def open(self):
# Check input data type
if isinstance(self.filebase, str):
self.dataInput = utils.readcsv(self.filebase+'.str', unitrow=8,
checkNaN=False, echo=self.echo)
elif isinstance(self.filebase, meca.Stress):
self.dataInput = self.filebase.dataOutput
else:
raise TypeError('[ERROR] Unknown type of input data {}, should be <str> or <meca.Stress> object'.format(self.filebase))
# Check where to count
if self.gages is None: # count cycles on every spot over each tower gage
print("|- [ALERT] Every stress history will be used to count Rainflow",
"cycles. If you don't mean it, try to choose serval tower gages in",
"order to reduce calculation time")
allSpots = self.dataInput.getkeys()
try:
allSpots.remove('Time') # remove "Time" column
except:
pass
self.spots = allSpots
elif isinstance(self.gages[0], int): # count cycles over given tower gages
available = self.dataInput.getkeys()
try:
available.remove('Time') # remove "Time" column
except:
pass
for name in available:
if int(name[4]) in self.gages:
self.spots.append(name)
else:
print("|- [ALERT] There is no tower gage TwHt{} in input file".format(name[4]))
else:
raise Exception('[ERROR] Wrong list of tower gages {}, shoud be a list of integer numbers or None'.format(self.gages))
def getConditions(self):
for v in self._speedRange:
filename = self._outputPath.joinpath("CST_{}.out".format(v))
data = utils.readcsv(filename)
conditions = collections.OrderedDict().fromkeys(
self._conditionKeys)
for key in self._conditionKeys:
conditions[key] = data.get(key)["Records"][-1]
self._allConditions[v] = conditions
def compare_YawBrTDx(columns=['YawBrTDxt'], minor=[True, True, True, True], xlim=[60, 90, 10], ylim=[-0.9, 0.7, 0.1], file='', residu=False, withPV=False, toPDF=[]):
# reference data
X1 = DATA_REF.get('Time')['Records']
Y1 = DATA_REF.get(columns[0])['Records']
# data to be compared
data = utils.readcsv(file)
X2 = data.get('Time')['Records']
Y2 = data.get(columns[0])['Records']
fig, axeLeft = plt.subplots()
# --- Left axis
color = 'tab:blue'
legendString1 = axeLeft.plot(X1, Y1, '--', label=DATA_REF.get(columns[0])['Title'])
if not residu:
legendString2 = axeLeft.plot(X2, Y2, label=data.get(columns[0])['Title']+file+" with TRD")
axeLeft.set_ylabel("Deflection (m)", color=color)
axeLeft.tick_params(axis='y', labelcolor=color)
axeLeft.set_yticks(numpy.arange(ylim[0], ylim[1]+ylim[2], ylim[2]))
plt.ylim(ylim[0], ylim[1])
if withPV: # mark peak and valley
filename = "reference_"+columns[0]+".ext"
plot_peak_and_valley(filename, axeLeft)
filename = file.rstrip(".out")+"_"+columns[0]+".ext"
plot_peak_and_valley(filename, axeLeft)
# --- Right axis
if residu:
color = 'tab:pink'
axeRight = axeLeft.twinx() # instantiate a second axes that shares the same x-axis
# calculate relative difference
X_residu = X1
Y_residu = [Y2[i]-Y1[i] for i in range(len(Y1))]
legendString2 = axeRight.plot(X_residu, Y_residu, '-', linewidth=0.8, color=color, label="Residue = REF - "+file)
axeRight.set_ylabel("Reletive difference in deflection (m)", color=color)
axeRight.tick_params(axis='y', labelcolor=color)
axeRight.set_yticks(numpy.arange(ylim[0], ylim[1]+ylim[2], ylim[2]))
plt.ylim(ylim[0], ylim[1])
# --- Common setting
lns = legendString1 + legendString2
labs = [l.get_label() for l in lns]
axeLeft.legend(lns, labs, loc=0)
plt.xlim(xlim[0], xlim[1])
plt.xticks(numpy.arange(xlim[0], xlim[1]+xlim[2], step=xlim[2]))
axeLeft.set_xlabel("Time (s)")
axeLeft.grid(axis='x')
axeLeft.grid(axis='y')
chart.draw(fig, toPDF)
def main():
# get reference data
filebase = 'reference'
global DATA_REF
DATA_REF = utils.readcsv(filebase+".out")
graphNum = 1
if graphNum == 0: # get peak/valley and its time
amp.find_peak_valley(filebase, header=7, datarow=6009, startline=12,
channels=["YawBrTDxt",])
if graphNum == 1:
# plot_Wind1Vel(file='EOG_O_277.826.7-86.712-17.0222.out')
compare_YawBrTDx(file='EOG_O_277.826.7-86.712-17.0222.out', withPV=True)
def open(self,):
''' Read data from .out file
'''
