def test(self):
result = ["A b ", "a B "]
self.assertEqual(wave("a b "), result)
result = ["This is a few words", "tHis is a few words", "thIs is a few words", "thiS is a few words", "this Is a few words", "this iS a few words", "this is A few words", "this is a Few words", "this is a fEw words", "this is a feW words", "this is a few Words", "this is a few wOrds", "this is a few woRds", "this is a few worDs", "this is a few wordS"]
self.assertEqual(wave("this is a few words"), result)
result = []
self.assertEqual(wave(""), result)
result = [" Gap ", " gAp ", " gaP "]
self.assertEqual(wave(" gap "), result)
def __init__(self,H=None,T=None,numFreq=10001):
self.sim = simulation.simulation()
self.waves = wave.wave(H,T,numFreq)
self.desiredRespAmp = 0.0 # [-] Desired response amplitude. M_d in documentation.
self.waveHeightDesired = None # [m] Height of wave desired if renormalizing amplitudes
# calculated variables
self._RAO = None # [-] Complex RAO array N x 6
self._RAOdataReadIn = np.zeros(6,dtype=bool) # [-] What RAO dimensions did we read in?
self._RAOdataFileName = ['','','','','',''] # [-] Name of the data file read in for RAO
self._CoeffA_Rn = None # [ ] MLER coefficients A_{R,n}
self._S = None # [m^2-s] Conditioned wave spectrum vector
self._A = None # [m^2-s] 2*(conditioned wave spectrum vector)
self._phase = 0.0 # [rad] Wave phase
self._Spect = None # [-] Spectral info
self._rescaleFact = None # [-] Rescaling factor for renormalizing the amplitude
self._animation = None # Object storing animation information
self._respExtremes = None # [m] Array containing min/max of the simulated response
def __init__(self,H=None,T=None,numFreq=10001):
self.sim = simulation.simulation()
self.waves = wave.wave(H,T,numFreq)
self.desiredRespAmp = 0.0 # [-] Desired response amplitude. M_d in documentation.
self.waveHeightDesired = None # [m] Height of wave desired if renormalizing amplitudes
# calculated variables
self._RAO = None # [-] Complex RAO array N x 6
self._RAOdataReadIn = np.zeros(6,dtype=bool) # [-] What RAO dimensions did we read in?
self._RAOdataFileName = ['','','','','',''] # [-] Name of the data file read in for RAO
self._CoeffA_Rn = None # [ ] MLER coefficients A_{R,n}
self._S = None # [m^2-s] Conditioned wave spectrum vector
self._A = None # [m^2-s] 2*(conditioned wave spectrum vector)
self._phase = 0.0 # [rad] Wave phase
self._Spect = None # [-] Spectral info
self._rescaleFact = None # [-] Rescaling factor for renormalizing the amplitude
self._animation = None # Object storing animation information
self._respExtremes = None # [m] Array containing min/max of the simulated response
def process_wave(filenames, classes, classes_io, classes_nums, fname_base_len, val=False):
data_x = []
data_y = []
data_y_io = []
for i, filename in enumerate(filenames):
printProgressBar(i+1, len(filenames))
img = cv2.imread(filename, 0)
im = img.copy()
h = wave.wave(im)
index = classes.index(filename[fname_base_len:-13])
data_x.append(h)
if val:
inout = int(classes_io[int(classes[i].split(" ")[1])])
data_y.append(int(classes[i].split(" ")[1]))
data_y_io.append(inout)
else:
data_y.append(int(classes_nums[index]))
data_y_io.append(int(classes_io[index]))
data_x_scaled = preprocessing.scale(data_x)
return data_x_scaled, data_y, data_y_io
def test_rand(self):
from random import randint
def wave2(str):
result = []
str = list(str)
for b in range(0,len(str)):
if str[b] != " ":
temp = []
for i in range(0, len(str)):
if i == b:
temp.append(str[i].upper())
else:
temp.append(str[i])
result.append("".join(temp))
return result
letters = list("abcd efghi jklmno pqrstu vwxyz")
for _ in range (1,97):
word = []
for _ in range(0,randint(0,100)):
word.append(letters[randint(0,len(letters)-1)])
word = "".join(word)
result = wave2(word)
self.assertEqual(wave(word), result)
qNour = defaultFill(1,dtNourish,500,10*dtNourish,T+dtNourish)
# initialize time steps
# loop through and update wave accordingly
t = 0
while t<T:
#interpolate waves
hs = interpParam(t,Hs,dtWave)
tp = interpParam(t,Tp,dtWave)
d = interpParam(t,D,dtWave)
qN = interpParam(t,qNour,dtNourish)
dStore.append(d)
# print(d)
#use the offshore contour to calculate wave refraction
wv = wave(hs,tp,d,test.normalsOff)
#wave angle relative to offshore contour
wv.orient()
#refract and shoal waves -> still need to add difraction
hb = wv.iteration()
#init morphology
bed = morph(test.x,test.y,test.yInit,test.xPoints,test.qPoints,test.swl,
test.yStr,test.xStr,hs,tp,1)
#calculate potential LST
Q = bed.CERC(wv.thetaB,hb,wv.Cgb,wv.sgn,rot,test.normals)
#quantify erosion and accretion
Q,qAn = bed.orient(wv.thetaB,test.normals,rot,Q,wv.sgn)
#add source and sinks
bed.source_sinks(qi=qN)
Dg = bed.A*test.yAdd**(2/float(3))
dyPot,dy = bed.update(6,2,dt,Q,Q,hb,rot,d,Dg,0.8)
for t in test_names:
fn = os.path.join(directory, t[7:])
img = cv2.imread(fn)
# print(fn)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# GBP
start = time.time()
gbp.gbp(gray)
gbp_times.append(time.time() - start)
# CENTRIST
start = time.time()
centrist.centrist_im(cl, gray)
centrist_times.append(time.time() - start)
# WHGO
start = time.time()
whgo.whgo(gray, 16)
whgo_times.append(time.time() - start)
# WAVE
start = time.time()
wave.wave(gray)
wave_times.append(time.time() - start)
print("GBP time", np.mean(gbp_times))
print("CENTRIST time", np.mean(centrist_times))
print("WHGO time", np.mean(whgo_times))
print("WAVE time", np.mean(wave_times))
#symulate full system
import wave as wv
wave = wv.wave(80000, 0.00001, 'results/solution.pvd',
'meshes/cracked_beam.xml', "full", "dontcare", 80)
print('Initializing FEM...')
