def Tdfind(wv, p):
"""
Tdfind(wv, p)
Calculates the due point temperature of an air parcel.
Parameters
- - - - - -
wv : float
Mixing ratio (kg/kg).
p : float
Pressure (Pa).
Returns
- - - -
Td : float
Dew point temperature (K).
Examples
- - - - -
>>> Tdfind(0.001, 8.e4)
253.39429263963504
References
- - - - - -
Emanuel 4.4.14 p. 117
"""
c = constants();
e = wv * p / (c.eps + wv);
denom = (17.67 / np.log(e / 611.2)) - 1.;
Td = 243.5 / denom;
Td = Td + 273.15;
return Td
def calcTvDiff(press, thetae0, interpTenv, interpTdEnv):
"""
Calculates the virtual temperature difference between the thetae0
moist adiabat and a given sounding at some pressure.
Parameters
- - - - - -
press: pressure (Pa)
thetae0: equivalent potential temperature of the adiabat (K)
interpTenv: interpolator for environmental temperature (deg C)
interpTdEnv: interpolator for environmental dew point temperature (deg C)
Returns
- - - - - -
TvDiff: the virtual temperature difference at pressure press
between the thetae0 moist adiabat and the given sounding (K).
"""
c = constants()
Tcloud=findTmoist(thetae0,press)
wvcloud=wsat(Tcloud,press)
Tvcloud=Tcloud*(1. + c.eps*wvcloud)
Tenv=interpTenv(press*1.e-2) + c.Tc
Tdenv=interpTdEnv(press*1.e-2) + c.Tc
wvenv=wsat(Tdenv,press)
Tvenv=Tenv*(1. + c.eps*wvenv)
return Tvcloud - Tvenv
def L(T):
"""
L(T)
Calculates the latent heat of vapourization for a given
temperature 'T'.
Parameters
- - - - - -
T : float
Temperature (K).
Returns
- - - -
theL : float
Latent heat of vaporization (J/kg)
Examples
- - - - -
>>> L(300.)
2438708.0
"""
c=constants();
theL = c.lv0 + (c.cpv - c.cl) * (T - c.Tc);
return theL
def thetaes(T, p):
"""
thetaes(T, p)
Calculates the pseudo equivalent potential temperature of an air
parcel.
Parameters
- - - - - -
T : float
Temperature (K).
p : float
Pressure (Pa).
Returns
- - - -
thetaep : float
Pseudo equivalent potential temperature (K).
Notes
- - -
It should be noted that the pseudo equivalent potential
temperature (thetaep) of an air parcel is not a conserved
variable.
References
- - - - - -
Emanuel 4.7.9 p. 132
Examples
- - - - -
>>> thetaes(300., 8.e4)
412.97362667593831
"""
c = constants();
# The parcel is saturated - prohibit supersaturation with Td > T.
Tlcl = T;
wv = wsat(T, p);
thetaval = theta(T, p, wv);
power = 0.2854 * (1 - 0.28 * wv);
thetaep = thetaval * np.exp(wv * (1 + 0.81 * wv) * \
(3376. / Tlcl - 2.54))
#
# peg this at 450 so rootfinder won't blow up
#
if thetaep > 450.:
thetaep = 450;
return thetaep
def thetaes(T, p):
"""
thetaes(T, p)
Calculates the pseudo equivalent potential temperature of an air
parcel.
Parameters
- - - - - -
T : float
Temperature (K).
p : float
Pressure (Pa).
Returns
- - - -
thetaep : float
Pseudo equivalent potential temperature (K).
Notes
- - -
It should be noted that the pseudo equivalent potential
temperature (thetaep) of an air parcel is not a conserved
variable.
References
- - - - - -
Emanuel 4.7.9 p. 132
Examples
- - - - -
>>> thetaes(300., 8.e4)
412.97362667593831
"""
c = constants()
# The parcel is saturated - prohibit supersaturation with Td > T.
Tlcl = T
wv = wsat(T, p)
thetaval = theta(T, p, wv)
power = 0.2854 * (1 - 0.28 * wv)
thetaep = thetaval * np.exp(wv * (1 + 0.81 * wv) * \
(3376. / Tlcl - 2.54))\
#if thetaep > 550:
# thetaep = 550
return thetaep
def __init__(self): #{{{
# classtype=model.properties
# for classe in dict.keys(classtype):
# print classe
# self.__dict__[classe] = classtype[str(classe)]
self.mesh = mesh2d()
self.mask = mask()
self.geometry = geometry()
self.constants = constants()
self.smb = SMBforcing()
self.basalforcings = basalforcings()
self.materials = matice()
self.damage = damage()
self.friction = friction()
self.flowequation = flowequation()
self.timestepping = timestepping()
self.initialization = initialization()
self.rifts = rifts()
self.slr = slr()
self.debug = debug()
self.verbose = verbose()
self.settings = settings()
self.toolkits = toolkits()
self.cluster = generic()
self.balancethickness = balancethickness()
self.stressbalance = stressbalance()
self.groundingline = groundingline()
self.hydrology = hydrologyshreve()
self.masstransport = masstransport()
self.thermal = thermal()
self.steadystate = steadystate()
self.transient = transient()
self.levelset = levelset()
self.calving = calving()
self.gia = giaivins()
self.autodiff = autodiff()
self.inversion = inversion()
self.qmu = qmu()
self.amr = amr()
self.results = results()
self.outputdefinition = outputdefinition()
self.radaroverlay = radaroverlay()
self.miscellaneous = miscellaneous()
self.private = private()
def run(self):
self.connected = True
print "Connection %d started" % self.connection_id
constant = constants()
try:
recv_data = self.client.recv(self.buffer_size)
try:
recv_packet = packet(recv_data)
except packet_exception as e:
self.master.debug("[%d] Invalid Packet, closing connection" % self.connection_id)
self.connected = False
print "packet type is ",recv_packet.packet_type
if recv_packet.packet_type == constant.JOIN:
doc = recv_packet.doc_name
print doc, "this is the doc... 1"
print doc_index;
if doc in doc_index.keys():
send_packet = packet()
send_packet.packet_type = constant.Dummy
send_packet.list_of_ip = doc_index[doc]
self.__send(send_packet)
doc_index[doc].append([recv_packet.my_host_name,recv_packet.my_port_name]);
else:
doc = recv_packet.doc_name
print doc, "this is the doc... 2"
print doc_index;
print "i am in else...",recv_packet.my_host_name,recv_packet.my_port_name
print "doc_index",doc_index
doc_index[doc] = list([[recv_packet.my_host_name,recv_packet.my_port_name]]);
print "doc_index",doc_index
send_packet = packet()
send_packet.packet_type = constant.NewFile
self.__send(send_packet)
print "client want to join " + doc
except socket.timeout:
#timeout hit
print "[%d] Client timed out, terminating thread" % self.connection_id
self.connected = False
except socket.error as e:
self.master.debug("socket.error (%d, %s)" % (e.errno, e.strerror))
if e.errno == 10054:
print "Connection closed by the client..."
self.connected = False
#little nap for the cpu
time.sleep(0.3)
self.terminate()
def __init__(self,text_data=None):
self.packet_id = -1
self.packet_type = constants().Dummy
self.stamp = 0
self.my_host_name = None
self.my_port_name = None
self.data = None
self.fields = {}
self.list_of_ip = []
if text_data is not None:
self.__from_string(text_data)
else:
self.packet_id = get_packet_id()
self.packet_type = self.Ping
self.fields = {}
def thetal(T, p, wv, wl):
"""
thetal(T,p,wv,wl)
Calculates the liquid water potential temperature of a parcel.
