,lat_index14-1:lat_index14+1, lon_index14-1:lon_index14+1].data, axis = (1,2)),
np.mean(vars_yr['FF_10m'][:,lat_index14-1:lat_index14+1, lon_index14-1:lon_index14+1].data, axis = (1,2)),
bins = np.arange(0, max(max_mod, max_obs),4), cmap = plt.get_cmap('viridis'), normed = True, opening=0.8, edgecolor='white')
lgd = wa.set_legend( bbox_to_anchor=(-0.5, 0.9))
frame = lgd.get_frame()
frame.set_facecolor('white')
for ln in lgd.get_texts():
plt.setp(ln, color='dimgrey', fontsize = 18)
lgd.get_frame().set_linewidth(0.0)
wa.axes.spines['polar'].set_visible(False)
wa.set_yticklabels([])
wa.tick_params(axis='both', which='both', labelsize=24, tick1On=False, tick2On=False, labelcolor='dimgrey', pad=10)
plt.savefig('/users/ellgil82/figures/Hindcast/validation/wind_rose_' + station + '_' + year + '.png')
plt.savefig('/users/ellgil82/figures/Hindcast/validation/wind_rose_' + station + '_' + year + '.eps')
plt.show()
def rose_diagram(self, direction, norm):
"""
Plot rose diagram
Inputs:
------
- direction = 1D array
- norm = 1D array
"""
#Convertion
#TR: not quite sure here, seems to change from location to location
# express principal axis in compass
direction = np.mod(90.0 - direction, 360.0)
#Create new figure
fig = plt.figure(figsize=(18,10))
plt.rc('font',size='22')
rect = [0.1, 0.1, 0.8, 0.8]
ax = WindroseAxes(fig, rect)#, axisbg='w')
fig.add_axes(ax)
#Rose
ax.bar(direction, norm , normed=True, opening=0.8, edgecolor='white')
#adjust legend
l = ax.legend(shadow=True, bbox_to_anchor=[-0.1, 0], loc='lower left')
plt.setp(l.get_texts(), fontsize=10)
plt.xlabel('Rose diagram in % of occurrences - Colormap of norms')
plt.show()
def rose_diagram(self, direction, norm):
"""
Plot rose diagram
Inputs:
- direction = 1D array
- norm = 1D array
"""
#Convertion
#TR: not quite sure here, seems to change from location to location
# express principal axis in compass
direction = np.mod(90.0 - direction, 360.0)
#Create new figure
self._def_fig()
rect = [0.1, 0.1, 0.8, 0.8]
ax = WindroseAxes(self._fig, rect)#, axisbg='w')
self._fig.add_axes(ax)
#Rose
ax.bar(direction, norm , normed=True, opening=0.8, edgecolor='white')
#adjust legend
l = ax.legend(shadow=True, bbox_to_anchor=[-0.1, 0], loc='lower left')
plt.setp(l.get_texts(), fontsize=10)
plt.xlabel('Rose diagram in % of occurrences - Colormap of norms')
self._plt.show()
def plotter(fdict):
""" Go """
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
from windrose import WindroseAxes
from matplotlib.patches import Rectangle
ctx = get_context(fdict)
fig = plt.figure(figsize=(6, 7.2), facecolor='w', edgecolor='w')
rect = [0.08, 0.1, 0.8, 0.8]
ax = WindroseAxes(fig, rect, axisbg='w')
fig.add_axes(ax)
ax.bar(ctx['df']['drct'].values, ctx['df']['smph'].values,
normed=True, bins=[0, 2, 5, 7, 10, 15, 20], opening=0.8,
edgecolor='white', nsector=18)
handles = []
for p in ax.patches_list:
color = p.get_facecolor()
handles.append(Rectangle((0, 0), 0.1, 0.3,
facecolor=color, edgecolor='black'))
l = fig.legend(handles,
('2-5', '5-7', '7-10', '10-15', '15-20', '20+'),
loc=(0.01, 0.03), ncol=6,
title='Wind Speed [%s]' % ('mph',),
mode=None, columnspacing=0.9, handletextpad=0.45)
plt.setp(l.get_texts(), fontsize=10)
plt.gcf().text(0.5, 0.99, ctx['plottitle'],
fontsize=16, ha='center', va='top')
plt.gcf().text(0.95, 0.12, "n=%s" % (len(ctx['df'].index),),
verticalalignment="bottom", ha='right')
return fig, ctx['df']
def main():
loc = 'fl0'
weatherDir = '/data1/ancillary_data/fl0/eol/'
weatherFileTag = 'v2'
iyear = 2010
fyear = 2010
wdir, wspeed, temp, rh, dtw = weatherout(loc, weatherDir, weatherFileTag,
iyear, fyear)
hours = []
for k in dtw:
hours.append(k.hour)
hours = np.asarray(hours)
inds = np.where((wspeed <= 10.0) & (hours > 8) & (hours < 18))[0]
fig = plt.figure(figsize=(8, 8), dpi=80, facecolor='w', edgecolor='w')
rect = [0.1, 0.1, 0.8, 0.8]
ax = WindroseAxes(fig, rect, axisbg='w')
fig.add_axes(ax)
ax.bar(wdir[inds],
wspeed[inds],
normed=True,
opening=0.9,
edgecolor='white')
ax.set_legend()
#fig2 = plt.figure(figsize=(8, 8), dpi=80, facecolor='w', edgecolor='w')
ax2 = WindAxes.from_ax()
bins = np.arange(0, 10, 0.5)
bins = bins[1:]
ax2, params = ax2.pdf(wspeed[inds], bins=bins)
ax3 = WindAxes.from_ax()
bins = np.arange(0, 360, 15)
bins = bins[1:]
ax3, params = ax3.pdf(wdir[inds], bins=bins)
# fig2, ax2 = plt.subplots(figsize=(8,6))
# ax2.scatter(wdir, wspeed, facecolors='red', edgecolors='black', s=35)
# ax2.grid(True)
plt.show(block=False)
pdfsav = PdfPages('/data/iortega/results/fl0/windrose.pdf')
pdfsav.savefig(fig, dpi=200)
pdfsav.close()
user_input = raw_input('Press any key to exit >>> ')
sys.exit()
def plot_roses(filename,
vdir,
mag,
nsector=16,
bins=10,
title=None,
legtitle=None,
dpi=150,
figsize=(10, 10),
tfont=17,
lfont=14):
"""
Plots the rose chart
from wind data and
saves it to png file.
