def test1():
xy = [[1,1], [2,5], [3,3], [4,7], [5,6], [6,5], [7,4], [8,3], [9,2], [10,1]]
n = len(xy)
c = interpolator.buildSpline(xy, n)
res = []
for i in [1.2, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5]:
res.append(interpolator.interpolate(xy, c, i))
print res
def blade_angle2cp(prop, blade_angle, J, tip_mach):
"""Returns propeller power coefficient (Cp), given blade angle, advance ratio (J) and the mach number of the blade tip.
"""
temp_cps = []
temp_blade_angles = []
for cp in N.arange(prop.blade_angle_Cp_min, prop.blade_angle_Cp_max, 0.005):
temp_cps.append(cp)
temp_blade_angles.append(cp2blade_angle(prop, cp, J, tip_mach))
i = N.searchsorted(temp_blade_angles, blade_angle)
return I.interpolate(temp_blade_angles[i : i + 2], temp_cps[i : i + 2], blade_angle)
def blade_angle2cp(prop, blade_angle, J, tip_mach):
"""Returns propeller power coefficient (Cp), given blade angle, advance ratio (J) and the mach number of the blade tip.
"""
temp_cps = []
temp_blade_angles = []
for cp in N.arange(prop.blade_angle_Cp_min, prop.blade_angle_Cp_max, .005):
temp_cps.append(cp)
temp_blade_angles.append(cp2blade_angle(prop, cp, J, tip_mach))
i = N.searchsorted(temp_blade_angles, blade_angle)
return I.interpolate(temp_blade_angles[i:i + 2], temp_cps[i:i + 2],
blade_angle)
def test2():
f = open('D:\\LEARN\\AnaNas-Python\\1.txt')
xy = []
i = 0
for line in f:
data = re.findall('\d+\.*\d*\.*\d*', str(line))
time_com = data[0].split('.')
time = float(time_com[0])*3600 + float(time_com[1])*60 + float(time_com[2])
xy.append([time, float(data[2])])
int_time = xy[0][0]
for i in xy:
i[0] = i[0]-int_time
n = len(xy)
c = interpolator.buildSpline(xy, n)
res = []
for i in range(0, int(xy[int(len(xy)-1)][0])):
res.append(interpolator.interpolate(xy, c, i))
res_file = open('D:\\LEARN\\AnaNas-Python\\res.txt', 'w')
for i in range(0, int(xy[int(len(xy)-1)][0])):
res_file.write(str(i)+' '+str(res[i])+'\r\n')
init_file = open('D:\\LEARN\\AnaNas-Python\\init.txt', 'w')
for i in range(0,int(len(xy)-1)):
init_file.write(str(xy[i][0])+' '+str(xy[i][1])+'\r\n')
print "say doing minfind"
pixel_coords_rows = getpoints.getpoints(diffratio)
print "say doing jonathan transform"
pointcloud = constants.default_threedize_phi_angles(pixel_coords_rows)
plt.plot(pointcloud[:,0], pointcloud[:,1])
plt.title("tranformed pointcloud")
plt.show()
xspace = np.linspace(4, 40, 60)
yspace = np.linspace(18, 44, int(60 * (44 - 18) / 36.))
xmesh, ymesh = np.meshgrid(xspace, yspace)
print "say interpolating pointcloud"
zmesh, _ = interpolator.interpolate(xmesh, ymesh, pointcloud)
print "say making string"
string = toMinecraft.createString(zmesh)
plt.imshow(zmesh)
plt.show()
print "say writing to minecraft"
for line in string.split("\n"):
print(line)
print "say done making commands"
break
reload(constants)
reload(interpolator)
reload(toMinecraft)
diffratio = camerastream.getCamStream()
print "say doing minfind"
pixel_coords_rows = getpoints.getpoints(diffratio)
print "say doing jonathan transform"
pointcloud = constants.default_threedize_phi_angles(pixel_coords_rows)
plt.plot(pointcloud[:, 0], pointcloud[:, 1])
plt.title("tranformed pointcloud")
plt.show()
xspace = np.linspace(4, 40, 60)
yspace = np.linspace(18, 44, int(60 * (44 - 18) / 36.))
xmesh, ymesh = np.meshgrid(xspace, yspace)
print "say interpolating pointcloud"
zmesh, _ = interpolator.interpolate(xmesh, ymesh, pointcloud)
print "say making string"
string = toMinecraft.createString(zmesh)
plt.imshow(zmesh)
plt.show()
print "say writing to minecraft"
for line in string.split("\n"):
print(line)
print "say done making commands"
def decipher(filename):
intername = interpolate(filename)
PROJECT_PATH = os.getcwd()
clf = tree.DecisionTreeRegressor()
with open('my_dumped_classifier.pkl', 'rb') as fid:
clf = cPickle.load(fid)
newfile = "newfile.csv"
try:
os.remove(newfile)
except OSError:
pass
f = open(filename, 'rU')
reader = csv.reader(f, dialect=csv.excel_tab)
data = [row for row in reader]
f.close()
f = open(newfile, "wb")
writer = csv.writer(f, dialect=csv.excel_tab)
for x in data:
if (x!=data[0]):
writer.writerow(x)
f.close()
testset = genfromtxt(open(intername,'r'), dtype=None, delimiter=',',usecols = (0,1,2,3,4,5))
dateset = genfromtxt(open(newfile,'r'), dtype=None, delimiter=',',usecols = (0,5))
index = 0
for date in testset:
if(date[5]=='null' or date[5]=='' or math.isnan(date[5])):
index += 1
newtestset = numpy.zeros(index*7).reshape(index,7)
isodate = [0 for x in range(index)]
index1 = 0
for date in testset:
if(date[5]=='null' or date[5]=='' or math.isnan(date[5])):
realdate = dateset[index1][0]
utc = arrow.get(realdate)
year = realdate[0:4]
month = utc.format('M')
day = utc.format('d')
day1 = utc.format('D')
time = realdate[11:13] + realdate[14:16]
print time
float(month)
float(day)
float(time)
float(date[1])
float(date[3])
newdata1 = [month,day,time,0,date[2],date[3],0]
newtestset[index1] = newdata1
isodate[index1] = realdate
index1+=1
#predicted_probs = [[x[4]] for index, x in enumerate(clf.predict(test))]
predicted_probs = clf.predict(newtestset)
output = [["" for i in range(2)] for j in range(index)]
for i in range(index):
output[i][0] = isodate[i]
print output[i][0]
output[i][1] = predicted_probs[i]
try:
os.remove('output.txt')
except OSError:
pass
#savetxt('output.text', output, delimiter=',', fmt='%s,%s')
savetxt('output.txt', output, delimiter=',', fmt='%s')
return os.path.join(PROJECT_PATH, 'output.txt')