Parameters
- - - - - -
T : float
Temperature (K).
p : float
Pressure (Pa)
wv : float
Vapour mixing ratio (kg/kg).
wl : float
Liquid water potential temperature (kg/kg).
Returns
- - - -
thetalOut : float
Liquid water potential temperature (K).
References
- - - - - -
Emanuel 4.5.15 p. 121
Examples
- - - - -
>>> thetal(300., 8.e4, 0.03, 0.01)
298.21374486200278
"""
c = constants()
Lval = L(T)
wt = wv + wl
chi = (c.Rd + wt * c.Rv) / (c.cpd + wt * c.cpv)
gamma = wt * c.Rv / (c.cpd + wt * c.cpv)
thetaVal = T * (c.p0 / p)**chi
term1 = (1 - wl / (1. + wt)) * (1 - wl / (c.eps + wt))**(chi - 1)
term2 = (1 - wl / wt)**(-1. * gamma)
cp = c.cpd + wt * c.cpv
thetalOut = thetaVal * term1 * term2 \
* np.exp(-1. * Lval * wl/(cp*T))
return thetalOut
def thetal(T,p,wv,wl):
"""
thetal(T,p,wv,wl)
Calculates the liquid water potential temperature of a parcel.
Parameters
- - - - - -
T : float
Temperature (K).
p : float
Pressure (Pa)
wv : float
Vapour mixing ratio (kg/kg).
wl : float
Liquid water potential temperature (kg/kg).
Returns
- - - -
thetalOut : float
Liquid water potential temperature (K).
References
- - - - - -
Emanuel 4.5.15 p. 121
Examples
- - - - -
>>> thetal(300., 8.e4, 0.03, 0.01)
298.21374486200278
"""
c = constants();
Lval = L(T);
wt = wv + wl;
chi = (c.Rd + wt * c.Rv) / (c.cpd + wt * c.cpv);
gamma = wt * c.Rv / (c.cpd + wt * c.cpv);
thetaVal = T * (c.p0 / p) ** chi;
term1 = (1 - wl / (1. + wt)) * (1 - wl / (c.eps + wt)) ** (chi-1)
term2 = (1 - wl / wt) ** (-1. * gamma);
cp = c.cpd + wt * c.cpv;
thetalOut = thetaVal * term1 * term2 \
* np.exp(-1. * Lval * wl/(cp*T));
return thetalOut
def __init__(self, src='multi_plant', labels='multi_label'):
self.c = constants()
self.window1 = self.c.window.window1
self.window2 = self.c.window.window2
cv.namedWindow(self.window1)
cv.namedWindow(self.window2)
cv.moveWindow(self.window2, 550, 90)
cv.createTrackbar(self.c.HSV.low_H_name, self.window1,
self.c.HSV.low_H, self.c.HSV.max_value_H,
self.on_low_H_thresh_trackbar)
cv.createTrackbar(self.c.HSV.high_H_name, self.window1,
self.c.HSV.high_H, self.c.HSV.max_value_H,
self.on_high_H_thresh_trackbar)
cv.createTrackbar(self.c.HSV.low_S_name, self.window1,
self.c.HSV.low_S, self.c.HSV.max_value,
self.on_low_S_thresh_trackbar)
cv.createTrackbar(self.c.HSV.high_S_name, self.window1,
self.c.HSV.high_S, self.c.HSV.max_value,
self.on_high_S_thresh_trackbar)
cv.createTrackbar(self.c.HSV.low_V_name, self.window1,
self.c.HSV.low_V, self.c.HSV.max_value,
self.on_low_V_thresh_trackbar)
cv.createTrackbar(self.c.HSV.high_V_name, self.window1,
self.c.HSV.high_V, self.c.HSV.max_value,
self.on_high_V_thresh_trackbar)
self.plants, self.plant_groups, self.labels = self.prepare_plant_collection(
src, labels)
# source https://docs.opencv.org/3.4/d1/dc5/tutorial_background_subtraction.html
for key in self.plant_groups:
if self.c.bgsub.mod == 'MOG2':
backSub = cv.createBackgroundSubtractorMOG2(history=60,
detectShadows=True)
elif self.c.bgsub.mod == 'KNN':
backSub = cv.createBackgroundSubtractorKNN()
fgMask = None
for i, image in enumerate(self.plant_groups[key]):
fgMask = backSub.apply(image)
self.plant_groups[key][i] = fgMask
def sendOperationToAllPeers(self):
constant = constants()
while 1:
if self.set_of_operation == []:
time.sleep(1)
else:
peers = self.peers
operation = self.set_of_operation
self.set_of_operation = []
print "===================SENDING OPERATIONS TO OTHER PEERS===================== "
for op in operation:
for peer in peers:
print "sending to peer", peer
self.connect_peer(peer[0],peer[1])
send_packet = packet()
send_packet.packet_type = constant.OperationTransformation
send_packet.data = "(" + str(op[0]) + "," + str(op[1]) + "," + str(op[2]) + ")"
self.__send(send_packet)
def calcConc(m, V, MM=368):
"""
Calculate the molar concentration of a sample with mass m dissolved in
volume V
========== ===============================================================
Input Meaning
---------- ---------------------------------------------------------------
m Mass of the solute [g]
V Volume of the solution [L]
MM Molar mass of the solute [g/mole]
Default set to 368 g/mole for Oregon Green
========== ===============================================================
========== ===============================================================
Output Meaning
---------- ---------------------------------------------------------------
c Concentration of the solution [mol/L]
========== ===============================================================
"""
Avogadro = constants('avogadro')
# grams to moles of solute
moles = m / MM
# concentration [mole/L]
c = moles / V
# concentration [particles/L]
c2 = c * Avogadro
# concentration [particles/fL]
c3 = c2 / 1e15
# print results
print('Concentration: {:.2e}'.format(c) + ' M = {:.2e}'.format(c2) + ' particles/L = {:.2e}'.format(c3) + ' particles/fL')
return c
def StokesEinstein(D, T=293, visc=1e-3):
"""
Calculate the diameter of particles based on the Stokes-Einstein equation
========== ===============================================================
Input Meaning
---------- ---------------------------------------------------------------
D Diffusion coefficient of the particles [in µm^2/s]
T Temperature of the suspension [in K]
visc Viscosity of the solvent [in Pa.s]
========== ===============================================================
========== ===============================================================
Output Meaning
---------- ---------------------------------------------------------------
d Diameter of the particles [in m]
========== ===============================================================
"""
kb = constants('boltzmann')
r = kb * T / 6 / np.pi / visc / D
d = 2 * r
return d
def theta(*args):
"""
theta(*args)
Computes potential temperature.
Allows for either T,p or T,p,wv as inputs.
Parameters
- - - - - -
T : float
Temperature (K).
p : float
Pressure (Pa).
Returns
- - - -
thetaOut : float
Potential temperature (K).
Other Parameters
- - - - - - - - -
wv : float, optional
Vapour mixing ratio (kg,kg). Can be appended as an argument
in order to increase precision of returned 'theta' value.
Raises
- - - -
NameError
If an incorrect number of arguments is provided.
References
- - - - - -
Emanuel p. 111 4.2.11
Examples
- - - - -
>>> theta(300., 8.e4) # Only 'T' and 'p' are input.