"""
fig = plt.figure(figsize=figsize)
# [left, bottom, width, height] as a fraction of total figure size
right_rectangle = [0.05, 0.05, 0.85, 0.8]
ax = WindroseAxes(fig, right_rectangle)
fig.add_axes(ax)
# ax.bar(wind['dir'], wind['sp'], normed=True, opening=0.9, edgecolor='white', bins=np.logspace(-1,1.3, 10), nsector=16)
# ax.bar(wind['dir'], wind['sp'], normed=True, opening=0.9, edgecolor='white', bins=np.linspace(0,max(wind['sp']), 10), nsector=16)
ax.bar(vdir,
mag,
normed=True,
opening=0.9,
edgecolor='white',
bins=bins,
nsector=nsector)
if title:
ax.set_title("{}".format(title), position=(0.5, 1.1), fontsize=tfont)
cfont = max([8, lfont - 2])
ax.tick_params(axis='both', which='major', labelsize=cfont)
ax.set_legend()
if legtitle:
ax.legend(title='{}'.format(legtitle), loc=(0.0, 0.0))
#used to pretty up the printing around of wind occurent frequencies
tictic = ax.get_yticks()
ax.set_yticks(np.arange(0, tictic[-1], tictic[-1] / len(tictic)))
ax.yaxis.set_major_formatter(tkr.FormatStrFormatter('%2.0f'))
if isinstance(filename, list):
for item in filename:
fig.savefig(item, dpi=dpi)
else:
fig.savefig(filename, dpi=dpi)
plt.close()
return 0
def wros(self, ws, wd, maxi=10, dev=None, date=None, base=None):
'''Plot a wind rose given an array of wind speed and wind direction'''
fig = plt.figure(figsize=(30, 30),
dpi=150,
facecolor='w',
edgecolor='w')
rect = [0.1, 0.1, 0.8, 0.8]
ax = WindroseAxes(fig, rect, axisbg='w')
fig.add_axes(ax, fontsize=12)
try:
ax.bar(wd,
ws,
normed=True,
opening=1,
edgecolor='white',
bins=[0, 2, 6, 12, 20, 29, 39, 50])
ax.set_rmax(12)
ax.set_radii_angle()
l = ax.legend(loc=(1, 0))
if self.periods == None:
if base != None and date != None:
title = 'Wind rose at ' + str(
self.height) + 'm and at ' + str(
self.selected_cell[0]) + ' in ' + str(
date) + ' during the ' + str(
base) + ' by ' + str(dev)
elif base != None:
title = 'Wind rose at ' + str(
self.height) + 'm and at ' + str(
self.selected_cell[0]) + ' during the ' + str(
base) + ' by ' + str(dev)
elif date != None:
title = 'Wind rose at ' + str(
self.height) + 'm and at ' + str(
self.selected_cell[0]) + ' in ' + str(
date) + ' by ' + str(dev)
else:
title = 'Wind rose at ' + str(
self.height) + 'm and at ' + str(
self.selected_cell[0]) + ' by ' + str(dev)
else:
title = 'Wind statistics at ' + str(
self.height) + 'm and at ' + str(
self.selected_cell[0]) + str(
self.periods) + ' by ' + str(dev)
plt.setp(l.get_texts(), fontsize=12)
plt.title(title, fontsize=12, y=1.07)
plt.show()
except ValueError:
print 'No windrose for ' + str(dev)
def main():
loc = 'fl0'
weatherDir = '/data1/ancillary_data/fl0/eol/'
weatherFileTag = 'v2'
iyear = 2010
fyear = 2016
wdir, wspeed, temp, rh, dtw = weatherout(loc, weatherDir, weatherFileTag, iyear, fyear )
hours = []
for k in dtw:
hours.append(k.hour)
hours = np.asarray(hours)
inds = np.where( (wspeed <= 10.0) & (hours > 8) & (hours < 18) )[0]
fig = plt.figure(figsize=(8, 8), dpi=80, facecolor='w', edgecolor='w')
rect = [0.1, 0.1, 0.8, 0.8]
ax = WindroseAxes(fig, rect, axisbg='w')
fig.add_axes(ax)
ax.bar(wdir[inds], wspeed[inds], normed=True, opening=0.9, edgecolor='white')
ax.set_legend()
