def basemap_earth(self):
data = np.array(self, dtype=float)
lat = data['lat']
lon = data['lon']
lon, lat = mp.meshgrid(lon, lat)
2m_mean_temp = data['air']
fig = plt.figure(figsize=(10, 8))
m = Basemap(projection='cyl', resolution='c',
lat_0=0, lon_0=0)
m.fillcontinents(color="#FAFAFA", lake_color="#FAFAFA")
m.drawmapboundary(fill_color="#FAFAFA")
m.drawcoastlines()
plt.
return draw_map(m)
ffrom mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
fig = plt.gcf()
# fig.set_size_inches(10, 15)
# Google map
map = Basemap( llcrnrlon= -80.080208,
llcrnrlat= 41.154397,
urcrnrlon= -80.077010,
urcrnrlat= 41.155810,
epsg=2271)
map.arcgisimage(service='World_Imagery', verbose= True)
# Scatter of gps data in lat lon
# plt.title("Latitude vs. Longitude")
plt.show()
fig.savefig("Map.png", bbox_inches='tight', pad_inches = -.1, dpi=220)
notglon = np.append(notglon, tslon[i][np.array(ts[i])>= LI0[i]])
notglat = np.append(notglat, tslat[i][np.array(ts[i])>= LI0[i]])
#%% Make the plot
fig, ax = plt.subplots(figsize=(12,8))
ACCloc = np.load('ACClocation.npz')
acclat = ACCloc['acclat'][:]
acclon = ACCloc['acclon'][:]
acclat = running_mean_circular(acclat,150)# To get a running_mean over circular data
plt.subplot2grid((16, 8), (0, 0), colspan=4, rowspan=12)
m = Basemap(projection='splaea',boundinglat=-30,lon_0=90,resolution=resolution)#north pole: 'nplaea', south pole: 'spaeqd'
m.drawcoastlines()
m.drawmapboundary(fill_color='w')#black')
m.fillcontinents(color='grey')#, lake_color='lightskyblue')
m.drawparallels(np.arange(-70, 70, 20), labels=[True, False, False, False])
m.drawmeridians(np.arange(0, 361, 45), labels=[False, False, False, True])
plt.title('(a) ' + zondata['variables'][specie_number][:-3],**ifont)
aclon, aclat = m(acclon, acclat)
xzon, yzon = m(zonlon, zonlat)
xadv, yadv = m(glon, glat)
xadv2, yadv2 = m(notglon, notglat)
cmap = plt.get_cmap('Blues')
plt.scatter(xadv, yadv, c=redcolor, label='backtracked cold tail', s=15, alpha=0.3)#, zorder=4
algoritmo.pyfrom mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import numpy as np
from numpy import meshgrid
import pandas as pd
import math
plt.figure(figsize=(48,24))
m = Basemap(projection='mill',llcrnrlat=25,urcrnrlat=33,llcrnrlon=-115,urcrnrlon=-107,resolution='i')
#%% read txt file
data = pd.read_csv('data/2017-09-25.csv')
#%% calculate U and V vectors
def calculateU(windSpeed, windDirection):
'''
Generate U vector
'''
return windSpeed * math.cos(windDirection)
def calculateV(windSpeed, windDirection):
'''
Generate V vector
'''
return windSpeed * math.sin(windDirection)
#%% cut info
data = data.loc[data['Long'] > -115.0]
data = data.loc[data['Long'] < -107.0]
m.plot(lons, lats, 'bo')
plt.draw()
# SAVE AS 2D ARRAY... pre land-masking
np.savez('test_grid', lats, lons)
MEEP += 1
MEEP = 0
# approximate radius of earth in km
R = 6378.13
fig = plt.figure(figsize=(11.7, 8.3))
plt.subplots_adjust(left=0.05,
right=0.95,
top=0.90,
bottom=0.05,
wspace=0.15,
hspace=0.05)
ax = plt.subplot(111)
m = Basemap(resolution='l')
m.drawmapboundary(fill_color='azure')
m.fillcontinents(color='palegoldenrod', lake_color='azure')
m.drawcoastlines()
grid_res = input("Grid resolution in km: ")
click = Click(ax, grid_gen)
#fig.canvas.mpl_connect("button_press_event", onclick)
plt.show()
