def distance(n1, n2):
"""Calculate distance in km between two nodes"""
lat1, lon1 = n1[0], n1[1]
lat2, lon2 = n2[0], n2[1]
delta_lat = lat2 - lat1
delta_lon = lon2 - lon1
d = math.sin(math.radians(delta_lat) * 0.5) ** 2 + math.cos(math.radians(lat1)) * math.cos(math.radians(lat2)) \
* math.sin(math.radians(delta_lon) * 0.5) ** 2
return math.asin(math.sqrt(d)) * 12742
def _get_alpha(self):
if abs(self.dec) + self.radius > 89.9:
return 180
return math.degrees(
abs(
math.atan(
math.sin(math.radians(self.radius)) / np.sqrt(
abs(
math.cos(math.radians(self.dec - self.radius)) *
math.cos(math.radians(self.dec + self.radius)))))))
def get_alpha(radius, dec):
if abs(dec) + radius > 89.9:
return 180
return math.degrees(
abs(
math.atan(
math.sin(math.radians(radius)) / np.sqrt(
abs(
math.cos(math.radians(dec - radius)) *
math.cos(math.radians(dec + radius)))))))
def Evolvent(self):
'''Расчет эвольвенты зуба
'''
#Расчет эвольветы зуба
# Читаем данные из полей формы
# z = Количество зубьев
z = self.doubleSpinBox_Z.value()
# m = Модуль зуба
m = self.doubleSpinBox_m.value()
# a = Угол главного профиля
a = self.doubleSpinBox_a.value()
#b = Угол наклона зубьев
b = self.doubleSpinBox_b.value()
#ha = Коэффициент высоты головки
ha = self.doubleSpinBox_ha.value()
#pf = К-т радиуса кривизны переходной кривой
pf = self.doubleSpinBox_pf.value()
#c = Коэффициент радиального зазора
c = self.doubleSpinBox_c.value()
#x = К-т смещения исходного контура
x = self.doubleSpinBox_x.value()
#y =Коэффициент уравнительного смещения
y = self.doubleSpinBox_y.value()
# n= Количество точек (точность построения)
#n=int(self.doubleSpinBox_n.value())
n=100
# заполня переменные
# Делительный диаметр
d = z * m
# Высота зуба h=
h = 2.25 * m
# Высота головки ha =
hav = m
# Высота ножки hf=
hf = 1.25 * m
#Диаметр вершин зубьев
#da = d + (2 * m)*(ha+x+y)
da = d + 2 * (ha + x - y) * m
#Диаметр впадин (справочно)
#df = d -(2 * hf)
df = d -2 * (ha + c - x) * m
#Окружной шаг зубьев или Шаг зацепления по дуге делительной окружности: Pt или p
pt = math.pi * m
#Окружная толщина зуба или Толщина зуба по дуге делительной окружности: St или S
#Суммарный коэффициент смещений: XΣ
X = 0.60 + 0.12
# St = 0.5 * pf
# St = 0.5 * pt
St = 0.5 * pt + 2 * x * m * math.tan(math.radians(a))
#inv a
inva=math.tan(math.radians(a))-math.radians(a)
#Угол зацепления invαw
invaw= (2 * X - math.tan(math.radians(a))) / (10+26) + inva
#Угол профиля
at = math.ceil(math.degrees(math.atan(math.tan(math.radians(a))
/math.cos( math.radians(b)))))
# Диаметр основной окружности
db = d * math.cos(math.radians(at))
#Диаметр начала выкружки зуба
D = 2 * m * ( ( z/( 2 * math.cos(math.radians(b)) )-(1-x)) ** 2 +
((1-x)/math.tan(math.radians(at)))**2)**0.5
#Промежуточные данные
yi = math.pi/2-math.radians(at)
hy = yi/(n-1)
x0 = math.pi/(4*math.cos(math.radians(b))
)+pf*math.cos(math.radians(at))+math.tan(math.radians(at))
y0 = 1-pf*math.sin(math.radians(at))-x
C = (math.pi/2+2*x*math.tan(math.radians(a))
)/z+math.tan(math.radians(at))-math.radians(at)