#fig2 = plt.figure(figsize=(8, 8), dpi=80, facecolor='w', edgecolor='w')
ax2 = WindAxes.from_ax()
bins = np.arange(0, 10 , 0.5)
bins = bins[1:]
ax2, params = ax2.pdf(wspeed[inds], bins=bins)
ax3 = WindAxes.from_ax()
bins = np.arange(0, 360, 15)
bins = bins[1:]
ax3, params = ax3.pdf(wdir[inds], bins=bins)
# fig2, ax2 = plt.subplots(figsize=(8,6))
# ax2.scatter(wdir, wspeed, facecolors='red', edgecolors='black', s=35)
# ax2.grid(True)
plt.show(block=False)
pdfsav = PdfPages('/data/iortega/results/fl0/windrose.pdf')
pdfsav.savefig(fig,dpi=200)
pdfsav.close()
user_input = raw_input('Press any key to exit >>> ')
sys.exit()
def plotter(fdict):
""" Go """
ctx = get_context(fdict)
fig = plt.figure(figsize=(6, 7.2), facecolor="w", edgecolor="w")
rect = [0.08, 0.1, 0.8, 0.8]
ax = WindroseAxes(fig, rect, facecolor="w")
fig.add_axes(ax)
ax.bar(
ctx["df"]["drct"].values,
ctx["df"]["smph"].values,
normed=True,
bins=[0, 2, 5, 7, 10, 15, 20],
opening=0.8,
edgecolor="white",
nsector=18,
)
handles = []
for p in ax.patches_list:
color = p.get_facecolor()
handles.append(
Rectangle((0, 0), 0.1, 0.3, facecolor=color, edgecolor="black"))
legend = fig.legend(
handles,
("2-5", "5-7", "7-10", "10-15", "15-20", "20+"),
loc=(0.01, 0.03),
ncol=6,
title="Wind Speed [%s]" % ("mph", ),
mode=None,
columnspacing=0.9,
handletextpad=0.45,
)
plt.setp(legend.get_texts(), fontsize=10)
plt.gcf().text(0.5,
0.99,
ctx["plottitle"],
fontsize=16,
ha="center",
va="top")
plt.gcf().text(
0.95,
0.12,
"n=%s" % (len(ctx["df"].index), ),
verticalalignment="bottom",
ha="right",
)
return fig, ctx["df"]
def animate_windrose_graph(i):
all_data_map=data_service.get_all_data_map()
is_active = data_service.get_active()
if is_active == "1_3":
data_service.update_all_data_map(data_service.get_start_date(), data_service.get_end_date())
ws = my_service.restore_lost_data(all_data_map['FF'])
wd = my_service.restore_lost_data(all_data_map['dd'])
ws_scale_1 = tab1_service.map_speed_to_scale_one(ws)
wd = tab1_service.map_compass_to_degrees(wd)
# hide axes
windrose_graph_fig.patch.set_visible(False)
windrose_graph_ax.axis('off')
windrose_graph_ax.axis('tight')
ws_frequency_map = tab1_service.map_ws_by_frequency(ws)
final_data = [list(ws_frequency_map.keys()), list(ws_frequency_map.values())]
table = windrose_graph_ax.table(cellText=final_data, loc='top', cellLoc='center',
rowLabels=[" м/с ", " % "], bbox=[0., 0., 0.23, .28])
windrose_graph_fig.subplots_adjust(bottom=0.6)
table.auto_set_font_size(False)
table.set_fontsize(7)
for (row, col), cell in table.get_celld().items():
if row == 0:
cell.set_text_props(fontproperties=FontProperties(weight='normal', size=7))
for key, cell in table.get_celld().items():
cell.set_linewidth(0.5)
# windrose_graph_fig.clear()
rect = [0.1, 0.1, 0.8, 0.8]
wa = WindroseAxes(windrose_graph_fig, rect)
windrose_graph_fig.add_axes(wa)
windrose_graph_ax.grid()
wa.bar(wd, ws_scale_1, normed=True, opening=0.8, edgecolor='white')
# wa.set_legend()
wa.set_legend(title="інтенсивність", loc="upper right")
tstr = '%s Visibility' % (stns[j])
pyplot.title(tstr, size=14)
pngnm = '%s_VisHist.png' % (stns[j])
fig.savefig(pngnm, bbox_inches=0)
pyplot.close()