319.72798180767984
>>> theta(300., 8.e4, 0.001) # 'T', 'p', and 'wv' all input.
319.72309475657323
"""
c = constants()
if len(args) == 2:
wv = 0
elif len(args) == 3:
wv = args[2]
else:
raise NameError('need either T,p or T,p,wv')
T = args[0]
p = args[1]
power = c.Rd / c.cpd * (1. - 0.24 * wv)
thetaOut = T * (c.p0 / p)**power
return thetaOut
def wsat(Temp, press):
"""
wsat(Temp, press)
Calculates the saturation vapor mixing ratio of an air parcel.
Parameters
- - - - - -
Temp : float or array_like
Temperature in Kelvin.
press : float or array_like
Pressure in Pa.
Returns
- - - -
theWs : float or array_like
Saturation water vapor mixing ratio in (kg/kg).
Raises
- - - -
IOError
If both 'Temp' and 'press' are array_like.
Examples
- - - - -
>>> wsat(300, 8e4)
0.028751159650442507
>>> wsat([300,310], 8e4)
[0.028751159650442507, 0.052579529573838296]
>>> wsat(300, [8e4, 7e4])
[0.028751159650442507, 0.033076887758679716]
>>> wsat([300, 310], [8e4, 7e4])
Traceback (most recent call last):
...
IOError: Can't have two vector inputs.
"""
c = constants()
es = esat(Temp)
# We need to test for all possible cases of (Temp,press)
# combinations (ie. (vector,vector), (vector,scalar),
# (scalar,vector), or (scalar,scalar).
try:
len(es)
except:
esIsVect = False
else:
esIsVect = True
try:
len(press)
except:
pressIsVect = False
else:
pressIsVect = True
if esIsVect and pressIsVect:
raise IOError, "Can't have two vector inputs."
elif esIsVect:
theWs = c.eps * es / (press - es)
#theWs = [(c.eps * i/ (press - i)) for i in es]
# Limit ws values so rootfinder doesn't blow up.
#theWs = list(replaceelem(theWs,0,0.060))
elif pressIsVect:
theWs = c.eps * es / (press - es)
#theWs = [(c.eps * es/ (i - es)) for i in press]
# Limit ws values so rootfinder doesn't blow up.
#theWs = list(replaceelem(theWs,0,0.060))
else: # Neither 'es' nor 'press' in a vector.
theWs = (c.eps * es / (press - es))
# Limit ws value so rootfinder doesn't blow up.
if theWs > 0.060: theWs = 0.060
elif theWs < 0: theWs = 0
# Set minimum and maximum acceptable values for theWs.
try:
len(theWs)
except:
if theWs > 0.060: theWs = 0.060
elif theWs < 0: theWs = 0
else:
theWs[theWs < 0] = 0
theWs[theWs > 0.060] = 0.060
# theWs = list(replaceelem(theWs, 0, 0.060))
return theWs
def loop(self,my_host_name,my_port_name):
constant = constants()
print my_host_name,my_port_name
while self.connected:
try:
send_packet = packet()
send_packet.packet_type = constant.JOIN
send_packet.my_host_name = my_host_name
send_packet.my_port_name = my_port_name
print "details packet_type",send_packet.packet_type
send_packet.doc_name = self.file_name
self.__send(send_packet)
recv_packet = self.__receive()
self.socket.close();
self.bind_socket.bind((my_host_name,my_port_name))
print "creating server at ",my_host_name,my_port_name
self.bind_socket.listen(10)
thread.start_new_thread(self.sendOperationToAllPeers,())
thread.start_new_thread(self.mergeNewOperations,())
if recv_packet.packet_type == constant.NewFile: #new file created.
while 1:
peer_socket, peer_address = self.bind_socket.accept()
print "connection accepted ....."
try:
recv_peer_packet = self.__peer_receive(peer_socket)
# <packet_type 1000: my_host_name: my_port_name>
if recv_peer_packet.packet_type == constant.NewConnection:
handleNewConnection()
if recv_peer_packet.packet_type == constant.OperationTransformation:
self.set_of_operation_to_merge.append(recv_peer_packet.data)
if recv_peer_packet.packet_type == constant.getData:
print "some peer wants my data workspace.data"
send_packet = packet()
print "my workspace data before is ", self.workspace.get_data()
print "my workspace data is ", self.workspace.get_data()
send_packet.data = self.workspace.get_data()
self.__peer_send(peer_socket,send_packet)
peer_socket.close()
except:
peer_socket.close()
print "error 265"
else:
print "joining existing file list_of_ip: ",recv_packet.list_of_ip
for peer in recv_packet.list_of_ip:
print "perr details are: ", peer
self.peers.append(peer)
self.connect_peer(peer[0],peer[1])
send_packet = packet()
send_packet.packet_type = constant.NewConnection
send_packet.my_host_name = my_host_name
send_packet.my_port_name = my_port_name
self.__send(send_packet)
recv_peer_ack = self.__receive()
peer = recv_packet.list_of_ip[0]
self.connect_peer(peer[0],peer[1])
send_packet.packet_type = constant.getData
self.__send(send_packet)
recv_peer_data = self.__receive()
self.workspace.set_data(recv_peer_data.data)
print "recv_data ", recv_peer_data.data
self.__workspace_received()
print "recv_packet data:",recv_peer_data.data
while 1:
print "waiting to accept....."
peer_socket, peer_address = self.bind_socket.accept()
print "connection accepted ....."
try:
recv_peer_packet = self.__peer_receive(peer_socket)
# <packet_type 1000: my_host_name: my_port_name>
if recv_peer_packet.packet_type == constant.NewConnection:
handleNewConnection()
if recv_peer_packet.packet_type == constant.OperationTransformation:
self.set_of_operation_to_merge.append(recv_peer_packet.data)
if recv_peer_packet.packet_type == constant.getData:
print "some peer wants my data workspace.data"
send_packet = packet()
print "my workspace data before is ", self.workspace.get_data()
print "my workspace data is ", self.workspace.get_data()
send_packet.data = self.workspace.get_data()
self.__peer_send(peer_socket,send_packet)
peer_socket.close()
except:
peer_socket.close()
print "error 265"
except socket.error as e:
print "Socket error [%s, %s]" % (e.errno, e.strerror)
self.connected = False
self.__disconnected()
time.sleep(0.2)
def thetaep(Td, T, p):
"""
thetaep(Td, T, p)
Calculates the pseudo equivalent potential temperature of a
parcel.
Parameters
- - - - - -
Td : float
Dewpoint temperature (K).
T : float
Temperature (K).
p : float
Pressure (Pa).
Returns
- - - -
thetaepOut : float
Pseudo equivalent potential temperature (K).
Notes
- - -
Note that the pseudo equivalent potential temperature of an air
parcel is not a conserved variable.
References
- - - - - -
Emanuel 4.7.9 p. 132
Examples
- - - - -
>>> thetaep(280., 300., 8.e4) # Parcel is unsaturated.
344.99830738253371
>>> thetaep(300., 280., 8.e4) # Parcel is saturated.