#Расчетный шаг точек эвольвенты
hdy = (da-D)/(n-1)
dyi = da
fi = 2*math.cos(math.radians(b))/z*(x0+y0*math.tan(yi))
#Заполняем текстовые поля в форме
# Делительный диаметр
# self.lineEdit_d.setText(str(d))
# Высота зуба h=
# self.lineEdit_h.setText(str(h))
# Высота головки ha =
# self.lineEdit_ha.setText(str(hav))
# Высота ножки hf=
# self.lineEdit_hf.setText(str(hf))
# Диаметр вершин зубьев
# self.lineEdit_da.setText(str(da))
# Диаметр впадин (справочно)
# self.lineEdit_df.setText(str(df))
# Окружной шаг зубьев Pt=
# self.lineEdit_Pt.setText(str(math.ceil(pt)))
# Окружная толщина зуба St=
# self.lineEdit_St.setText(str(math.ceil(St)))
# Угол профиля
# self.lineEdit_at.setText(str(at))
# Диаметр основной окружности
# self.lineEdit_db.setText(str(math.ceil(db)))
# Создаем списки
List_dyi=[]
List_Di=[]
List_Yei=[]
List_Xei=[]
List_Minus_Xei=[]
List_Xdai=[]
List_Ydai=[]
List_yi=[]
List_Ai=[]
List_Bi=[]
List_fi=[]
List_Ypki=[]
List_Xpki=[]
List_Minus_Xpki=[]
# Заполняем нуливой (первый )индекс списка значениями
List_dyi.append(dyi)
List_Di.append( math.acos( db/ List_dyi[0] ) - math.tan( math.acos( db / List_dyi[0] ) ) + C )
List_Yei.append(dyi / 2*math.cos( List_Di[0]))
List_Xei.append(List_Yei[0]*math.tan(List_Di[0]))
List_Minus_Xei.append(-List_Xei[0])
List_Xdai.append(-List_Xei[0])
List_Ydai.append(((da/2)**2-List_Xdai[0]**2)**0.5)
hda=(List_Xei[0]-List_Minus_Xei[0])/(n-1)
# Заполняем первый (второй по счету )индекс списка значениями
List_dyi.append(dyi-hdy)
List_Di.append( math.acos(db/List_dyi[1])-math.tan(math.acos(db/List_dyi[1]))+C)
List_Yei.append( List_dyi[1]/2*math.cos(List_Di[1]))
List_Xei.append( List_Yei[1]* math.tan(List_Di[1]))
List_Minus_Xei.append(-List_Xei[1])
List_Xdai.append(List_Xdai[0]+hda)
List_Ydai.append(((da/2)**2-List_Xdai[1]**2)**0.5)
Xdai=List_Xdai[1]
dyi=dyi-hdy
# Начинаем заполнять списки в цикле
i=0
while i < n-2:
i=i+1
dyi=dyi-hdy
List_Di.append(math.acos(db/dyi)-math.tan(math.acos(db/dyi))+C)
Di=math.acos(db/dyi)-math.tan(math.acos(db/dyi))+C
Yei=dyi/2*math.cos(Di)
Xei=Yei*math.tan(Di)
List_dyi.append(dyi)
List_Yei.append(dyi/2*math.cos(Di))
List_Xei.append(Yei*math.tan(Di))
List_Minus_Xei.append(-Xei)
Xdai=Xdai+hda
List_Xdai.append(Xdai)
List_Ydai.append(((da/2)**2-Xdai**2)**0.5)
#Заполняем последний индекс списка
List_dyi[n-1]=D
# Заполняем нуливой (первый )индекс списка значениями
List_yi.append(yi)
List_Ai.append(z/(2*math.cos(math.radians(b)))-y0-pf*math.cos(List_yi[0]) )
List_Bi.append(y0*math.tan(List_yi[0])+pf*math.sin(List_yi[0]))
List_fi.append(fi)
List_Ypki.append((List_Ai[0] * math.cos(fi)+List_Bi[0] * math.sin(fi)) * m)
List_Xpki.append((List_Ai[0] * math.sin(fi)-List_Bi[0] * math.cos(fi)) * m)
List_Minus_Xpki.append(-List_Xpki[0])
# Начинаем заполнять списки в цикле
i=0
while i < n-2:
i=i+1
yi=yi-hy
List_yi.append(yi)
Ai = z / (2 * math.cos(math.radians(b)))-y0-pf*math.cos(yi)
List_Ai.append( z / (2 * math.cos(math.radians(b)))-y0-pf*math.cos(yi))
Bi =y0*math.tan(yi)+pf*math.sin(yi)