# A Rose?
fig = pyplot.figure(figsize=(7.5, 6), facecolor='w', edgecolor='w')
rect = [0.08, 0.1, 0.8, 0.8]
ax = WindroseAxes(fig, rect, facecolor='w')
fig.add_axes(ax)
ax.bar(wndsb['WindDir'],
wndsb['Visibility'],
normed=True,
bins=[0, 0.3, 1.1, 2.1, 3.1, 4.1, 5.1],
opening=0.8,
edgecolor='white',
nsector=18,
cmap=rdmp)
# ax.set_legend()
handles = []
for p in ax.patches_list:
color = p.get_facecolor()
handles.append(
Rectangle((0, 0), 0.1, 0.3, facecolor=color,
edgecolor='black'))
legend = fig.legend(handles, ('< 0.5', '0.5-1.0', '1.0-2.0', '2.0-3.0',
'3.0-4.0', '4.0-5.0', '> 5.0'),
loc=(0.75, 0.03),
ncol=2,
title='Visibility',
from windrose import WindroseAxes
from matplotlib import pyplot as plt
import matplotlib.cm as cm
import numpy as np
from windrose import WindroseAxes
from matplotlib import pyplot as plt
import numpy as np
kmh_to_ms = 0.277778
# Decembre 2020
ws = [
5.6 * kmh_to_ms, 6.8 * kmh_to_ms, 6.4 * kmh_to_ms, 4.5 * kmh_to_ms,
3.5 * kmh_to_ms, 5 * kmh_to_ms, 5.1 * kmh_to_ms
]
wd = [45, 45, 67.5, 67.5, 45, 45, 45]
# Février 2021
# ws = [5.60*kmh_to_ms, 2.90*kmh_to_ms, 2.90*kmh_to_ms, 3.40*kmh_to_ms, 5.00*kmh_to_ms, 6.30*kmh_to_ms, 3.70*kmh_to_ms]
# wd = [135, 45, 90, 90, 90, 112.5, 112.5]
fig = plt.figure()
rect = [0.125, 0.125, 0.75, 0.75]
# rect = [0.5, 0.5, 0.5, 0.5]
wa = WindroseAxes(fig, rect)
fig.add_axes(wa)
wa.bar(wd, ws, normed=True, opening=0.8, edgecolor='white')
wa.set_legend(bbox_to_anchor=(1, -0.08), title="WIND SPEED\n(m/s)")
plt.show()
def plot_mag_vel_graphs(deployment,
magnitude_mean_df,
direction_mean_df,
no_nan_dir_mag_df,
water_cell_range_list,
mag_dir_cells_df,
selected_cells,
velocity_north_df,
velocity_east_df,
mean_df,
subset_title='',
subset=''):
""" (str, df, df, df, lst[int], df, lst[int], df, df, str, str) -> fig, fig, fig,
fig
deployment (str) is defined as ID_sitename
The magnitude_mean_df is defined in the notebook
The direction_mean_df is defined in the notebook
The no_nan_dir_mag_df is defined in the notebook
list[int] for water_cell_range_list (y axis for plotting) defined in
notebook
The mag_dir_cells_df is defined in the notebook
The list of selected_cells [int,int,int] is defined at the beginning of the
notebook
string defining whether the data is pre/post subset (e.g. 'presubset' or
'postsubset') to be used in titles
velocity_east_df is defined earlier in the notebook"""
#mean dir, mag, nan
matplotlib.rcParams.update({'font.size': 15})
fig = plt.figure(figsize=(10, 15))
gs1 = gridspec.GridSpec(3, 3, wspace=0.4)
ax1 = plt.subplot(gs1[:, :-1])
ax1.plot(magnitude_mean_df.mean_magnitude,
water_cell_range_list,
color='b')
ax1.yaxis.set_ticks(range(1, (max(water_cell_range_list) + 1), 1))
ax1.grid(axis='y')
ax1.set_xlabel('mean magnitude (m/sec)', color='b')
ax1.set_ylabel('cell number')
ax1.tick_params('x', colors='b')
for index in range(3):
plt.axhline(y=selected_cells[index], color='k')
ax2 = plt.subplot(gs1[:, :-1])
ax2 = ax1.twiny()
ax2.plot(direction_mean_df, water_cell_range_list, color='g')
ax2.set_xlabel('mean direction (deg mag)', color='g')
ax2.tick_params('x', colors='g')
ax2.set_xticks([0, 90, 180, 270])
ax2.set_xlim(0, 360)
for angle in [90, 180, 270]:
plt.axvline(x=angle, linestyle='--', lw='1', color='k')
ax3 = plt.subplot(gs1[:, -1])
ax3.plot(no_nan_dir_mag_df, water_cell_range_list, color='k')
ax3.set_xlabel('Number of NaNs')
ax3.yaxis.set_ticks(range(1, (max(water_cell_range_list) + 1), 1))
ax3.grid(axis='y')
for index in range(3):
plt.axhline(y=selected_cells[index], color='k')
plt.savefig("{0}_Mean_Direction_and_Magnitude_{1}".format(
deployment, subset))
#mag vs time
plt.figure(figsize=(200, 10))
plt.plot(mag_dir_cells_df[str("cell_{}_magnitude".format(
selected_cells[2]))])
plt.plot(mag_dir_cells_df[str("cell_{}_magnitude".format(
selected_cells[1]))])
plt.plot(mag_dir_cells_df[str("cell_{}_magnitude".format(
selected_cells[0]))])
plt.title("{0} Magnitude {1}".format(deployment, subset))
plt.ylabel('Magnitude (m/s)')
plt.xlabel('Date (YYY-MM-DD)')
#plt.xlim(min(mag_dir_cells_df.index)-40, max(mag_dir_cells_df.index)+40) #sets the size of the blank space at the edge of the plot
plt.legend()
plt.grid()
plt.savefig("{0}_Magnitude_{1}.png".format(deployment, subset))
#vel north and east vs time
fig, (ax1, ax2) = plt.subplots(nrows=2,
ncols=1,
sharex=True,
figsize=(100, 15))
ax1.plot(velocity_north_df[str("cell_{}_velocity".format(
selected_cells[2]))])
ax1.plot(velocity_north_df[str("cell_{}_velocity".format(
selected_cells[1]))])
ax1.plot(velocity_north_df[str("cell_{}_velocity".format(
selected_cells[0]))])
ax1.set_ylabel('velocity North (m/sec)')
ax1.grid()
ax1.legend()
ax2.plot(velocity_east_df[str("cell_{}_velocity".format(
selected_cells[2]))])
ax2.plot(velocity_east_df[str("cell_{}_velocity".format(
selected_cells[1]))])
ax2.plot(velocity_east_df[str("cell_{}_velocity".format(
selected_cells[0]))])
ax2.set_ylabel('Velocity East (m/sec))')
ax2.grid()
ax2.legend()
plt.xlabel('Date (YYY-MM-DD)')
#plt.xlim(min(mag_dir_cells_df.index)-40, max(mag_dir_cells_df.index)+40) #sets the size of the blank space at the edge of the plot
plt.suptitle("{0} Velocity North and East vs Time {1}".format(
deployment, subset))
plt.savefig("{0}_Velocity_North_and_East_vs_Time_{1}".format(
deployment, subset))
#current rose
fig = plt.figure(figsize=(10, 10))
rect = [0.05, 0.05, 0.8, 0.8]
wa = WindroseAxes(fig, rect)
fig.add_axes(wa)
wa.bar(mean_df.MeanDirection,
mean_df.MeanSpeed,
bins=6,
normed=True,
opening=0.8,
edgecolor='white')
plt.legend(fontsize=20)
plt.title(
"{0} {1} \nMean Velocity (m/Sec) - radial values indicate percentage of occurance"
.format(deployment, subset),
size=15)
leg = plt.legend(0)
#Sort out units if you changed to knots
leg.set_title('Velocity - (m/Sec)')
plt.savefig("{}_Current_Rose_Presubset".format(deployment))
fig.savefig(pngnm, bbox_inches=0)
pyplot.close()
wndsb = wndsb[(wndsb['WindSpeed'] > 0)]