def value6_map1(xCoord, yCoord, sList):
symbolSize=5
s = np.asarray(sList)
maxValue = np.amax(s)
minValue = np.amin(s)
if abs(maxValue) >= abs(minValue):
absRange = abs(maxValue)
else:
absRange = abs(minValue)
value1 = -(absRange/3*2)
value2 = -(absRange/3)
value3 = 0
value4 = absRange/3
value5 = absRange/3*2
group1 = np.ma.masked_where(s > value1, s)
group2 = np.ma.masked_where(np.logical_or(s< value1, s> value2), s)
group3 = np.ma.masked_where(np.logical_or(s< value2, s> value3), s)
group4 = np.ma.masked_where(np.logical_or(s< value3, s> value4), s)
group5 = np.ma.masked_where(np.logical_or(s< value4, s> value5), s)
group6 = np.ma.masked_where(s < value5, s)
oneGroup1 = []
oneGroup2 = []
oneGroup3 = []
oneGroup4 = []
oneGroup5 = []
oneGroup6 = []
for grp1 in group1:
if grp1 !='--':
oneGroup1.append(symbolSize)
else:
oneGroup1.append(0)
for grp2 in group2:
if grp2 !='--':
oneGroup2.append(symbolSize)
else:
oneGroup2.append(0)
for grp3 in group3:
if grp3 !='--':
oneGroup3.append(symbolSize)
else:
oneGroup3.append(0)
for grp4 in group4:
if grp4 !='--':
oneGroup4.append(symbolSize)
else:
oneGroup4.append(0)
for grp5 in group5:
if grp5 !='--':
oneGroup5.append(symbolSize)
else:
oneGroup5.append(0)
for grp6 in group6:
if grp6 !='--':
oneGroup6.append(symbolSize)
else:
oneGroup6.append(0)
fig = plt.figure(figsize=(12, 10))
ax = fig.add_subplot(1,1,1)
legendValue1 = str(round(value1,2))
legendValue2 = str(round(value2,2))
legendValue3 = str(round(value3,2))
legendValue4 = str(round(value4,2))
legendValue5 = str(round(value5,2))
rangeList = bm.addBasemap(bm.basemapRange, bm.basemapPolygonList, bm.basemapLineList, bm.basemapPointList, bm.basemapElements, ax)
## Setting for ax
ax.set_xlim(rangeList[0],rangeList[1])
ax.set_ylim(rangeList[2],rangeList[3])
ax.scatter(0,0, s=0, c='w', label = 'Estimates')
if oneGroup1.count(0) != len(oneGroup1):
ax.scatter(xCoord,yCoord, s= oneGroup1, c='#3300CC', edgecolor='none', label = 'less than ' + legendValue1)
if oneGroup2.count(0) != len(oneGroup2):
ax.scatter(xCoord,yCoord, s= oneGroup2, c='#3333FF', edgecolor='none', label = legendValue1 + ' - ' + legendValue2)
if oneGroup3.count(0) != len(oneGroup3):
ax.scatter(xCoord,yCoord, s= oneGroup3, c='#33CCFF', edgecolor='none', label = legendValue2 + ' - ' + legendValue3)
if oneGroup4.count(0) != len(oneGroup4):
ax.scatter(xCoord,yCoord, s= oneGroup4, c='#FFCC00', edgecolor='none', label = legendValue3 + ' - ' + legendValue4)
if oneGroup5.count(0) != len(oneGroup5):
ax.scatter(xCoord,yCoord, s= oneGroup5, c='#FF6600', edgecolor='none', label = legendValue4 + ' - ' + legendValue5)
if oneGroup6.count(0) != len(oneGroup6):
ax.scatter(xCoord,yCoord, s= oneGroup6, c='#FF0000', edgecolor='none', label = 'more than '+legendValue5)
ax.legend(loc=3, ncol=1, fontsize=7, bbox_to_anchor=(-0.15,-0.15), markerscale=3.0, fancybox = True, scatterpoints = 1)
return fig, ax
def map2(xCoord, yCoord, estValues, tValues, correctedT, rangeValue):
#correctedT : double determined by year variable
#rangeValue :
valueList = []
for ind, value in enumerate(xCoord):
# print value
# print type(yCoord[ind])
tempArray = [float(value[0]), float(yCoord[ind]), float(estValues[ind]), float(tValues[ind])]
valueList.append(tempArray)
newValueList = []
index = 0