List_Bi.append(y0*math.tan(yi)+pf*math.sin(yi))
fi = 2*math.cos(math.radians(b))/z*(x0+y0*math.tan(yi))
List_fi.append(2*math.cos(math.radians(b))/z*(x0+y0*math.tan(yi)))
List_Ypki.append((Ai*math.cos(fi)+Bi*math.sin(fi))*m)
Ypki=(Ai*math.cos(fi)+Bi*math.sin(fi))*m
Xpki=(Ai*math.sin(fi)-Bi*math.cos(fi))*m
List_Xpki.append((Ai*math.sin(fi)-Bi*math.cos(fi))*m)
List_Minus_Xpki.append(-Xpki)
#Заполняем последний индекс списка
List_yi.append(yi-yi)
List_Ai.append(z/(2*math.cos(math.radians(b)))-y0-pf*math.cos(List_yi[n-1]) )
List_Bi.append(y0*math.tan(List_yi[n-1])+pf*math.sin(List_yi[n-1]))
List_fi.append(2*math.cos(math.radians(b))/z*(x0+y0*math.tan(List_yi[n-1])))
List_Ypki.append((List_Ai[n-1] * math.cos(fi)+List_Bi[n-1] * math.sin(List_fi[n-1])) * m)
List_Xpki.append((List_Ai[n-1] * math.sin(fi)-List_Bi[n-1] * math.cos(List_fi[n-1])) * m)
List_Minus_Xpki.append(-List_Xpki[n-1])
# self.WiPfileZub(List_Yei,List_Xei,List_Minus_Xei,List_Ypki,List_Xpki,List_Minus_Xpki,List_Ydai,List_Xdai)
self.GragEvolvent(List_Minus_Xei+List_Minus_Xpki,List_Yei+List_Ypki,n)
DFreza = self.lineEditDFreza.text()
VisotaYAxis = self.lineEditVisota.text()
Diametr = self.lineEditDiametr.text()
if DFreza and VisotaYAxis:
E30 = (int(DFreza)/2) +float(VisotaYAxis)
else:
E30 = 0
angi_B=0
if ValkosZub:
angie_A:float = 90# угол А треугольника по высоте детали
angie_B:float = float(b) #угол B треугольника по высоте детали ( угол наклона зуба по чертежу)
angie_Y:float = 180 - (angie_A + angie_B) # трерий уго треугольника по высоте детали
side_c:float = float(E30)# высота детали первая сторона треугольника
side_a = side_c * math.sin(math.radians(angie_A)) / math.sin(math.radians(angie_Y))# вторая сторона треугольника
side_b = side_c * math.sin(math.radians(angie_B)) / math.sin(math.radians(angie_Y))# третия сторона треугольника ( ось Х)
sid_a:float = float(Diametr)/2 # радиус детали первая и вторая тророны треугольника по торцу
# sid_a:float = float(self.lineEdit_da.text())/2 # радиус детали первая и вторая тророны треугольника по торцу
sid_c:float = sid_a
if sid_c < 10 :
sid_a:float = 10
sid_c:float = 10
angi_B = float('{:.3f}'.format(math.degrees(math.acos((sid_a**2+sid_c**2-side_b**2)/(2*sid_a*sid_c)))))
QMessageBox.about (self, "Ошибка " , "Диаметр шестерни задан меньше 20 мм. \n Введите риальный диаметр шестерни " )
else:
angi_B = float('{:.3f}'.format(math.degrees(math.acos((sid_a**2+sid_c**2-side_b**2)/(2*sid_a*sid_c)))))# результат угол поворота стола
self.label_da.setText(str(round(da,1)))
self.label_d.setText(str(round(d,1)))
self.label_at.setText(str(round(at,1)))
self.label_db.setText(str(round(db,1)))
self.label_df.setText(str(round(df,1)))
self.label_St.setText(str(round(St,1)))
self.label_Pt.setText(str(round(pt,1)))
self.label_hf.setText(str(round(hf,1)))
self.label_ha.setText(str(round(ha,1)))
self.label_h.setText(str(round(h,1)))
self.lineEditDiametr.setText(str(da))
self.lineEditUgol.setText(str(angi_B))
def __init__(self,
ra,
dec,
radius,
time_start,
time_end,
flag,
aws_profile,