temp = utils.readcsv(filename=self.filenameInput, datarow=self.datarow,
checkNaN=False, echo=self.echo)
self.dataInput['Time'] = temp.get('Time')['Records']
for i in self.gages: # force and moment on each node
self.dataInput[i] = {'FLzt':[], 'MLxt':[], 'MLyt':[]}
self.dataInput[i]['FLzt'] = temp.get('TwHt'+str(i)+'FLzt')['Records']
self.dataInput[i]['MLxt'] = temp.get('TwHt'+str(i)+'MLxt')['Records']
self.dataInput[i]['MLyt'] = temp.get('TwHt'+str(i)+'MLyt')['Records']
self.dataLength = len(self.dataInput[i]['FLzt'])
if self.echo:
print("|- {} lines of data have been imported from {}".format(self.dataLength,
self.filenameInput))
def plot_trd_AON_AOFF(TRD_AON, TRD_AOFF, columns=('NTRD_FC', 'NTRD_A', 'NTRD_VA'),
velocities=('I','R-2','R','R+2','O'), xlim=(60, 90, 10),
file='', toPDF=[]):
for v in velocities:
fig, axes = plt.subplots()
# Create subplots
axes = []
gs = gridspec.GridSpec(3, 1, height_ratios=[2, 1, 2])
axes.append( plt.subplot(gs[0]) )
axes.append( plt.subplot(gs[1]) )
axes.append( plt.subplot(gs[2]) )
# slice data
data = utils.readcsv(file)
start = data.get('Time')['Records'].index(xlim[0])
end = data.get('Time')['Records'].index(xlim[1])
X = data.get('Time')['Records'][start:end]
# Chart 1: NTRD_FC -----------------------------------------------------
Y = data.get(columns[0])['Records'][start:end]
axes[0].plot(X, Y, label=data.get(columns[0])['Title'])
# Chart 2: NTRD_A ------------------------------------------------------
Y = data.get(columns[1])['Records'][start:end]
axes[1].plot(X, Y, '--', label=data.get(columns[1])['Title'])
indices = [i for (i,y) in enumerate(Y) if y == 1] # TRD is activated: A = 1
axes[1].plot([X[i] for i in indices], [Y[i] for i in indices], '.', markersize=1, color='tab:green', label="TRD ON")
indices = [i for (i,y) in enumerate(Y) if y == 0] # TRD is inactivated: A = 0
axes[1].plot([X[i] for i in indices], [Y[i] for i in indices],'.', markersize=1, color='tab:red', label="TRD OFF")
# Chart 3: NTRD_VA -----------------------------------------------------
Y = data.get(columns[2])['Records'][start:end]
axes[2].plot(X, Y, ':', label=data.get(columns[2])['Title'])
# TRD_AON
indices = [i for (i,y) in enumerate(Y) if y >= TRD_AON]
axes[2].plot([X[i] for i in indices], [Y[i] for i in indices], '.', markersize=1, color='tab:green', label="AON="+str(TRD_AON))
# TRD_AOFF
indices = [i for (i,y) in enumerate(Y) if y <= TRD_AOFF]
axes[2].plot([X[i] for i in indices], [Y[i] for i in indices],'.', markersize=1, color='tab:red', label="AOFF="+str(TRD_AOFF))
# Set axes properties
chart.adjust(axes[0], xlim=xlim, ylim=[-30e3, 30e3], ylabel="Force (kN)", xVisible=False)
chart.adjust(axes[1], xlim=xlim, ylim=[-0.2, 1.2], ylabel="TRD Status", xVisible=False, seperator=False)
chart.adjust(axes[2], xlim=xlim, ylim=[-0.1, 2.0], ylabel="Amplitude of vibration (m/s)", seperator=False)
chart.draw(fig, toPDF, left=0.08, bottom=0.06, right=0.92, top=0.94, wspace=0.14, hspace=0.14)
def plot_Wind1Vel(columns=['Wind1VelX','Wind1VelY','Wind1VelZ'], xlim=[60, 90, 10], ylim=[-5, 35, 5], file='', toPDF=[]):
data = utils.readcsv(file)
fig, ax = plt.subplots()
X = data.get('Time')['Records']
Y = data.get(columns[0])['Records']
ax.plot(X, Y, label=data.get(columns[0])['Title'])
Y = data.get(columns[1])['Records']
ax.plot(X, Y, 'o--', markevery=(0.1), label=data.get(columns[1])['Title'])
Y = data.get(columns[2])['Records']
ax.plot(X, Y, '^:', markevery=(0.05, 0.1), label=data.get(columns[2])['Title'])
chart.adjust(ax, minor=[True, False, True, False], xlim=xlim, ylim=ylim, ylabel="Wind velocity (m/s)")
chart.draw(fig, toPDF)
def run(self):
if self.echo: print("Extrema Finder v0.2 (October 17 2018)")
if self.echo: print("|- Importing "+self.filebase+" ...")
self.dataInput = utils.readcsv(filename=self.filebase+'.out', header=self.header,
datarow=self.datarow, echo=self.echo)
# searching peak/valley upon each channel
for para in self.channels:
if self.echo: print("|- Searching local maximum/minimum of {}..."