321.5302927767795
"""
c = constants()
if Td < T:
#parcel is unsaturated
[Tlcl, plcl] = LCLfind(Td, T, p)
wv = wsat(Td, p)
else:
#parcel is saturated -- prohibit supersaturation with Td > T
Tlcl = T
wv = wsat(T, p)
# $$$ disp('inside theate')
# $$$ [Td,T,wv]
thetaval = theta(T, p, wv)
power = 0.2854 * (1 - 0.28 * wv)
thetaep = thetaval * np.exp(wv * (1 + 0.81 * wv) \
* (3376. / Tlcl - 2.54))
#
# peg this at 450 so rootfinder won't blow up
#
#thetaepOut = thetaep
#if(thetaepOut > 450.):
# thetaepOut = 450;
return thetaep
from threading import Thread
import time
import sys
import os
# add module folders to path
sys.path.append(os.getcwd()+'/Gmodule')
sys.path.append(os.getcwd()+'/MSHmodule')
import gExtract
import mshExtract
from MainFrame import MFrame
from constants import constants
#initializing vizulization constants for model and also variables space
cons=constants()
print('constants initialized')
## open stl file
print('exctracting geometry from file')
path='D:/tre.stl'
model,cmass=gExtract.eSTL(path) # model=[[normal,vecn1,vecn2,vecn3],... ](triangles); cmass = (x,y,z)
print('stl surface elements: ',len(model))
##assign geometry
cons.vect=model
cons.cmass_xyz=cmass
cons.Gwidgets.append('geometry')
print('model assigned to constants')
## open mesh file
print('exctracting geometry from file')
def LCLfind(Td, T, p):
"""
LCLfind(Td, T, p)
Finds the temperature and pressure at the lifting condensation
level (LCL) of an air parcel.
Parameters
- - - - - -
Td : float
Dewpoint temperature (K).
T : float
Temperature (K).
p : float
Pressure (Pa)
Returns
- - - -
Tlcl : float
Temperature at the LCL (K).
plcl : float
Pressure at the LCL (Pa).
Raises
- - - -
NameError
If the air is saturated at a given Td and T (ie. Td >= T)
Examples
- - - - -
>>> [Tlcl, plcl] = LCLfind(280., 300., 8.e4)
>>> print [Tlcl, plcl]
[275.76250387361404, 59518.928699453245]
>>> LCLfind(300., 280., 8.e4)
Traceback (most recent call last):
...
NameError: parcel is saturated at this pressure
References
- - - - - -
Emanuel 4.6.24 p. 130 and 4.6.22 p. 129
"""
c = constants()
hit = Td >= T
if hit is True:
raise NameError('parcel is saturated at this pressure')
e = esat(Td)
ehPa = e * 0.01
#Bolton's formula requires hPa.
# This is is an empircal fit from for LCL temp from Bolton, 1980 MWR.
Tlcl = (2840. / (3.5 * np.log(T) - np.log(ehPa) - 4.805)) + 55.
r = c.eps * e / (p - e)
#disp(sprintf('r=%0.5g',r'))
cp = c.cpd + r * c.cpv
logplcl = np.log(p) + cp / (c.Rd * (1 + r / c.eps)) * \
np.log(Tlcl / T)
plcl = np.exp(logplcl)
#disp(sprintf('plcl=%0.5g',plcl))
return Tlcl, plcl
def O18EVA_MEAN(tmax, TC, pCO2, pCO2cave, h, v, R18_hco_ini, R18_h2o_ini, R18v, HCOMIX, h2o_new,tt):
# Sourcecode to develope the evolution of the isotopic ratio of the oxygen
# compostion of the oxygen isotopes 16O and 18O as a function of
# temperature TC, supersaturation (pCO2), relative humidity (h) and wind
# velocity (v). %(08.12.2010/m)
eva = evaporation.evaporation(TC, h, v)
fracs = cmodel_frac.cmodel_frac(TC)
TK = 273.15 + TC
#Tau precipitation (s); t=d/a (according to Baker 98)
alpha_p = (1.188e-011 * TC**3 - 1.29e-011 * TC**2 + 7.875e-009 * TC + 4.844e-008)
#Tau buffering, after Dreybrodt and Scholz (2010)
T = 125715.87302 - 16243.30688*TC + 1005.61111*TC**2 - 32.71852*TC**3 + 0.43333*TC**4
#Concentrations and mol mass
outputcave = constants.constants(TC, pCO2cave) #Concentrations of the spezies in the solution, with respect to cave pCO2
HCOCAVE = outputcave[2][2]/math.sqrt(0.8) #HCO3- concentration, with respect to cave pCO2 (mol/l)
h2o_ini = h2o_new #Mol mass of the water, with respect to the volume of a single box (mol)
H20_ini = h2o_ini*18/1000
hco_ini = HCOMIX*H20_ini #Mol mass of the HCO3-(soil), with respect to the volume of a single box (mol)
hco_eq = HCOCAVE*H20_ini #Mol mass of the HCO3-(cave), with respect to the volume of a single box (mol)
#Fractionation facors for oxygen isotope
eps_m = fracs['a18_m'] - 1
avl = ((-7356/TK + 15.38)/1000 + 1)
abl = 1/(fracs['e18_hco_h2o'] + 1)
a = 1/1.008*1.003
f = 1/6
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
#Calculation of the 18R
r_hco18 = [R18_hco_ini]
r_h2o18 = [R18_h2o_ini]
if tmax > math.floor(h2o_ini/eva):
tmax = int(math.floor(h2o_ini/eva))
print 'DRIPINTERVALL IS TOO LONG, THE WATERLAYER EVAPORATES COMPLETLY FOR THE GIVEN d, run # %i' %(tt)
dt = 1
t=range(1,tmax+1)
HCO = [HCOMIX] #Konzentration von HCO3-
hco = [hco_ini] #Menge an HCO3-
H2O = [H20_ini]
h2o = [h2o_new]
delta_1 = [H2O[-1]/1000/0.001]
#"Restwassermenge" und daher konstant
for i in t:
delta_1.append(H2O[-1]/1000/0.001)
delta = (H2O[-1]/1000)/0.001
#Neue Wassermenge
h2o.append(h2o[-1] - eva*dt) #Water (mol)
d_h2o = -eva #Evaporationrate (mol/l)
H2O.append(h2o[-1]*18*1e-3) #Water (l)
HCO_EQ = HCOCAVE #Equilibriumconcentration
#Verdundstung
HCO_temp = (HCO[-1] - HCO_EQ) * math.exp(-dt/(delta/alpha_p)) + HCO_EQ #HCO3- concentration after timeintervall dt
hco.append(HCO_temp * H2O[-2]) #HCO3- mass (mol)
HCO.append(HCO_temp * (H2O[-2]/H2O[-1])) #HCO3- concentration after timeintervall dt and the evaporation of water
r_hco18.append(r_hco18[-1] + ((eps_m*(hco[-1]-hco[-2])/hco[-1]-1/T) * r_hco18[-1] + abl/T*r_h2o18[-1]) * dt)
r_h2o18.append(r_h2o18[-1] + ((hco[-1]/h2o[-1]/T - f/abl/h2o[-1]*(hco[-1]-hco[-2]) * r_hco18[-1] + (d_h2o/h2o[-1]*(a*avl/(1-h)-1) - hco[-1]/h2o[-1]*abl/T) * r_h2o18[-1] - a*h/(1-h)*R18v/h2o[-1]*d_h2o)) * dt)
if tmax > math.floor(h2o_ini/eva):
r_hco18 = NaN
r_h2o18 = NaN
hco = NaN
h2o = NaN
delta_1 = NaN
return [r_hco18, r_h2o18, hco, h2o, delta_1]
def LCLfind(Td, T, p):
"""
LCLfind(Td, T, p)
Finds the temperature and pressure at the lifting condensation
level (LCL) of an air parcel.