aws_region,
s3_output_location,
local_output_location,
athena_database,
athena_workgroup,
query_life=10,
wait_time=0.1,
single_query=True):
self.ra = ra
self.dec = dec
self.radius = radius
self.time_start = time_start
self.time_end = time_end
self.flag = flag
self.s3_output_location = s3_output_location
self.local_output_location = local_output_location
self.athena_database = athena_database
self.athena_workgroup = athena_workgroup
self.query_life = query_life
self.wait_time = wait_time
self.single_query = single_query
sess = boto3.Session(profile_name=aws_profile, region_name=aws_region)
global athena_client, s3_client
athena_client = sess.client('athena')
s3_client = sess.client('s3')
self.s3_output_path = s3_output_location.replace('s3://',
'').split('/')
self.bucket = self.s3_output_path[0]
self.additional_s3_path = s3_output_location.replace(
's3://{}/'.format(self.bucket), '')
self.query = '''
SELECT *
FROM gPhoton_partitioned
WHERE zoneID = {}
AND dec BETWEEN {} AND {}
AND ra BETWEEN {} AND {}
AND ({}*cx + {}*cy + {}*cz) > {}
AND time >= {} AND time < {}
AND flag = {};
'''
# calculate_query_parameters
self.cx = math.cos(math.radians(self.dec)) * math.cos(
math.radians(self.ra))
self.cy = math.cos(math.radians(self.dec)) * math.sin(
math.radians(self.ra))
self.cz = math.sin(math.radians(self.dec))
self.alpha = self._get_alpha()
if (self.ra - self.alpha) < 0:
self.ra = self.ra + 360
self.zoneHeight = 30.0 / 3600.0
self.min_zoneid = int(
np.floor((self.dec - self.radius + 90.0) / self.zoneHeight))
self.max_zoneid = int(
np.floor((self.dec + self.radius + 90.0) / self.zoneHeight))
self.query_args_collection = {
'non-conditional': [
self.dec - self.radius, self.dec + self.radius,
self.ra - self.alpha, self.ra + self.alpha, self.cx, self.cy,
self.cz,
math.cos(math.radians(self.radius)), self.time_start,
self.time_end, self.flag
],
'conditional': [
self.dec - self.radius, self.dec + self.radius, 0,
self.ra - 360 + self.alpha, self.cx, self.cy, self.cz,
math.cos(math.radians(self.radius)), self.time_start,
self.time_end, self.flag
]
}
def vinc_inv(f, a, coordinate_a, coordinate_b):
"""
Returns the distance between two geographic points on the ellipsoid
and the forward and reverse azimuths between these points.
lats, longs and azimuths are in radians, distance in metres
:param f: flattening of the geodesic
:param a: the semimajor axis of the geodesic
:param coordinate_a: decimal coordinate given as named tuple coordinate
:param coordinate_b: decimal coordinate given as named tuple coordinate
Note: The problem calculates forward and reverse azimuths as: coordinate_a -> coordinate_b
"""
phi1 = math.radians(coordinate_a.lat)
lembda1 = math.radians(coordinate_a.lon)
phi2 = math.radians(coordinate_b.lat)
lembda2 = math.radians(coordinate_b.lon)
if (abs(phi2 - phi1) < 1e-8) and (abs(lembda2 - lembda1) < 1e-8):
return {'distance': 0.0, 'forward_azimuth': 0.0, 'reverse_azimuth': 0.0}
two_pi = 2.0 * math.pi
b = a * (1 - f)
TanU1 = (1 - f) * math.tan(phi1)