wave.initiate_fem()
print('Time integrating...')
wave.mid_point()
print('Genearting the weight matrix...')
wave.generate_X_matrix()
print('Saving snapshots...')
wave.save_snapshots()
print('complete.')
# genearate reduced basis
print('Generateing reduced basis...')
import mor as mr
mor = mr.Mor()
#mor.set_basis_size(100)
#mor.POD_energy()
mor.initiate_greedy()
mor.greedy(100, 100)
mor.save_basis()
print('complete.')
# simulate reduced system
print('simulating Iweighted reduced system...')
import wave as wv
frequency = 440.0 * STEP**note
volume = volume_step * (MAX_VOLUME / 20)
stdscr.addstr(1, 2, NOTES[note % 12] + ' ' * 80)
stdscr.addstr(3, 2, str(score) + ' points')
stdscr.addstr(4, 2, str(health) + ' health')
stdscr.move(10, 2)
if target_position >= TARGET_FRAMES:
if frequency >= target_frequency / STEP and frequency <= target_frequency * STEP:
score += 1
wave_bytes, target_position, time = wave(frames=FRAMES * 2,
left=score_tones,
right=score_tones,
position=1,
max_position=1,
volume=MAX_VOLUME,
bitrate=BITRATE,
time=time)
else:
health -= 1
wave_bytes, target_position, time = wave(
frames=FRAMES * 4,
left=health_tones[:health],
right=health_tones[:health],
position=1,
max_position=1,
volume=MAX_VOLUME,
bitrate=BITRATE,
time=time)
target_frequency = 440.0 * STEP**random.randint(
dsun_meters = i0.meta['dsun_obs'],
occultation = True) for line in lonlatgc]
pxcoord = [np.array(np.round(np.nan_to_num(wcs.convert_data_to_pixel(line[0], line[1],
i0.scale.values(), i0.reference_pixel.values(),
[0,0]))), #i0.reference_coordinate.values()))),
dtype = np.int) for line in xycoord]
pxcoord_arr = np.array(pxcoord) # shape for default -> (360,2,180)
# Convert the values from physical to pixel values
deltaX = wcs.rsun_meters * np.deg2rad(step) / 1e3 # km
velocity_px = velocity / deltaX
deltaT = 1 / velocity_px # sec
cadencewave = int(cadence / deltaT)
front = int(150e3 / deltaX)
# Create the wave
wavearr, tsteps = wave.wave(len(line[0]), velocity = velocity_px, cadence = cadencewave,
wave_func = wave.square, wave_args = {'size': front })
messa = \
"""The velocity used is: {velocity} km/s
with a front size of: {front} km
and a cadence of: {cadence} s""".format(velocity = velocity,
front = front * deltaX,
cadence = cadencewave * deltaT)
print messa
# Create t-x-y array for all the images
mask_series = np.zeros((wavearr.shape[0],) + i0.shape)
time0 = stime.parse_time(i0.meta['date-obs'])
times_str = [(time0 + datetime.timedelta(0,deltaT * ts + cadence)).isoformat() for ts in tsteps] # the first image is at dt = cadence from i0.
for ind, mask in enumerate(mask_series):
for line in pxcoord_arr:
def test_string2(self):
result = [
"Codewars", "cOdewars", "coDewars", "codEwars", "codeWars",
"codewArs", "codewaRs", "codewarS"
]
self.assertEqual(wave("codewars"), result)
def test_string1(self):
result = ["Hello", "hEllo", "heLlo", "helLo", "hellO"]
self.assertEqual(wave("hello"), result)
def test_string5(self):
result = [" Gap ", " gAp ", " gaP "]
self.assertEqual(wave(" gap "), result)
def test_string4(self):
result = [
"Two words", "tWo words", "twO words", "two Words", "two wOrds",
"two woRds", "two worDs", "two wordS"
]
self.assertEqual(wave("two words"), result)
def test_string3(self):
result = []
self.assertEqual(wave(""), result)