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')