TanU2 = (1 - f) * math.tan(phi2)
U1 = math.atan(TanU1)
U2 = math.atan(TanU2)
lembda = lembda2 - lembda1
last_lembda = -4000000.0 # an impossibe value
omega = lembda
# Iterate the following equations,
# until there is no significant change in lembda
while (last_lembda < -3000000.0 or lembda != 0 and abs((last_lembda - lembda) / lembda) > 1.0e-9):
sqr_sin_sigma = pow(math.cos(U2) * math.sin(lembda), 2) + \
pow((math.cos(U1) * math.sin(U2) -
math.sin(U1) * math.cos(U2) * math.cos(lembda)), 2)
Sin_sigma = math.sqrt(sqr_sin_sigma)
Cos_sigma = math.sin(U1) * math.sin(U2) + math.cos(U1) * math.cos(U2) * math.cos(lembda)
sigma = math.atan2(Sin_sigma, Cos_sigma)
Sin_alpha = math.cos(U1) * math.cos(U2) * math.sin(lembda) / math.sin(sigma)
alpha = math.asin(Sin_alpha)
Cos2sigma_m = math.cos(sigma) - (2 * math.sin(U1) * math.sin(U2) / pow(math.cos(alpha), 2))
C = (f / 16) * pow(math.cos(alpha), 2) * (4 + f * (4 - 3 * pow(math.cos(alpha), 2)))
last_lembda = lembda
lembda = omega + (1 - C) * f * math.sin(alpha) * (sigma + C * math.sin(sigma) * \
(Cos2sigma_m + C * math.cos(sigma) * (
-1 + 2 * pow(Cos2sigma_m, 2))))
u2 = pow(math.cos(alpha), 2) * (a * a - b * b) / (b * b)
A = 1 + (u2 / 16384) * (4096 + u2 * (-768 + u2 * (320 - 175 * u2)))
B = (u2 / 1024) * (256 + u2 * (-128 + u2 * (74 - 47 * u2)))
delta_sigma = B * Sin_sigma * (Cos2sigma_m + (B / 4) * \
(Cos_sigma * (-1 + 2 * pow(Cos2sigma_m, 2)) - \
(B / 6) * Cos2sigma_m * (-3 + 4 * sqr_sin_sigma) * \
(-3 + 4 * pow(Cos2sigma_m, 2))))
s = b * A * (sigma - delta_sigma)
alpha12 = math.atan2((math.cos(U2) * math.sin(lembda)), \
(math.cos(U1) * math.sin(U2) - math.sin(U1) * math.cos(U2) * math.cos(lembda)))
alpha21 = math.atan2((math.cos(U1) * math.sin(lembda)), \
(-math.sin(U1) * math.cos(U2) + math.cos(U1) * math.sin(U2) * math.cos(lembda)))
if (alpha12 < 0.0):
alpha12 += two_pi
if (alpha12 > two_pi):
alpha12 -= two_pi
alpha21 += two_pi / 2.0
if alpha21 < 0.0:
alpha21 += alpha21 + two_pi
if alpha21 > two_pi:
alpha21 -= two_pi
return {"distance": s, "forward_azimuth": alpha12, "reverse_azimuth": alpha21}
def cone_search(ra,
dec,
radius,
time_start,
time_end,
flag,
aws_profile,
aws_region,
s3_output_location,
local_output_location,
athena_database,
athena_workgroup,
query_life=10,
wait_time=0.1,
single_query=True):
def query_athena(query, query_args):
query = query.format(*query_args)
response = athena_client.start_query_execution(
QueryString=query,
QueryExecutionContext={'Database': athena_database},
ResultConfiguration={'OutputLocation': s3_output_location},
WorkGroup=athena_workgroup)
print('Query submitted:\n{}\n'.format(query))
rsp = athena_client.get_query_execution(
QueryExecutionId=response['QueryExecutionId'])
succeeded_query = True if rsp['QueryExecution']['Status'][
'State'] == 'SUCCEEDED' else False
num_sec_query_has_been_running = 0
# check to see if the query has succeeded
while not succeeded_query:
if num_sec_query_has_been_running >= query_life:
print(
'QUERY CANCELLED: Query {} has been running for ~{} seconds.'