# A Rose?
fig = pyplot.figure(figsize=(7.5, 6), facecolor='w', edgecolor='w')
rect = [0.08, 0.1, 0.8, 0.8]
ax = WindroseAxes(fig, rect, facecolor='w')
fig.add_axes(ax)
#ax.bar(wndsb['WindDir'],wndsb['WindSpeed'],normed=True,opening=0.8,edgecolor='white')
#ax.set_legend()
ax.bar(wndsb['WindDir'],
wndsb['WindSpeed'],
normed=True,
bins=[0, 2, 5, 7, 10, 15, 20],
opening=0.8,
edgecolor='white',
nsector=36)
handles = []
pctr = 0
for p in ax.patches_list:
color = p.get_facecolor()
# Skip the first bin
if pctr > 0:
handles.append(
Rectangle((0, 0),
0.1,
0.3,
facecolor=color,
edgecolor='black'))
def _make_plot(station, sknt, drct, units, nsector, rmax, hours, months,
sname, minvalid, maxvalid, level, bins):
"""Generate a matplotlib windrose plot
Args:
station (str): station identifier
sknt (list): list of wind obs
drct (list): list of wind directions
units (str): units of wind speed
nsector (int): number of bins to use for windrose
rmax (float): radius of the plot
hours (list): hour limit for plot
month (list): month limit for plot
sname (str): station name
minvalid (datetime): minimum observation time
maxvalid (datetime): maximum observation time
level (int): RAOB level in hPa of interest
bins (list): values for binning the wind speeds
Returns:
matplotlib.Figure
"""
# Generate figure
fig = plt.figure(figsize=(7, 7), dpi=80, facecolor='w', edgecolor='w')
rect = [0.15, 0.15, 0.7, 0.7]
ax = WindroseAxes(fig, rect, axisbg='w')
fig.add_axes(ax)
wu = WINDUNITS[units] if level is None else RAOB_WINDUNITS[units]
if len(bins) > 0:
wu['bins'] = bins
wu['binlbl'] = []
for i, mybin in enumerate(bins[1:-1]):
wu['binlbl'].append("%g-%g" % (mybin, bins[i+2]))
wu['binlbl'].append("%g+" % (bins[-1],))
ax.bar(drct, sknt, normed=True, bins=wu['bins'], opening=0.8,
edgecolor='white', nsector=nsector, rmax=rmax)
handles = []
for p in ax.patches_list:
color = p.get_facecolor()
handles.append(plt.Rectangle((0, 0), 0.1, 0.3,
facecolor=color, edgecolor='black'))
l = fig.legend(handles, wu['binlbl'], loc=(0.01, 0.01),
ncol=6,
title='Wind Speed [%s]' % (wu['abbr'],),
mode=None, columnspacing=0.9, handletextpad=0.45)
plt.setp(l.get_texts(), fontsize=10)
# Now we put some fancy debugging info on the plot
tlimit = "Time Domain: "
if len(hours) == 24 and len(months) == 12:
tlimit = "All Year"
if len(hours) < 24:
if len(hours) > 4:
tlimit += "%s-%s" % (
datetime.datetime(2000, 1, 1, hours[0]).strftime("%-I %p"),
datetime.datetime(2000, 1, 1, hours[-1]).strftime("%-I %p")
)
else:
for h in hours:
tlimit += "%s," % (
datetime.datetime(2000, 1, 1, h).strftime("%-I %p"),)
if len(months) < 12:
for h in months:
tlimit += "%s," % (datetime.datetime(2000, h, 1).strftime("%b"),)
label = """[%s] %s%s
Windrose Plot [%s]
Period of Record: %s - %s""" % (
station, sname if sname is not None else "((%s))" % (station, ),
"" if level is None else " @%s hPa" % (level, ),
tlimit,
minvalid.strftime("%d %b %Y"), maxvalid.strftime("%d %b %Y"))
plt.gcf().text(0.14, 0.99, label, va='top')
plt.gcf().text(0.96, 0.11, (
"Stats\nn: %s\nCalm: %.1f%%\nAvg Speed: %.1f %s"
) % (np.shape(sknt)[0],
np.sum(np.where(sknt < 2., 1., 0.)) / np.shape(sknt)[0] * 100.,
np.average(sknt), wu['abbr']), ha='right')
plt.gcf().text(0.01, 0.11, "Generated: %s" % (
datetime.datetime.now().strftime("%d %b %Y"),),
verticalalignment="bottom")
# Make a logo
im = mpimage.imread('%s/%s' % (DATADIR, 'logo.png'))
plt.figimage(im, 10, 625)
return fig
count[mo] += 1
sped[mo].append( ss )
drct[mo].append( dd )
print east, count
fig = plt.figure(figsize=(12, 10), dpi=80, facecolor='w', edgecolor='w')
i = 0
months = ['JAN','FEB','MAR','APR','MAY','JUN','JUL','AUG','SEP','OCT',
'NOV','DEC']
fig.text(0.5,0.96, "1960-2013 Omaha RAOB 200 hPa Monthly Wind Roses", ha='center', va='top', fontsize=26)
fig.text(0.98,0.01, "Percentages shown are frequency of primarily easterly wind",
ha='right')