Parameters
- - - - - -
Td : float
Dewpoint temperature (K).
T : float
Temperature (K).
p : float
Pressure (Pa)
Returns
- - - -
Tlcl : float
Temperature at the LCL (K).
plcl : float
Pressure at the LCL (Pa).
Raises
- - - -
NameError
If the air is saturated at a given Td and T (ie. Td >= T)
Examples
- - - - -
>>> [Tlcl, plcl] = LCLfind(280., 300., 8.e4)
>>> print [Tlcl, plcl]
[275.76250387361404, 59518.928699453245]
>>> LCLfind(300., 280., 8.e4)
Traceback (most recent call last):
...
NameError: parcel is saturated at this pressure
References
- - - - - -
Emanuel 4.6.24 p. 130 and 4.6.22 p. 129
"""
c = constants();
hit = Td >= T;
if hit is True:
raise NameError('parcel is saturated at this pressure');
e = esat(Td);
ehPa = e * 0.01; #Bolton's formula requires hPa.
# This is is an empircal fit from for LCL temp from Bolton, 1980 MWR.
Tlcl = (2840. / (3.5 * np.log(T) - np.log(ehPa) - 4.805)) + 55.;
r = c.eps * e / (p - e);
#disp(sprintf('r=%0.5g',r'))
cp = c.cpd + r * c.cpv;
logplcl = np.log(p) + cp / (c.Rd * (1 + r / c.eps)) * \
np.log(Tlcl / T);
plcl = np.exp(logplcl);
#disp(sprintf('plcl=%0.5g',plcl))
return Tlcl, plcl
import warpGen as wg
#constants scripts
#these create libraries where integer constants are made
#based on the file names
#story struct pre-processing
d.dialog("story_merge", "jass", ["msg"])
#quest description adding
qm.questMsg("quests_merge", "quest_struct", ["msg"])
#creates library for monster constants--however, must be integer to rawcode!
cns.constants("monsters", "tables/monsters_constants.j", "lua", ["header", "insert"], "M")
#creates library for npc names--for enumeration, string to string
#cns.constantsStr("npcs", "tables/npc_names_constants.j", "lua", ["header", "insert"])
#creates library for warp constants--integer to integer
#cns.constants("warps", "tables/warps_constants.j", "lua", ["header", "insert"])
#cns.constants("warps", "tables/warp_id_constants.j", "lua", ["header", "insert"], "w", "_ID", "Ids")
#creates library for quest constants--integer to integer
cns.constants("quests_merge", "tables/quests_constants.j", "quest_struct", ["header", "insert", "msg"])
#creates library for reward constants--integer to integer
cns.constants("reward_merge", "tables/reward_constants.j", "reward_struct", ["header", "insert"], "", "_REWARD")
#creates library for story constants--integer to integer
def constants(self, constants_arr, jd=0.0):
"""
Syntax: constants(constants_arr, [jd= ])
Purpose: Parse aircraft constants XML files and return desired aircraft
constants in a dictionary.
Input: 'constants_arr' - an array of desired constants as strings
'jd' - optional argument sets Julian Date for time-dependent constants
Output: a dictionary containing the desired constants that are correct for
the given Julian Date.
Notes: If no Julian Date is given, the class attribute 'jul_date' is used.
"""
# Import the constants method.
from constants import constants
# Parse the default constants XML file for the desired constants.
constants_dict = constants(constants_arr)
# Get calibration data based on the ADPAA class attribute 'SNAME'.
if 'Convair 580 (C-FNRC)' in self.SNAME:
# Create a dictionary 'N_consts' with the desired constants from the
# N555DS XML constants file using the Julian Date passed into
# the method.
if jd > 0.0:
N_consts = constants(constants_arr, \
fname='C-FNRC_constants.xml', jul_date=jd)
# Create a dictionary 'N_consts' with the desired constants from the
# N555DS XML constants file using the Julian Date calculated from
# the filename.
elif self.jul_date > 0.0:
N_consts = constants(constants_arr, \
fname='C-FNRC_constants.xml', \
jul_date=self.jul_date)
else:
print("WARNING (adpaa.py): Julian Date not set--returning only desired"+\
" default constants. Use the 'jd' argument to manually"+\
" set the Julain Date.")
return constants_dict
# Update the 'constant_dict' dictionary with the desired constants
# only if a value exists for that item in the 'N_const' dictionary
# as to not override the values already in 'const_dict'.
for key,val in N_consts.items():
if val != None:
constants_dict.update({key:val})
if 'UND Citation II' in self.SNAME:
# Create a dictionary 'N_consts' with the desired constants from the
# N555DS XML constants file using the Julian Date passed into
# the method.
if jd > 0.0:
N_consts = constants(constants_arr, \
fname='N555DS_constants.xml', jul_date=jd)
# Create a dictionary 'N_consts' with the desired constants from the
# N555DS XML constants file using the Julian Date calculated from
# the filename.
elif self.jul_date > 0.0:
N_consts = constants(constants_arr, \
fname='N555DS_constants.xml', \
jul_date=self.jul_date)
else:
print("WARNING (adpaa.py): Julian Date not set--returning only desired"+\
" default constants. Use the 'jd' argument to manually"+\
" set the Julain Date.")
return constants_dict
# Update the 'constant_dict' dictionary with the desired constants
# only if a value exists for that item in the 'N_const' dictionary
# as to not override the values already in 'const_dict'.
for key,val in N_consts.items():
if val != None:
constants_dict.update({key:val})
else:
print("WARNING (adpaa.py): invalid ADPAA class attribute 'SNAME'--only "+\
"desired default constants will be returned.")
# Remove constants that have not been found in any constants file.
for k in constants_dict.keys():
if constants_dict[k] == None:
print("WARNING (adpaa.py): constant '"+k+"' does not exist and will not"+\
" be returned.")
del constants_dict[k]
return constants_dict
def convecSkew(figNum):
"""
Usage: convecSkew(figNum)
Input: figNum = integer
Takes any integer, creates figure(figNum), and plots a
skewT logp thermodiagram.
Output: skew=30.
"""
c = constants();
plt.figure(figNum);
plt.clf();
yplot = range(1000,190,-10)
xplot = range(-300,-139)
pvals = np.size(yplot)
tvals = np.size(xplot)
temp = np.zeros([pvals, tvals]);
theTheta = np.zeros([pvals, tvals]);
ws = np.zeros([pvals, tvals]);
theThetae = np.zeros([pvals, tvals]);
skew = 30; #skewness factor (deg C)
# lay down a reference grid that labels xplot,yplot points
# in the new (skewT-lnP) coordinate system .
# Each value of the temp matrix holds the actual (data)
# temperature label (in deg C) of the xplot, yplot coordinate.
# pairs. The transformation is given by W&H 3.56, p. 78. Note
# that there is a sign difference, because rather than
# taking y= -log(P) like W&H, I take y= +log(P) and
# then reverse the y axis
for i in yplot:
for j in xplot:
# Note that we don't have to transform the y
# coordinate, as it is still pressure.
iInd = yplot.index(i)
jInd = xplot.index(j)
temp[iInd, jInd] = convertSkewToTemp(j, i, skew);
Tk = c.Tc + temp[iInd, jInd];
pressPa = i * 100.;
theTheta[iInd, jInd] = theta(Tk, pressPa);
ws[iInd, jInd] = wsat(Tk, pressPa);
theThetae[iInd, jInd] = thetaes(Tk, pressPa);
#
# Contour the temperature matrix.
#
# First, make sure that all plotted lines are solid.
mpl.rcParams['contour.negative_linestyle'] = 'solid'
tempLabels = range(-40, 50, 10);
output1 = plt.contour(xplot, yplot, temp, tempLabels, \
colors='k')
#
# Customize the plot
#
plt.setp(plt.gca(), yscale='log')
locs = np.array(range(100, 1100, 100))
labels = locs
plt.yticks(locs, labels) # Conventionally labels semilog graph.
