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Not able to plot vectorfield with resterize and trimesh combination. #3890

Closed sameerCoder closed 5 years ago

sameerCoder commented 5 years ago

Hi , I am plotting Significant wave height and direction both by giving Holomap features . But when i am using restarize with gv.vectorfield then i am getting the actual vectordirection plot . i required restarize as after using holomap features i want to do zoomin and my data should get changed as dynamic data . so how i can modify my code so that i can get Trimesh + vectorfield plot with restarize . from shapely.geometry import Point, Polygon

` import pandas as pd import numpy as np import geoviews as gv import bokeh import datashader.utils as du, datashader.transfer_functions as tf

from scipy.interpolate import griddata import holoviews as hv from holoviews import opts from holoviews.operation.datashader import datashade , rasterize hv.extension("bokeh") from bokeh.models import ColorBar import math from bokeh.plotting import output_file, save from bokeh.models import HoverTool from scipy.io import loadmat import datetime import pandas as pd from dateutil.parser import parse

from bokeh.plotting import figure import datashader as ds from scipy.interpolate import InterpolatedUnivariateSpline from datetime import timedelta from numpy import ogrid datamat = loadmat('IOEC_ECM_noDA_20190703_masked.mat') Xp = datamat['Xp'] Yp = datamat['Yp'] strt = datetime.datetime(2019, 7, 4, 0, 0) end = datetime.datetime(2019, 1, 13, 0, 0)

def perdelta(strt, end, delta): curr = strt while curr < end: yield curr curr += delta

Read element file

data = pd.read_table('fort.ele',delim_whitespace=True,names=('A','B','C','D'))

tri_new = pd.read_csv('fort.ele', delim_whitespace=True, names=('A', 'B', 'C', 'D'), usecols=[1, 2, 3], skiprows=1, dtype={'D': np.int}) def plotthis(datetime): dat=datetime dt = parse(str(dat)) yr = dt.year mn = dt.month d = dt.day hr = dt.hour mi = dt.minute

print(y,mn,d,hr,mi)

if hr < 10:
# d='0'+str(d)
    hr = '0' + str(hr)
else:
    d = str(d)
    hr = str(hr)
if int(d) < 10:
    d = '0' + str(d)
else:
    d = str(d)
varname = 'Hsig_' + str(yr) + '0' + str(mn) + str(d) + '_' + hr + '0000'
print(varname)

x = Xp.flatten()
y = Yp.flatten()
z = datamat[varname]
z = z.flatten()
Longitude=x
Latitude=y
HS=z
pts = np.stack((Longitude,Latitude,HS)).T
verts = pd.DataFrame(np.stack((Longitude,Latitude,HS)).T, columns=['Longitude', 'Latitude' , 'HS'])
pkname = 'PkDir_' + str(yr) + '0' + str(mn) + str(d) + '_' + hr + '0000'

pkvalue = datamat[pkname]
pksub=pkvalue[1:200000]
d1 = pkvalue * (math.pi / 180)

u = np.cos(d1) * 1
v = np.sin(d1) * 1

u = u.flatten()
v = v.flatten()

print("length of u ", len(u))
print("lenght of v ", len(v))

um, vm = np.meshgrid(u, v, sparse=True)
print(um)
um = um.flatten()

vm = vm.flatten()

tiles=gv.WMTS('https://maps.wikimedia.org/osm-intl/{Z}/{X}/{Y}@2x.png')

#openStreet Background.
tri_sub = tri_new.apply(lambda x: x - 1)

levels=[0,0.2,0.4,0.6,0.8,1,1.2,1.4,1.6,1.8,2,2.2,2.5,3,]
colorbar_opts={
'major_label_overrides': {
0:'0',

0.5:'0.5',

1:'1',

1.5:'1.5',

2:'2',

2.5:'2.5',
3:'3',

3.5:'3.5',
3.8:' ',
3.9:'>3.9',

},
'major_label_text_align': 'left','major_label_text_font_style':'bold',}

def plot_limits(plot, element):
    plot.handles['x_range'].min_interval = 100
    plot.handles['x_range'].max_interval = 55000000
    #3000000
    plot.handles['y_range'].min_interval = 500
    plot.handles['y_range'].max_interval = 900000
opts = dict(width=700, height=700, logz=False, tools=['hover','save','wheel_zoom'],hooks=[plot_limits],colorbar=True,color_levels=15,
    colorbar_opts=colorbar_opts,cmap= ['#000080',
                                       '#0000cd',