for value in valueList:
if abs(value[3]) > abs(correctedT):
newValueList.append(value)
index+=1
newxCoord = []
newyCoord = []
newEstValues = []
newTValues = []
for newValue in newValueList:
newxCoord.append(newValue[0])
newyCoord.append(newValue[1])
newEstValues.append(newValue[2])
newTValues.append(newValue[3])
symbolSize=15
sEst = np.asarray(newEstValues)
absRange = rangeValue
value1 = -(absRange/3*2)
value2 = -(absRange/3)
value3 = 0
value4 = absRange/3
value5 = absRange/3*2
group1Est = np.ma.masked_where(sEst > value1, sEst)
group2Est = np.ma.masked_where(np.logical_or(sEst< value1, sEst> value2), sEst)
group3Est = np.ma.masked_where(np.logical_or(sEst< value2, sEst> value3), sEst)
group4Est = np.ma.masked_where(np.logical_or(sEst< value3, sEst> value4), sEst)
group5Est = np.ma.masked_where(np.logical_or(sEst< value4, sEst> value5), sEst)
group6Est = np.ma.masked_where(sEst < value5, sEst)
oneGroup1Est = []
oneGroup2Est = []
oneGroup3Est = []
oneGroup4Est = []
oneGroup5Est = []
oneGroup6Est = []
for grp1 in group1Est:
if grp1 !='--':
oneGroup1Est.append(symbolSize)
else:
oneGroup1Est.append(0)
for grp2 in group2Est:
if grp2 !='--':
oneGroup2Est.append(symbolSize)
else:
oneGroup2Est.append(0)
for grp3 in group3Est:
if grp3 !='--':
oneGroup3Est.append(symbolSize)
else:
oneGroup3Est.append(0)
for grp4 in group4Est:
if grp4 !='--':
oneGroup4Est.append(symbolSize)
else:
oneGroup4Est.append(0)
for grp5 in group5Est:
if grp5 !='--':
oneGroup5Est.append(symbolSize)
else:
oneGroup5Est.append(0)
for grp6 in group6Est:
if grp6 !='--':
oneGroup6Est.append(symbolSize)
else:
oneGroup6Est.append(0)
legendValue1 = str(round(value1,2))
legendValue2 = str(round(value2,2))
legendValue3 = str(round(value3,2))
legendValue4 = str(round(value4,2))
legendValue5 = str(round(value5,2))
fig = plt.figure(figsize=(9, 7.5))
ax = fig.add_subplot(1,1,1)
rangeList = bm.addBasemap(bm.basemapRange, bm.basemapPolygonList, bm.basemapLineList, bm.basemapPointList, bm.basemapElements, ax)
## Setting for ax
ax.set_xlim(rangeList[0],rangeList[1])
ax.set_ylim(rangeList[2],rangeList[3])
ax.scatter(0,0, s=0, c='w', label = 'Estimates')
if oneGroup1Est.count(0) != len(oneGroup1Est):
ax.scatter(newxCoord,newyCoord, s= oneGroup1Est, c='#3300CC', edgecolor='none', label = 'less than ' + legendValue1)
if oneGroup2Est.count(0) != len(oneGroup2Est):
ax.scatter(newxCoord,newyCoord, s= oneGroup2Est, c='#3333FF', edgecolor='none', label = legendValue1 + ' - ' + legendValue2)
if oneGroup3Est.count(0) != len(oneGroup3Est):
ax.scatter(newxCoord,newyCoord, s= oneGroup3Est, c='#33CCFF', edgecolor='none', label = legendValue2 + ' - ' + legendValue3)
if oneGroup4Est.count(0) != len(oneGroup4Est):
ax.scatter(newxCoord,newyCoord, s= oneGroup4Est, c='#FFCC00', edgecolor='none', label = legendValue3 + ' - ' + legendValue4)
if oneGroup5Est.count(0) != len(oneGroup5Est):
ax.scatter(newxCoord,newyCoord, s= oneGroup5Est, c='#FF6600', edgecolor='none', label = legendValue4 + ' - ' + legendValue5)
if oneGroup6Est.count(0) != len(oneGroup6Est):
ax.scatter(newxCoord,newyCoord, s= oneGroup6Est, c='#FF0000', edgecolor='none', label = 'more than '+legendValue5)
# ax.legend(loc=3, ncol=1, fontsize=9, bbox_to_anchor=(0.,-0.1), markerscale=3.0, fancybox = True, scatterpoints = 1)
return fig, ax