plt.setp(plt.gca(), ybound=(200, 1000))
plt.setp(plt.getp(plt.gca(), 'xticklabels'), fontweight='bold')
plt.setp(plt.getp(plt.gca(),'yticklabels'), fontweight='bold')
plt.grid(True)
plt.setp(plt.gca().get_xgridlines(), visible=False)
plt.hold(True);
thetaLabels = range(200, 380, 10);
output2 = plt.contour(xplot, yplot, theTheta, thetaLabels, \
colors='b');
wsLabels = range(6, 24, 2);
output3 = plt.contour(xplot, yplot, (ws * 1.e3), wsLabels, \
colors='g');
thetaeLabels = range(250, 380, 10);
output4 = plt.contour(xplot, yplot, theThetae, thetaeLabels, \
colors='r');
# Transform the temperature,dewpoint from data coords to
# plotting coords.
plt.title('skew T - lnp chart');
plt.ylabel('pressure (hPa)');
plt.xlabel('temperature (deg C)');
#
# Crop image to a more usable size
#
TempTickLabels = range(5, 35, 5);
TempTickCoords = TempTickLabels;
skewTickCoords = convertTempToSkew(TempTickCoords, 1.e3, skew);
plt.xticks(skewTickCoords, TempTickLabels)
skewLimits = convertTempToSkew([5, 30], 1.e3, skew);
plt.axis([skewLimits[0], skewLimits[1], 600, 1.e3]);
#
# Create line labels
#
fntsz = 9 # Handle for 'fontsize' of the line label.
ovrlp = 1 # Handle for 'inline'. Any integer other than 0
# creates a white space around the label.
plt.clabel(output1, inline=ovrlp, fmt='%1d', fontsize=fntsz);
plt.clabel(output2, inline=ovrlp, fmt='%1d', fontsize=fntsz);
plt.clabel(output3, inline=ovrlp, fmt='%1d', fontsize=fntsz);
plt.clabel(output4, inline=ovrlp, fmt='%1d', fontsize=fntsz);
#
# Flip the y axis
#
plt.setp(plt.gca(), ylim=plt.gca().get_ylim()[::-1])
return skew
def O18EVA(tmax, TC, pCO2, pCO2cave, h, v, R18_hco_ini, R18_h2o_ini, R18v,
HCOMIX, h2o_new, tt):
# Sourcecode to develope the evolution of the isotopic ratio of the oxygen
# compostion of the oxygen isotopes 16O and 18O as a function of
# temperature TC, supersaturation (pCO2), relative humidity (h) and wind
# velocity (v). %(08.12.2010/m)
eva = evaporation.evaporation(TC, h, v)
fracs = cmodel_frac.cmodel_frac(TC)
TK = 273.15 + TC
#Tau precipitation (s); t=d/a (according to Baker 98)
alpha_p = (1.188e-011 * TC**3 - 1.29e-011 * TC**2 + 7.875e-009 * TC +
4.844e-008)
#Tau buffering, after Dreybrodt and Scholz (2010)
T = 125715.87302 - 16243.30688 * TC + 1005.61111 * TC**2 - 32.71852 * TC**3 + 0.43333 * TC**4
#Concentrations and mol mass
outputcave = constants.constants(
TC, pCO2cave
) #Concentrations of the spezies in the solution, with respect to cave pCO2
HCOCAVE = outputcave[2][2] / math.sqrt(
0.8) #HCO3- concentration, with respect to cave pCO2 (mol/l)
h2o_ini = h2o_new #Mol mass of the water, with respect to the volume of a single box (mol)
H20_ini = h2o_ini * 18 / 1000.
hco_ini = HCOMIX * H20_ini #Mol mass of the HCO3-(soil), with respect to the volume of a single box (mol)
#hco_eq = HCOCAVE*H20_ini #Mol mass of the HCO3-(cave), with respect to the volume of a single box (mol)
#Fractionation facors for oxygen isotope
eps_m = fracs['a18_m'] - 1
avl = ((-7356. / TK + 15.38) / 1000. + 1)
abl = 1 / (fracs['e18_hco_h2o'] + 1)
a = 1 / 1.008 * 1.003
f = 1 / 6
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
#Calculation of the 18R
r_hco18 = [R18_hco_ini]
r_h2o18 = [R18_h2o_ini]
if tmax > math.floor(h2o_ini / eva):
tmax = int(math.floor(h2o_ini / eva))
print 'DRIPINTERVALL IS TOO LONG, THE WATERLAYER EVAPORATES COMPLETLY FOR THE GIVEN d, run # %i' % (
tt)
dt = 1
t = range(1, tmax + 1)
HCO = [HCOMIX] #Konzentration von HCO3-
hco = [hco_ini] #Menge an HCO3-
H2O = [H20_ini]
h2o = [h2o_new]
#"Restwassermenge" und daher konstant
HCO_EQ = HCOCAVE #Equilibriumconcentration
for i in t:
delta = (H2O[-1] / 1000.) / 0.001
#Neue Wassermenge
h2o.append(h2o[-1] - eva * dt) #Water (mol)
d_h2o = -eva #Evaporationrate (mol/l)
H2O.append(h2o[-1] * 18 * 1e-3) #Water (l)
#Verdundstung
HCO_temp = (HCO[-1] - HCO_EQ) * math.exp(
-dt /
(delta /
alpha_p)) + HCO_EQ #HCO3- concentration after timeintervall dt
hco.append(HCO_temp * H2O[-2]) #HCO3- mass (mol)
HCO.append(
HCO_temp * (H2O[-2] / H2O[-1])
) #HCO3- concentration after timeintervall dt and the evaporation of water
r_hco18.append(r_hco18[-1] +
((eps_m *
(hco[-1] - hco[-2]) / hco[-1] - 1 / T) * r_hco18[-1] +
abl / T * r_h2o18[-1]) * dt)
r_h2o18.append(r_h2o18[-1] + (
(hco[-1] / h2o[-1] / T - f / abl / h2o[-1] *
(hco[-1] - hco[-2]) * r_hco18[-1] +
(d_h2o / h2o[-1] *
(a * avl /
(1 - h) - 1) - hco[-1] / h2o[-1] * abl / T) * r_h2o18[-1] -
a * h / (1 - h) * R18v / h2o[-1] * d_h2o) * dt))
return [r_hco18[-1], r_h2o18[-1], HCO[-1], hco[-1], H2O[-1], h2o[-1]]
import datetime as dt
import os
import constants
c = constants.constants()
import globals
g = globals.ioGlobals()
# Logging system for ioController and testController
class log():
# Very simple logging system. Just formats the supplied message with a timestamp
# and a level (which defaults to "debug"). Outputs the message to a TCP data client
# if it's connected
def __init__(self):
# Open a file on the local drive to which we're going to send all the logging
# messages. Note that errors here are printed (rather than logged) because
# the log file is not set up until we exit so printing is the least-worst
# thing to do
# First we need to create a log directory if there's not one already
try:
os.mkdir(c.logDirectory)
print('Created log directory: ' + c.logDirectory)
except FileExistsError:
# We got an error because the logs directory already exists. Now we need
# to delete all the old log files. Work out the cut off for deleting them
def thetaep(Td, T, p):
"""
thetaep(Td, T, p)
Calculates the pseudo equivalent potential temperature of a
parcel.