.format(response['QueryExecutionId'],
num_sec_query_has_been_running))
_ = athena_client.stop_query_execution(
QueryExecutionId=response['QueryExecutionId'])
return None
if num_sec_query_has_been_running % 60 == 0 and num_sec_query_has_been_running:
duration = int(num_sec_query_has_been_running / 60)
word = 'minutes' if duration > 1 else 'minute'
print('...Query has been running for ~{} {}.'.format(
duration, word))
# wait until query has succeeded to start the next query
if num_sec_query_has_been_running + wait_time > query_life:
sleep_time = query_life - num_sec_query_has_been_running
else:
sleep_time = wait_time
time.sleep(sleep_time)
num_sec_query_has_been_running += sleep_time
rsp = athena_client.get_query_execution(
QueryExecutionId=response['QueryExecutionId'])
succeeded_query = True if rsp['QueryExecution']['Status'][
'State'] == 'SUCCEEDED' else False
return response['QueryExecutionId']
sess = boto3.Session(profile_name=aws_profile, region_name=aws_region)
athena_client = sess.client('athena')
s3_client = sess.client('s3')
s3_output_path = s3_output_location.replace('s3://', '').split('/')
bucket = s3_output_path[0]
additional_s3_path = s3_output_location.replace('s3://{}/'.format(bucket),
'')
queries = {
'single':
'''
SELECT *
FROM gPhoton_partitioned
WHERE zoneID BETWEEN {} AND {}
AND dec BETWEEN {} AND {}
AND ra BETWEEN {} AND {}
AND ({}*cx + {}*cy + {}*cz) > {}
AND time >= {} AND time < {}
AND flag = {};
''',
'multiple':
'''
SELECT *
FROM gPhoton_partitioned
WHERE zoneID = {}
AND dec BETWEEN {} AND {}
AND ra BETWEEN {} AND {}
AND ({}*cx + {}*cy + {}*cz) > {}
AND time >= {} AND time < {}
AND flag = {};
'''
}
cx = math.cos(math.radians(dec)) * math.cos(math.radians(ra))
cy = math.cos(math.radians(dec)) * math.sin(math.radians(ra))
cz = math.sin(math.radians(dec))
alpha = get_alpha(radius, dec)
if (ra - alpha) < 0:
ra = ra + 360
zoneHeight = 30.0 / 3600.0
min_zoneid = int(np.floor((dec - radius + 90.0) / zoneHeight))
max_zoneid = int(np.floor((dec + radius + 90.0) / zoneHeight))
query_args_collection = {
'non-conditional': [
dec - radius, dec + radius, ra - alpha, ra + alpha, cx, cy, cz,
math.cos(math.radians(radius)), time_start, time_end, flag
],
'conditional': [
dec - radius, dec + radius, 0, ra - 360 + alpha, cx, cy, cz,
math.cos(math.radians(radius)), time_start, time_end, flag
]
}
query_collection = ''
query_argument_collection = []
for zoneid in range(min_zoneid, max_zoneid + 1):
query = queries['single'] if single_query else queries['multiple']
zone_args = [min_zoneid, max_zoneid] if single_query else [zoneid]
query_args = zone_args + query_args_collection['non-conditional']
if (ra + alpha) > 360:
query = query.replace(';',
'') + '\n UNION ALL\n' + query
additional_args = [min_zoneid, max_zoneid
] if single_query else [zoneid]
query_args = query_args + additional_args + query_args_collection[
'conditional']
temp_query = query.replace(
';', ''
) + '\n UNION ALL\n' if not single_query and zoneid != max_zoneid else query
query_collection += temp_query
query_argument_collection.extend(query_args)
if single_query:
break
start_time = time.time()
execution_id = query_athena(query_collection, query_argument_collection)
print('Time taken to query: ~{:.4f} seconds'.format(time.time() -
start_time))
# get single CSV or accumulate the CSVs from the different SELECT statements
dfs = []
download_paths = []
if execution_id is not None:
path_to_csv = os.path.join(additional_s3_path, execution_id + '.csv')
download_path = os.path.join(local_output_location,
execution_id + '.csv')
start_time = time.time()
s3_client.download_file(bucket, path_to_csv, download_path)
print('Time taken to download: ~{:.4f} seconds'.format(time.time() -
start_time))
dfs.append(pd.read_csv(download_path, engine='python'))
download_paths.append(download_path)
if len(dfs):
df = pd.concat(dfs)
output_location = os.path.join(local_output_location,
str(uuid4()) + '.csv')
df.to_csv(output_location, index=False)
print('\nData written to {}\n'.format(output_location))
for download_path in download_paths:
os.remove(download_path)
print(df.head())
else:
print('No CSVs were found.')