for y in [0.65,0.35,0.05]:
for x in [0.02,0.27,0.52,0.77]:
ax = WindroseAxes(fig, [x,y,0.21,0.28], axisbg='w')
fig.add_axes(ax)
ax.bar(drct[i], sped[i], normed=True, bins=[0,1,20,40,60,80,100,200],
opening=0.8, edgecolor='white', nsector=16, rmax=30.0)
ax.text(0.5,0.25, "%s\n%.1f%%" % (months[i],
east[i] / float(count[i]) * 100.0), transform=ax.transAxes, fontsize=26)
i += 1
handles = []
for p in ax.patches_list:
color = p.get_facecolor()
handles.append( Rectangle((0, 0), 0.1, 0.3,
facecolor=color, edgecolor='black'))
l = fig.legend( handles, ['0-20','20-40','40-60','60-80', '80-100','100+'] ,
loc=3,
ncol=6, title='Wind Speed [%s]' % ('mph',),
mode=None, columnspacing=0.9, handletextpad=0.45)
wdir_b[wdir_b == 'nan'] = np.nan
wspd_b[wspd_b == 0] = np.nan
wdir_b[wspd_b == 0] = np.nan
indices = np.logical_not(np.logical_or(np.isnan(wspd_b), np.isnan(wdir_b)))
WS_b = wspd_b[indices]
WD_b = wdir_b[indices]
fig = plt.figure(figsize=[14, 6])
rect = [0, 0, 0.5, 1]
ax = WindroseAxes(fig, rect)
fig.add_axes(ax)
#ax = WindroseAxes.from_ax()
ax.bar(WD,
WS,
cmap=cm.viridis,
normed=True,
nsector=36,
bins=np.arange(0, 14, 2)) #summer
plt.text(-0.06,
1,
'(a)',
ha='left',
va='center',
transform=ax.transAxes,
fontsize=bx_fs + 3)
plt.tick_params(axis='x', which='major', labelsize=tk_fs + 3)
ax.set_rlabel_position(340) #122, 344, 198, 340
ax.set_rmax(10) #8, 10
ax.set_rticks(np.arange(0, 11, 2))
ax.set_yticklabels(['', ' 2%', ' 4%', ' 6%', ' 8%', ' 10%'],
"1960-2013 Omaha RAOB 200 hPa Monthly Wind Roses",
ha='center',
va='top',
fontsize=26)
fig.text(0.98,
0.01,
"Percentages shown are frequency of primarily easterly wind",
ha='right')
for y in [0.65, 0.35, 0.05]:
for x in [0.02, 0.27, 0.52, 0.77]:
ax = WindroseAxes(fig, [x, y, 0.21, 0.28], axisbg='w')
fig.add_axes(ax)
ax.bar(drct[i],
sped[i],
normed=True,
bins=[0, 1, 20, 40, 60, 80, 100, 200],
opening=0.8,
edgecolor='white',
nsector=16,
rmax=30.0)
ax.text(0.5,
0.25,
"%s\n%.1f%%" % (months[i], east[i] / float(count[i]) * 100.0),
transform=ax.transAxes,
fontsize=26)
i += 1
handles = []
for p in ax.patches_list:
color = p.get_facecolor()
handles.append(
Rectangle((0, 0), 0.1, 0.3, facecolor=color, edgecolor='black'))
def plotter( fdict ):
""" Go """
ASOS = psycopg2.connect(database='asos', host='iemdb', user='******')
cursor = ASOS.cursor(cursor_factory=psycopg2.extras.DictCursor)
station = fdict.get('zstation', 'AMW')
network = fdict.get('network', 'IA_ASOS')
threshold = int(fdict.get('threshold', 80))
opt = fdict.get('opt', 'ts')
month = fdict.get('month', 'all')
nt = NetworkTable(network)
if month == 'all':
months = range(1,13)
elif month == 'fall':
months = [9,10,11]
elif month == 'winter':
months = [12,1,2]
elif month == 'spring':
months = [3,4,5]
elif month == 'summer':
months = [6,7,8]
else:
ts = datetime.datetime.strptime("2000-"+month+"-01", '%Y-%b-%d')
# make sure it is length two for the trick below in SQL
months = [ts.month, 999]
limiter = "presentwx ~* 'TS'"
title = "Thunderstorm (TS) contained in METAR"
if opt == 'tmpf_above':
limiter = "round(tmpf::numeric,0) >= %s" % (threshold,)
title = "Air Temp at or above %s$^\circ$F" % (threshold,)
elif opt == 'tmpf_below':
limiter = "round(tmpf::numeric,0) < %s" % (threshold,)
title = "Air Temp below %s$^\circ$F" % (threshold,)
elif opt == 'dwpf_below':
limiter = "round(dwpf::numeric,0) < %s" % (threshold,)
title = "Dew Point below %s$^\circ$F" % (threshold,)
elif opt == 'dwpf_above':
limiter = "round(tmpf::numeric,0) >= %s" % (threshold,)
title = "Dew Point at or above %s$^\circ$F" % (threshold,)
cursor.execute("""
SELECT valid, drct, sknt from alldata where station = %s and
"""+limiter+""" and sknt > 0 and drct >= 0 and drct <= 360
and extract(month from valid) in %s
""", (station, tuple(months)))
sped = []
drct = []
for i, row in enumerate(cursor):
if i == 0:
minvalid = row[0]
maxvalid = row[0]