Parameters
- - - - - -
Td : float
Dewpoint temperature (K).
T : float
Temperature (K).
p : float
Pressure (Pa).
Returns
- - - -
thetaepOut : float
Pseudo equivalent potential temperature (K).
Notes
- - -
Note that the pseudo equivalent potential temperature of an air
parcel is not a conserved variable.
References
- - - - - -
Emanuel 4.7.9 p. 132
Examples
- - - - -
>>> thetaep(280., 300., 8.e4) # Parcel is unsaturated.
344.99830738253371
>>> thetaep(300., 280., 8.e4) # Parcel is saturated.
321.5302927767795
"""
c = constants();
if Td < T:
#parcel is unsaturated
[Tlcl, plcl] = LCLfind(Td, T, p);
wv = wsat(Td, p);
else:
#parcel is saturated -- prohibit supersaturation with Td > T
Tlcl = T;
wv = wsat(T, p);
# $$$ disp('inside theate')
# $$$ [Td,T,wv]
thetaval = theta(T, p, wv);
power = 0.2854 * (1 - 0.28 * wv);
thetaep = thetaval * np.exp(wv * (1 + 0.81 * wv) \
* (3376. / Tlcl - 2.54));
#
# peg this at 450 so rootfinder won't blow up
#
if(thetaepOut > 450.):
thetaepOut = 450;
return thetaepOut
def isotope_calcite(d, TC, pCO2, pCO2cave, h, V, phi, d18Oini,tt):
#boundary value constant parameters (equiv of BOUNDARY)
R2smow = 0.00015575
R18smow = 0.0020052
R18vpdb = 0.0020672
eva=evaporation.evaporation(TC, h, V) #Evaporationrate (mol/l)
fracs=cmodel_frac.cmodel_frac(TC) #Fractionation factors
TK = 273.15 + TC #Absolute temperature (K)
#Tau precipitation (s); t=d/a (according to Baker 98)
Z = 0.0001/(1.188e-011 * TC**3 - 1.29e-011 * TC**2 + 7.875e-009 * TC + 4.844e-008)
alpha = (1.188e-011 * TC**3 - 1.29e-011 * TC**2 + 7.875e-009 * TC + 4.844e-008)
#Tau buffering, after Dreybrodt and Scholz (2010)
T = 125715.87302 - 16243.30688*TC + 1005.61111*TC**2 - 32.71852*TC**3 + 0.43333*TC**4
#Concentrations and mol mass
#Concentrations of the spezies in the solution, with respect to soil pCO2
outputsoil = constants.constants(TC, pCO2)
#Concentrations of the spezies in the solution, with respect to cave pCO2
outputcave = constants.constants(TC, pCO2cave)
HCOSOIL = outputsoil[2][2] #HCO3- concentration, with respect to soil pCO2 (mol/l)
HCOCAVE = outputcave[2][2]/math.sqrt(0.8) #HCO3- concentration, with respect to cave pCO2 (mol/l)
#Mol mass of the water, with respect to the volume of a single box (mol)
h2o_ini = 0.1/18
#Mol mass of the HCO3-(soil), with respect to the volume of a single box (mol)
hco_ini = HCOSOIL*1e-4
#Mol mass of the HCO3-(cave), with respect to the volume of a single box (mol)
hco_eq = HCOCAVE*1e-4
#Fractionation facors for oxygen isotope
eps_m = fracs['a18_m'] - 1
avl = (-7356./TK + 15.38)/1000. + 1
abl = 1/(fracs['e18_hco_h2o'] + 1)
a = 1/1.008
f = 1/6.
Rdrop18_w = ( (d18Oini / 1000.) + 1) * R18smow
Rdrop18_b = Rdrop18_w / (fracs['e18_hco_h2o'] + 1)
Rv18 = avl * Rdrop18_w
# Definition of the input-parameter of the program "O18EVA" at the time
# t=0s, e.g. at the beginning of the mix process
hco_mix = hco_ini
h2o_mix = h2o_ini
HCOMIX = hco_mix / 1e-4
r_hco18_mix = Rdrop18_b
r_h2o18_mix = Rdrop18_w
number = 0
r18res = 0
r18mix = 1
while r18mix != r18res:
number += 1
r18_hco_res = r_hco18_mix
temp = O18EVA.O18EVA(d, TC, pCO2, pCO2cave, h, V, r_hco18_mix, r_h2o18_mix, Rv18, HCOMIX,
h2o_mix,tt)
hco_out = temp[3] #mol mass of hco
h2o_out = temp[5] #mol mass of h2o
r_hco18_out = temp[0] #oxygen isotopic ratio of hco
r_h2o18_out = temp[1] #oxygen isotopic ratio of h2o
#%%% 1) simple mixprocess
hco_mix = phi*hco_ini + (1-phi)*hco_out #mixing of hco
h2o_mix = phi*h2o_ini + (1-phi)*h2o_out #mixing of h2o
phi_r_b = 1 / (1 + (1-phi) / phi*hco_out*hco_ini) #isotopic mixing parameter of hco
phi_r_w = 1 / (1 + (1-phi) / phi*h2o_out/h2o_ini) #isotopic mixing parameter of h2o
r_hco18_mix = phi_r_b*Rdrop18_b + (1-phi_r_b)*r_hco18_out #new oxygen isotopic ratio of hco
r_h2o18_mix = phi_r_w*Rdrop18_w + (1-phi_r_w)*r_h2o18_out #new oxygen isotopic ratio of h2o
H2O_mix = h2o_mix*18/1000. #mol -> l (mol*(g/mol)/(g/kg)*(l/kg)
HCOMIX = hco_mix / H2O_mix #new hco condentration
#end of the extended mixprocess
r18mix = round(r_hco18_mix*10**13)
r18res = round(r18_hco_res*10**13)
temp = O18EVA_MEAN.O18EVA_MEAN(d, TC, pCO2, pCO2cave, h, V, r_hco18_mix, r_h2o18_mix, Rv18,
HCOMIX, h2o_mix,tt)
r_hco18 = np.array(temp[0])
hco = np.array(temp[2])
delta_1 = np.array(temp[4])
delta_0 = delta_1[0]
delta_end= delta_1[-1]
r_h2o18 = np.array(temp[1])
h2o = np.array(temp[3])
tmp = np.isnan(r_hco18)
if tmp.all() != True:
r_hco18_mean = sum( (r_hco18[:-1] + np.diff(r_hco18,n=1)/2.) * (-np.diff(hco,n=1) / (hco[0]-hco[-1]) ))
d18Ocalcite = (r_hco18_mean*(fracs['e18_hco_caco'] + 1)/R18vpdb - 1)*1000
r_h2o18_mean = sum( (r_h2o18[:-1] + np.diff(r_h2o18,n=1)/2.) * (-np.diff(h2o,n=1) / (h2o[0]-h2o[-1]) ))
d18Owater = (r_h2o18_mean/R18smow - 1)*1000
d18Ovapor = (Rv18/R18smow - 1)*1000
return d18Ocalcite
else:
return [NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN]
from threading import Thread
import time
import sys
import os
# add module folders to path
sys.path.append(os.getcwd()+'/Gmodule')
sys.path.append(os.getcwd()+'/MSHmodule')
import gExtract
import mshExtract
from MainFrame import MFrame
from constants import constants
#initializing vizulization constants for model and also variables space
cons=constants()
print('constants initialized')
## open stl file
print('exctracting geometry from file')
path='D:/tre.stl'
model,cmass=gExtract.eSTL(path) # model=[[normal,vecn1,vecn2,vecn3],... ](triangles); cmass = (x,y,z)
print('stl surface elements: ',len(model))
##assign geometry
cons.vect=model
cons.cmass_xyz=cmass
cons.Gwidgets.append('geometry')
print('model assigned to constants')
## open mesh file
#print('exctracting geometry from file')
#path='D:/el_ex.txt'
from constants import constants
from node import node, getiter
from knowndict import knowndict
n = node(constants())
with open('qfiles/testcode.qq') as f:
gen = getiter(n.consts, f.read())
known = knowndict(n.consts)
print('----')
print(n.evalnode(gen, known), known)
print('----\n')
if __debug__ and '$dnd' not in known:
print(known, end = '\n--\n')
print(repr(known))
def wsat(Temp, press):
"""
wsat(Temp, press)
Calculates the saturation vapor mixing ratio of an air parcel.