'#0008ff',
'#004cff',
'#0090ff',
'#00d4ff',
'#29ffce',
'#60ff97',
'#97ff60',
'#ceff29',
'#ffe600',
'#ffa700',
#'#ff6800',
                                       '#ff2900',
                                       '#cd0000',
                                       '#800000',

],clim=(0,3.76),title=" \t\t\t\tSignificant Wave Height (m) ",fontsize={'title': 26, 'xlabel':15, 'ylabel':15, 'ticks':12} )

pkname = 'PkDir_' + str(yr) + '0' + str(mn) + str(d) + '_' + hr + '0000'

#pkvalue = datamat[pkname]
print(pkname)
pkvalue = datamat[pkname]
pkvalue=pkvalue.flatten()
d=pkvalue*(math.pi/180)

# target grid to interpolate to
xt = np.arange(76.937,92.008,0.1)
yt = np.arange(1.482,22.461,0.1)
xi,yi = np.meshgrid(xt,yt)
di = griddata((Longitude,Latitude),d,(xi,yi))

dfcoast = pd.read_csv('ECpolygonTwoDegreeOffsetBorder.txt', delim_whitespace=True, names=('X', 'Y'))
dfcoast['geometry'] = dfcoast.apply(lambda row: Point(row.X, row.Y), axis=1)
poly = Polygon([(p.x, p.y)  for p in  dfcoast.geometry])

arr=np.zeros((len(yt),len(xt)))
for i in range(len(xt)):
    for j in range(len(yt)):
        point=Point(xt[i],yt[j])
        arr[j,i]=poly.contains(point)

mask = (xi > 79.7817) & (xi < 81.2718) & (yi > 7.6951) & (yi < 9.7406)
di[mask] = np.nan
di[arr==False]=np.nan
U=np.cos(di)
V=np.sin(di)

mag = np.sqrt(U**2 + V**2)
angle = (np.pi/2.) - np.arctan2(U/mag, V/mag)
tiles = gv.tile_sources.Wikipedia
ggpoints=gv.Points(verts,vdims=['HS'])

#return gg
#return tiles*gv.TriMesh((tri_sub,gv.Points(verts)))*gv.VectorField((xi[::15,::15], yi[::15,::15], angle[::15,::15], mag[::15,::15]))
return tiles*gv.VectorField((xi[::5,::5], yi[::5,::5], angle[::5,::5], mag[::5,::5]))

allplot={k.strftime("%Y-%m-%d %H"):plotthis(k)for k in perdelta(strt, strt + timedelta(days=1), timedelta(hours=18))} colorbar_opts={ 'major_label_overrides': { 0:'0',

0.5:'0.5',

1:'1',

1.5:'1.5',

2:'2',

2.5:'2.5',
3:'3',

3.5:'3.5',
3.8:' ',
3.9:'>3.9',

},
'major_label_text_align': 'left','major_label_text_font_style':'bold',}

levels=[0,0.2,0.4,0.6,0.8,1,1.2,1.4,1.6,1.8,2,2.2,2.5,3,]

def plot_limits(plot, element): plot.handles['x_range'].min_interval = 100 plot.handles['x_range'].max_interval = 55000000

3000000

    plot.handles['y_range'].min_interval = 500
    plot.handles['y_range'].max_interval = 900000

opts = dict(width=700, height=700, tools=['hover','save','wheel_zoom'],hooks=[plot_limits],title=" \t\t\t\tSignificant Wave Height (m) ",fontsize={'title': 26, 'xlabel':15, 'ylabel':15, 'ticks':12} )

hmap = hv.HoloMap(allplot, kdims='Date and Time :') hmap.options(**opts)

restarize(hmap).options(**opts)

I want return tilesgv.TriMesh((tri_sub,gv.Points(verts)))gv.VectorField((xi[::15,::15], yi[::15,::15], angle[::15,::15], mag[::15,::15]))` above code to work fine so that i can get Trimesh as well as vectorfield plot return from for loop and restarize at last after holomap , i.e restarize(hmap).options(**opts) . so that i can do dynamic data update while zoomin and zoom out.

philippjfr commented 5 years ago

Please reopen the issue with your code formatted correctly. This is also more of a usage question than an actual issue.