.format(para), end="")
temp = self.find(para)
if self.echo: print(" Done !")
if self.saveToFile:
self.save(para, temp)
else:
self.dataOutput.append(temp)
print("|- The peak and valley of channel {} in {} are exported !".format(
self.channels, self.filebase))
def get_peak_valley(filename):
# Reference data
# ref_time = (75.20, 77.33, 78.94, 80.48, 82.04, 83.56, 85.1, 86.64, 88.17,
# 89.7) # time that occurs extremum deflection
ref_index = (1520, 1733, 1894, 2048, 2204, 2356, 2510, 2664, 2817, 2970
) # index of time in list of time
ref_deflX = (0.5529, -0.8429, 0.495, -0.6029, 0.5595, -0.5398, 0.5607,
-0.5233, 0.5454, -0.5063) # extremum deflection
# get peak and valley
data = utils.readcsv(filename='./Output/' + filename,
header=7,
datarow=6009)
deflX = data.get("YawBrTDxt")["Records"]
trd_deflX = [deflX[i] for i in ref_index]
# calculate difference
diff = sum([abs(x) - abs(y) for x, y in zip(trd_deflX, ref_deflX)])
return diff
def main():
testCase = 3
if testCase == 1: # simple case
with utils.cd(
"~/Eolien/Parameters/NREL_5MW_Onshore/Output/DLC2.3/withoutTRD/EOGO"
):
# bande of grid loss
filelist = [str(t) for t in utils.frange(74.0, 76.1, 0.1)]
channels = [
'YawBrTDxt', 'YawBrTDyt', 'YawBrFxp', 'YawBrFyp', 'TwHt4FLxt',
'TwHt4FLyt', 'TwrBsFxt', 'TwrBsFyt', 'TwrBsMxt', 'TwrBsMyt'
]
# # ----- Running on single processor
# for file in filelist:
# amplitude.find_peak_valley(file, header=7, datarow=6009,
# startline=12, channels=channels)
# ----- Running on multi processor
amp.find_peak_valley_multiprocess(filelist, 7, 6009, 12, channels)
wind = 'EOG'
speedRange = utils.frange(3.0, 25.1, 0.1) # wind speed [m/s]
timeRange = utils.frange(70.0, 80.1, 0.1) # grid loss time [s]
channels = [
'YawBrTDxt',
]
if testCase == 2: # complex case
with utils.cd("~/Eolien/Parameters/NREL_5MW_Onshore/Output/DLC2.3"):
# find peak and valley
filelist = [
"{}_{}_{}".format(wind, v, t) for v in speedRange
for t in timeRange
]
amp.find_peak_valley_multiprocess(list_filebase=filelist,
header=7,
datarow=6009,
startline=12,
channels=channels)
# find maximum amplitude
all_files = []
for v in speedRange:
temp = ["{}_{}_{}".format(wind, v, t) for t in timeRange]
all_files.append(temp)
all_results = []
for f in all_files:
resu = amp.Amplitude.max_p2p_amplitude(f, channels, '.ext',
True)
all_results.extend(resu)
# save to file/print to screen
output = amp.Amplitude.print(all_results, channels,
'max_amplitude.amp')
# compress files
output_files = [
elem["File"] + ".out" for elem in output[channels[0]]
]
pool = multiprocessing.Pool()
[
pool.apply_async(utils.compress,
args=(filename, True),
error_callback=utils.handle_error)
for filename in output_files
]
pool.close()
pool.join()
# get maxi amplitude for all time range and all speed
if testCase == 3:
with utils.cd("."):
all_files = [
"{}_{}_{}".format(wind, v, t) for v in speedRange
for t in timeRange
]
all_results = []
for f in all_files:
resu = amp.Amplitude.max_p2p_amplitude(f, channels, '.ext',
True)
all_results.extend(resu)
output = amp.Amplitude.print(all_results, channels,
'max_amplitude_ALL.amp')
# For testing ...
if testCase == 4:
with utils.cd("~/Eolien/Parameters/Python/DLC2.3/Output/DLC2.3"):
# find peak and valley
filelist = ["{}_O_{}".format(wind, t) for t in timeRange]
amp.find_peak_valley_multiprocess(list_filebase=filelist,
header=7,
datarow=6009,
startline=12,
channels=channels)
# find maximum amplitude
all_files = []
all_files.append(filelist)
all_results = []
for f in all_files:
resu = amp.Amplitude.max_p2p_amplitude(f, channels, '.ext',
False)
all_results.extend(resu)
# save to file/print to screen
output = amp.Amplitude.print(all_results, channels,
'max_amplitudeO.amp')
# To verifiy if .out file contains NaN
if testCase == 5:
with utils.cd("."):
list_filebase = utils.find(".", "*.out")
option = 1
# Option 1: through multiprocessing
if option == 1:
amp.find_peak_valley_multiprocess(list_filebase=list_filebase,
header=7,
datarow=6009,
startline=12,
channels=channels,
peak=False,
valley=False,
saveToFile=False)
# Option 2: one by one
if option == 2:
for f in list_filebase:
try:
utils.readcsv("./" + f + ".out")
except:
print("[ERROR] {} has an error during reading, please "
"check this file".format(f))
raise