Parameters
- - - - - -
Temp : float or array_like
Temperature in Kelvin.
press : float or array_like
Pressure in Pa.
Returns
- - - -
theWs : float or array_like
Saturation water vapor mixing ratio in (kg/kg).
Raises
- - - -
IOError
If both 'Temp' and 'press' are array_like.
Examples
- - - - -
>>> wsat(300, 8e4)
0.028751159650442507
>>> wsat([300,310], 8e4)
[0.028751159650442507, 0.052579529573838296]
>>> wsat(300, [8e4, 7e4])
[0.028751159650442507, 0.033076887758679716]
>>> wsat([300, 310], [8e4, 7e4])
Traceback (most recent call last):
...
IOError: Can't have two vector inputs.
"""
c = constants();
es = esat(Temp);
# We need to test for all possible cases of (Temp,press)
# combinations (ie. (vector,vector), (vector,scalar),
# (scalar,vector), or (scalar,scalar).
try:
len(es)
except:
esIsVect = False
else:
esIsVect = True
try:
len(press)
except:
pressIsVect = False
else:
pressIsVect = True
if esIsVect and pressIsVect:
raise IOError, "Can't have two vector inputs."
elif esIsVect:
theWs = c.eps*es/(press - es)
#theWs = [(c.eps * i/ (press - i)) for i in es]
# Limit ws values so rootfinder doesn't blow up.
#theWs = list(replaceelem(theWs,0,0.060))
elif pressIsVect:
theWs = c.eps*es/(press - es)
#theWs = [(c.eps * es/ (i - es)) for i in press]
# Limit ws values so rootfinder doesn't blow up.
#theWs = list(replaceelem(theWs,0,0.060))
else: # Neither 'es' nor 'press' in a vector.
theWs = (c.eps * es/ (press - es))
# Limit ws value so rootfinder doesn't blow up.
if theWs > 0.060: theWs = 0.060
elif theWs < 0: theWs = 0
# Set minimum and maximum acceptable values for theWs.
try:
len(theWs)
except:
if theWs > 0.060: theWs = 0.060
elif theWs < 0: theWs = 0
else:
theWs[theWs < 0] = 0
theWs[theWs > 0.060] = 0.060
# theWs = list(replaceelem(theWs, 0, 0.060))
return theWs
#import matplotlib as mpl
#mpl.use('Agg')
from pylab import *
import os, sys
import traceback
from constants import constants
(h, k, c, Tcmb) = constants()
# change log
# v0.4 Added capability in getAtmosphere to define a custom transmission file
class NETlib():
"""
class with all necesary libraries to compute bolometer NET
"""
def __init__(self, verbose=True):
"""
symlink from NETlib.py to the latest version NETlib_v0.X.py
"""
self.path = '/n/home01/dbarkats/work/20170801_S4_NET_forecast_python/'
self.amversion = 9.2
self.verbose = verbose
self.orig_stdout = sys.stdout
self.getVersion()
#if self.verbose==False:
# self.f = open('outputs.txt','w')
# sys.stdout = self.f
"""
Author:
Benjamin Hills
University of Washington
Earth and Space Sciences
April 28, 2020
"""
# Import necessary libraries
import numpy as np
from scipy import sparse
from scipy.integrate import cumtrapz
from scipy.interpolate import interp1d
from supporting_functions import analytical_model, viscosity, Robin_T
from constants import constants
const = constants()
class numerical_model():
"""
1-D finite-difference model for ice temperature based on
Weertman (1968)
Assumptions:
1) Initialize to 1-D Analytical temperature profile from either Robin (1955) or Rezvanbehbahani et al. (2019)
then spin up the numbercal model to steady state until all points are changing by less then 'tol' every time step.
2) Horizontal velocity
Shear stress for lamellar flow then optimize the viscosity to match the surface velocity.
3) Vertical velocity
Two options: first is to use an exponential form as in Rezvanbehbahani et al. (2019)
second is to use the shape factor, p, as from Lliboutry
# from netCDF4 import Dataset
# import matplotlib.pyplot as plt
# import glob
# import numpy as np
# import matplotlib
# import matplotlib.cm as cm
# import SAM_init_plot.block_fns
# import SAM_init_plot.misc_fns
# from SAM_init_plot.misc_fns import raddist, radprof
# from SAM_init_plot.block_fns import blockave2D, blockxysort2D, xysort
# from thermolib.constants import constants
#plt.rc('text', usetex=True)
c = constants()
plt.close('all')
def expfunc(x, a, b, c):
return a*np.exp(-b*x) + c
matplotlib.rcParams.update({'font.size': 28})
matplotlib.rcParams.update({'figure.figsize': (18, 12)})
matplotlib.rcParams.update({'lines.linewidth': 3})
matplotlib.rcParams.update({'legend.fontsize': 24})
#matplotlib.rcParams.update({'mathtext.fontset': 'custom'})
matplotlib.rcParams.update({'mathtext.fontset': 'cm'})
#matplotlib.rcParams.update({'font.family': 'serif'})
plt.style.use('seaborn-white')
def theta(*args):
"""
theta(*args)
Computes potential temperature.
Allows for either T,p or T,p,wv as inputs.
Parameters
- - - - - -
T : float
Temperature (K).
p : float
Pressure (Pa).
Returns
- - - -
thetaOut : float
Potential temperature (K).
Other Parameters
- - - - - - - - -
wv : float, optional
Vapour mixing ratio (kg,kg). Can be appended as an argument
in order to increase precision of returned 'theta' value.
Raises
- - - -
NameError
If an incorrect number of arguments is provided.
References
- - - - - -
Emanuel p. 111 4.2.11
Examples
- - - - -
>>> theta(300., 8.e4) # Only 'T' and 'p' are input.
319.72798180767984
>>> theta(300., 8.e4, 0.001) # 'T', 'p', and 'wv' all input.
319.72309475657323
"""
c = constants();
if len(args) == 2:
wv = 0;
elif len(args) == 3:
wv = args[2];
else:
raise NameError('need either T,p or T,p,wv');
T = args[0];
p = args[1];
power = c.Rd / c.cpd * (1. - 0.24 * wv);
thetaOut = T * (c.p0 / p) ** power;
return thetaOut