if row[0] < minvalid: minvalid = row[0]
if row[0] > maxvalid: maxvalid = row[0]
sped.append( row[2] * 1.15)
drct.append( row[1] )
fig = plt.figure(figsize=(6, 7), facecolor='w', edgecolor='w')
rect = [0.1, 0.09, 0.8, 0.8]
ax = WindroseAxes(fig, rect, axisbg='w')
fig.add_axes(ax)
ax.bar(drct, sped, normed=True, bins=[0,2,5,7,10,15,20], opening=0.8,
edgecolor='white', nsector=18)
handles = []
for p in ax.patches_list:
color = p.get_facecolor()
handles.append( Rectangle((0, 0), 0.1, 0.3,
facecolor=color, edgecolor='black'))
l = fig.legend( handles, ('2-5','5-7','7-10','10-15','15-20','20+') , loc=3,
ncol=6, title='Wind Speed [%s]' % ('mph',),
mode=None, columnspacing=0.9, handletextpad=0.45)
plt.setp(l.get_texts(), fontsize=10)
plt.gcf().text(0.5,0.99, ("%s-%s %s Wind Rose, month=%s\n%s\nWhen "
+"%s") % (minvalid.year,
maxvalid.year, station, month.upper(),
nt.sts[station]['name'],
title ),
fontsize=16, ha='center', va='top')
plt.gcf().text(0.01, 0.1, "Generated: 8 September 2014" ,
verticalalignment="bottom")
plt.gcf().text(0.95, 0.1, "n=%s" % (len(drct),) ,
verticalalignment="bottom", ha='right')
return fig
def plotter(fdict):
""" Go """
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
from windrose import WindroseAxes
from matplotlib.patches import Rectangle
pgconn = psycopg2.connect(database='asos', host='iemdb', user='******')
station = fdict.get('zstation', 'AMW')
network = fdict.get('network', 'IA_ASOS')
threshold = int(fdict.get('threshold', 80))
opt = fdict.get('opt', 'ts')
month = fdict.get('month', 'all')
nt = NetworkTable(network)
if month == 'all':
months = range(1, 13)
elif month == 'fall':
months = [9, 10, 11]
elif month == 'winter':
months = [12, 1, 2]
elif month == 'spring':
months = [3, 4, 5]
elif month == 'summer':
months = [6, 7, 8]
else:
ts = datetime.datetime.strptime("2000-"+month+"-01", '%Y-%b-%d')
# make sure it is length two for the trick below in SQL
months = [ts.month, 999]
limiter = "presentwx ~* 'TS'"
title = "Thunderstorm (TS) contained in METAR"
if opt == 'tmpf_above':
limiter = "round(tmpf::numeric,0) >= %s" % (threshold,)
title = "Air Temp at or above %s$^\circ$F" % (threshold,)
elif opt == 'tmpf_below':
limiter = "round(tmpf::numeric,0) < %s" % (threshold,)
title = "Air Temp below %s$^\circ$F" % (threshold,)
elif opt == 'dwpf_below':
limiter = "round(dwpf::numeric,0) < %s" % (threshold,)
title = "Dew Point below %s$^\circ$F" % (threshold,)
elif opt == 'dwpf_above':
limiter = "round(tmpf::numeric,0) >= %s" % (threshold,)
title = "Dew Point at or above %s$^\circ$F" % (threshold,)
df = read_sql("""
SELECT valid, drct, sknt * 1.15 as smph from alldata
where station = %s and
"""+limiter+""" and sknt > 0 and drct >= 0 and drct <= 360
and extract(month from valid) in %s
""", pgconn, params=(station, tuple(months)), index_col='valid')
minvalid = df.index.min()
maxvalid = df.index.max()
fig = plt.figure(figsize=(6, 7.2), facecolor='w', edgecolor='w')
rect = [0.08, 0.1, 0.8, 0.8]
ax = WindroseAxes(fig, rect, axisbg='w')
fig.add_axes(ax)
ax.bar(df['drct'].values, df['smph'].values,
normed=True, bins=[0, 2, 5, 7, 10, 15, 20], opening=0.8,
edgecolor='white', nsector=18)
handles = []
for p in ax.patches_list:
color = p.get_facecolor()
handles.append(Rectangle((0, 0), 0.1, 0.3,
facecolor=color, edgecolor='black'))
l = fig.legend(handles,
('2-5', '5-7', '7-10', '10-15', '15-20', '20+'),
loc=(0.01, 0.03), ncol=6,
title='Wind Speed [%s]' % ('mph',),
mode=None, columnspacing=0.9, handletextpad=0.45)
plt.setp(l.get_texts(), fontsize=10)
plt.gcf().text(0.5, 0.99,
("%s-%s %s Wind Rose, month=%s\n%s\nWhen "
"%s") % (minvalid.year,
maxvalid.year, station, month.upper(),
nt.sts[station]['name'],
title),
fontsize=16, ha='center', va='top')
plt.gcf().text(0.95, 0.12, "n=%s" % (len(df.index),),
verticalalignment="bottom", ha='right')
return fig, df
def _make_plot(station, df, units, nsector, rmax, hours, months, sname, level,
