def getSliceData_Ny_sowfa(dir, jobName, slice, var, varD, trs_para, tInd, xInd,
zInd):
""" extract velocity data of specified slice_Nz """
readDir = dir + '/data/'
readName = slice
fr = open(readDir + readName, 'rb')
data = pickle.load(fr)
fr.close()
slc = sdc.Slice(data, 1)
del data # 2 means z-axis
tSeq = slc.data['time']
tSeq = tSeq[tInd[0]:tInd[1]]
Y = slc.N_location # height of this plane
O, alpha = trs_para[0], trs_para[1]
varSeq = []
for t_ind in range(tInd[0], tInd[1]):
print('processing: ' + str(t_ind) + ' ...')
tmp = slc.data[var][t_ind]
tmp = funcs.trs(tmp, O, alpha)
tmp1 = slc.meshITP_Ny(xInd, zInd, tmp[:, varD], 0, method_='linear')
xSeq, zSeq, varSeq_ = tmp1[0], tmp1[1], tmp1[2]
varSeq.append(varSeq_)
varSeq = np.array(varSeq)
return tSeq, xSeq, zSeq, Y, varSeq
def getSliceData_Nz_sowfa(jobDir, slice, var, varD, trs_para, tInd, xcoor,
ycoor):
"""
Extract data from specified slice_Nz
INPUT
jobDir: job directory, e.g. '/scratch/sowfadata/pp/tutorials/example_nbl'
slice: the name of the slice, e.g. 'Nz2'
var: name of the target variable, e.g. 'U'
varD: the dimension of which the target vector variable will be outputted
trs_para: coordinate transform parameters, e.g. ((0,0,0),30.0), the origin and the conterclockwise rotation degree
tInd: a tuple containing the start time index and end time index of the output data (not including the end tInd)
xcoor: a tuple containing the start x, end x and x.size of the output data
ycoor: a tuple containing the start y, end y and y.size of the output data
OUTPUT
tSeq: 1D array of times
ySeq: 1D array of y positions
xSeq: 1D array of x positions
H: the height of the slice
varSeq: 3D array of the target variable, 1st dim time, 2nd dim y, 3rd x
"""
readDir = jobDir + '/data/'
readName = slice
fr = open(readDir + readName, 'rb')
data = pickle.load(fr)
fr.close()
slc = sdc.Slice(data, 2)
del data # 2 means z-axis
tSeq = slc.data['time']
tSeq = tSeq[tInd[0]:tInd[1]]
H = slc.N_location # height of this plane
O, alpha = trs_para[0], trs_para[1]
varSeq = []
for t_ind in range(tInd[0], tInd[1]):
print('processing: ' + str(t_ind) + ' ...')
tmp = slc.data[var][t_ind]
tmp = funcs.trs(tmp, O, alpha)
tmp1 = slc.meshITP_Nz(xcoor, ycoor, tmp[:, varD], method_='linear')
xSeq, ySeq, varSeq_ = tmp1[0], tmp1[1], tmp1[2]
varSeq.append(varSeq_)
varSeq = np.array(varSeq)
return tSeq, xSeq, ySeq, H, varSeq
'Nz5',
'Nz6',
'Nz7',
]
sliceNum = len(sliceList)
var = 'U'
varD = 0 # u:0, v:1, w:2
varNameDict = {0: 'u', 1: 'v', 2: 'w'}
readDir = ppDir + '/data/'
readName = sliceList[0]
fr = open(readDir + readName, 'rb')
data_org = pickle.load(fr)
fr.close()
slc = sdc.Slice(data_org, 2)
tSeq = slc.data['time']
tInd = -1 # index of time step
plotDataList = []
HList = []
for slice in sliceList:
readDir = ppDir + '/data/'
readName = slice
fr = open(readDir + readName, 'rb')
data_org = pickle.load(fr)
fr.close()
slc = sdc.Slice(data_org, 2)
H = slc.N_location # height of this plane
jobName = 'pcr_NBL_U10'
ppDir = '/scratch/sowfadata/pp/' + jobName
sliceList = ['Ny0']
sliceNum = len(sliceList)
var = 'U'
varD = 0 # u:0, v:1, w:2
varNameDict = {0: 'u', 1: 'v', 2: 'w'}
readDir = ppDir + '/data/'
readName = sliceList[0]
fr = open(readDir + readName, 'rb')
data_org = pickle.load(fr)
fr.close()
slc = sdc.Slice(data_org, 1)
tSeq = slc.data['time']
tInd = -1 # index of time step
plotDataList = []
YList = []
for slice in sliceList:
readDir = ppDir + '/data/'
readName = slice
fr = open(readDir + readName, 'rb')
data_org = pickle.load(fr)
fr.close()
slc = sdc.Slice(data_org, 1)
Y = slc.N_location # height of this plane
import pickle
import sliceDataClass as sdc
import matplotlib.pyplot as plt
# the directory where the wake data locate
prjDir = '/scratch/sowfadata/JOBS'
jobName = 'pcr_NBL_U10'
ppDir = '/scratch/sowfadata/pp/' + jobName + '/data'
readDir = ppDir + '/'
readName = 'Ny0'
fr = open(readDir + readName, 'rb')
data_org = pickle.load(fr)
fr.close()
test = sdc.Slice(data_org, 1)
plotdata = test.meshITP_Ny((0, 2000, 200), (0, 960, 48), test.data['U'][-1][:,
0])
fig, axs = plt.subplots(figsize=(8, 8))
cbreso = 100 # resolution of colorbar
CS = axs.contourf(plotdata[0],
plotdata[1],
plotdata[2],
cbreso,
cmap='coolwarm')
cbar = plt.colorbar(CS, ax=axs, shrink=1.0)
cbar.ax.set_ylabel('u (m/s)')
# xaxis_min = xseq
# xaxis_max = 2