bins):
"""Generate a matplotlib windrose plot
Args:
station (str): station identifier
df (pd.DataFrame): observations
drct (list): list of wind directions
units (str): units of wind speed
nsector (int): number of bins to use for windrose
rmax (float): radius of the plot
hours (list): hour limit for plot
month (list): month limit for plot
sname (str): station name
level (int): RAOB level in hPa of interest
bins (list): values for binning the wind speeds
Returns:
matplotlib.Figure
"""
# Generate figure
fig = plt.figure(figsize=(8, 8), dpi=100, facecolor='w', edgecolor='w')
rect = [0.15, 0.15, 0.7, 0.7]
ax = WindroseAxes(fig, rect, facecolor='w', rmax=rmax)
fig.add_axes(ax)
wu = WINDUNITS[units] if level is None else RAOB_WINDUNITS[units]
if bins:
wu['bins'] = bins
wu['binlbl'] = []
for i, mybin in enumerate(bins[1:-1]):
wu['binlbl'].append("%g-%g" % (mybin, bins[i + 2]))
wu['binlbl'].append("%g+" % (bins[-1], ))
# Filters the missing values
df2 = df[df['drct'] >= 0]
try:
# Unsure why this bombs out sometimes
ax.bar(df2['drct'].values,
df2['speed'].values,
normed=True,
bins=wu['bins'],
opening=0.8,
edgecolor='white',
nsector=nsector)
except Exception as exp:
pass
handles = []
for p in ax.patches_list:
color = p.get_facecolor()
handles.append(
plt.Rectangle((0, 0), 0.1, 0.3, facecolor=color,
edgecolor='black'))
l = fig.legend(handles,
wu['binlbl'],
bbox_to_anchor=(0.01, 0.01, 0.98, 0.09),
loc='center',
ncol=6,
title='Wind Speed [%s]' % (wu['abbr'], ),
mode=None,
columnspacing=0.9,
handletextpad=0.45,
fontsize=14)
plt.setp(l.get_texts(), fontsize=10)
# Now we put some fancy debugging info on the plot
tlimit = "Time Domain: "
if len(hours) == 24 and len(months) == 12:
tlimit = "All Year"
if len(hours) < 24:
if len(hours) > 4:
tlimit += "%s-%s" % (
datetime.datetime(2000, 1, 1, hours[0]).strftime("%-I %p"),
datetime.datetime(2000, 1, 1, hours[-1]).strftime("%-I %p"))
else:
for h in hours:
tlimit += "%s," % (datetime.datetime(2000, 1, 1,
h).strftime("%-I %p"), )
if len(months) < 12:
for h in months:
tlimit += "%s," % (datetime.datetime(2000, h, 1).strftime("%b"), )
label = """[%s] %s%s
Windrose Plot [%s]
Period of Record: %s - %s""" % (
station, sname if sname is not None else "((%s))" %
(station, ), "" if level is None else " @%s hPa" %
(level, ), tlimit, df['valid'].min().strftime("%d %b %Y"),
df['valid'].max().strftime("%d %b %Y"))
plt.gcf().text(0.14, 0.99, label, va='top', fontsize=14)
plt.gcf().text(
0.96,
0.11,
("Summary\nn: %s\nMissing: %s\nCalm: %.1f%%\nAvg Speed: %.1f %s") %
(len(df.index), len(df.index) - len(df2.index),
len(df[df['sknt'] == 0].index) / float(len(df2.index)) * 100.,
df['speed'].mean(), wu['abbr']),
ha='right',
fontsize=14)
plt.gcf().text(0.01,
0.11,
"Generated: %s" %
(datetime.datetime.now().strftime("%d %b %Y"), ),
verticalalignment="bottom",
fontsize=14)
# Make a logo
im = mpimage.imread('%s/%s' % (DATADIR, 'logo.png'))
plt.figimage(im, 10, 735)
return fig
left_rectangle = [
0, 0.1, 0.4, 0.75
] # [left, bottom, width, height] as a fraction of total figure size
ax1 = fig.add_axes(left_rectangle) # creates the axes of specified dimensions
mto[wsp].hist(bins=100)
ax1.set_xscale("log")
ax1.set_xlabel("wind speed (m/s)")
right_rectangle = [0.5, 0.1, 0.5, 0.75] # [left, bottom, width, height]
ax = WindroseAxes(fig, right_rectangle)
fig.add_axes(ax)
ax.bar(mto[wdir],
mto[wsp],
normed=True,
opening=0.8,
edgecolor='white',
bins=np.logspace(-1, 1, 10))
ax.set_title("annual", position=(0.5, 1.1))
ax.set_legend()
ax.legend(title="wind speed (m/s)", loc=(1.1, 0))
######################################################################
# The numbers around the radar plot indicate frequencies for the given
# direction. They look quite ugly, and would benefit from some formatting.
# which is not super trivial:
#
from windrose import WindroseAxes
