import numpy as np
import scipy as sc
import scipy.stats as stats
import pySALEPlot as psp
import matplotlib.pyplot as plt
field1 = 'Pre'
field2 = 'V_y'
field3 = 'Den'
field4 = 'TPS'
field5 = 'Tmp'
dirname = 'shockfronts'
model = psp.opendatfile('./jdata.dat') # Open datafile
psp.mkdir_p('./shockfronts')
model.setScale('mm')
tstart = 1 # Start at t>0 such that there IS a shock present
tfin = 250
tintv = 1
YC = model.yc
XC = model.xc
TME = np.zeros((int((tfin - tstart + 1) / tintv))) # time
YSF = np.zeros((int((tfin - tstart + 1) / tintv))) # Shock Front Y position
PBD = np.zeros((int((tfin - tstart + 1) /
tintv))) # Shock in Particle Bed array. 1 is yes 0 is no
QUP = np.zeros((int(
(tfin - tstart + 1) / tintv))) # Quasi steady state Particle velocity
Us = np.zeros((int((tfin - tstart + 1) / (5 * tintv)) + 1))
Up = np.zeros(
(int((tfin - tstart + 1) / (5 * tintv)) +
p_list = list(eval(file2.readline().replace('\n','')))
T_list = list(eval(file2.readline().replace('\n','')))
m_list = list(eval(file2.readline().replace('\n','')))
t_list = list(eval(file2.readline().replace('\n','')))
r_list = list(eval(file2.readline().replace('\n','')))
used = list(eval(file2.readline().replace('\n','')))
jumps, start_time, end_time, save_step, R, grid_spacing, g, a, v_0, layers, datafile = eval(file2.readline().replace('\n',''))
print('DONE\n')
# Make an output directory
dirname='Origin_Landing'
psp.mkdir_p(dirname)
print('Extracting Materials...')
# Open the datafile
model=psp.opendatfile(datafile)
model.setScale('km')
step = model.readStep('TrP', 0)
yy = np.append(np.zeros(0), step.ymark)
col = []
for i in range(len(yy)): # find materials based on starting height
if yy[i] > layers[0]:
co = 'black'
elif yy[i] > layers[1]:
co = 'darkgrey'
elif yy[i] > layers[2]:
co = 'y'
else:
co = 'r'
col.append(co)
print('DONE\n')
iplt.morphology(path1, paths, norm, normpath, timei, showtransient, showhline,
lbl)
#path1 = '/uio/kant/geo-ceed-u1/nilscp/Desktop/stallo_work/benchmarkFI/CPPR/UAVG/CPPR10/IVANOVS/IVANOVS_L100/'
#path2 = '/uio/kant/geo-ceed-u1/nilscp/Desktop/stallo_work/benchmarkFI/CPPR/UAVG/CPPR10/COLDWPO/COLDWPO_L100/'
#path3 = '/uio/kant/geo-ceed-u1/nilscp/Desktop/stallo_work/benchmarkFI/CPPR/UAVG/CPPR10/COLDNOP/COLDNOP_L100/'
#path4 = '/uio/kant/geo-ceed-u1/nilscp/Desktop/stallo_work/benchmarkFI/CPPR/UAVG/CPPR10/SANDCOH/SANDCOH_L100/'
path1 = '/uio/kant/geo-ceed-u1/nilscp/Desktop/stallo_work/benchmarkFI/CPPR/UAVG/CPPR5/CDILWPO/CDILWPO_L100/'
path2 = '/uio/kant/geo-ceed-u1/nilscp/Desktop/stallo_work/benchmarkFI/CPPR/UAVG/CPPR10/CDILWPO/CDILWPO_L100/'
path3 = '/uio/kant/geo-ceed-u1/nilscp/Desktop/stallo_work/benchmarkFI/CPPR/UAVG/CPPR20/CDILWPO/CDILWPO_L100/'
#path4 = '/uio/kant/geo-ceed-u1/nilscp/Desktop/stallo_work/benchmarkFI/CPPR/UAVG/CPPR10/SANDCOH/SANDCOH_L100/'
os.chdir(path1)
model1 = psp.opendatfile('jdata.dat')
den1 = model1.readStep('Den', 68)
os.chdir(path2)
model2 = psp.opendatfile('jdata.dat')
den2 = model2.readStep('Den', 68)
os.chdir(path3)
model3 = psp.opendatfile('jdata.dat')
den3 = model3.readStep('Den', 68)
os.chdir(path4)
model4 = psp.opendatfile('jdata.dat')
den4 = model4.readStep('Den', 400)
plt.figure(1)
import ejecta as ej
'''
***********************************************************************
'''
path = '/work/nilscp/iSALE/isaleruns/testruns/ejecta/L20km_part1_HYDRO_CPPR1000/results/L20km_HYDRO_part2_CPPR80g/'
path = '/work/nilscp/iSALE/isaleruns/testruns/ejecta/L20km_part1_HYDRO_CPPR1000/results/L20km_HYDRO_part1g/'
path = '/uio/kant/geo-ceed-u1/nilscp/Desktop/stallo_work/ejecta/results/length/a2km/'
path = '/uio/kant/geo-ceed-u1/nilscp/Desktop/stallo_work/ejecta/results/length/a2km_C1000/'
path = '/work/nilscp/iSALE/isaleruns/testruns/multilayers/NILS_L100/'
'''
***********************************************************************
'''
os.chdir(path)
model = psp.opendatfile('jdata.dat')
'''
***********************************************************************
'''
# print a single saved timesteps
u = 0
den = model.readStep(['Den', 'Yld'], u)
step = copy.deepcopy(den)
a = 2000.
plt.pcolormesh(model.x / a, model.y / a, step.cmc[0], cmap='Pastel1')
# plot the high resolution zone
plt.hlines(model.yhires[0] / a,
model.xhires[0] / a,
import pySALEPlot as psp
from matplotlib.pyplot import figure,colorbar
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.axes_grid1 import make_axes_locatable
# This example plotting script designed to plot
# damage in the demo2D example simulation
# Make an output directory
#field1 = 'Den'#raw_input('Which field is to be considered? (3 chars) =>')
field2 = 'Den'#raw_input('Which field is to be considered? (3 chars) =>')
dirname='./%s'%field2
psp.mkdir_p(dirname)
# Open the datafile
model=psp.opendatfile('jdata.dat')
# Set the distance units to km
model.setScale('um')
# Set up a pylab figure
fig=figure()
ax=fig.add_subplot(111,aspect='equal')
fig.set_size_inches(4,3)
# Loop over timesteps, in increments of 5
#step_1=model.readStep('%s'%field2,0)
#MAXvalue = abs(np.amax(step_1.data[0]))
plt.tight_layout()
for i in np.arange(0,37,1):
# Set the axis labels
from mpl_toolkits.axes_grid1 import make_axes_locatable
# If viridis colormap is available, use it here
try:
plt.set_cmap('viridis')
except:
plt.set_cmap('YlGnBu_r')
# This example plotting script designed to plot
# damage and pressure for the demo2D example
# Make an output directory
dirname = './generatedPlots/25kms'
# Open the datafile
model = psp.opendatfile('./data/job-25kmhr/jdata.dat')
# Set the distance units to km
model.setScale('km')
# Set up a pylab figure
fig = plt.figure(figsize=(8, 4))
ax = fig.add_subplot(111, aspect='equal')
divider = make_axes_locatable(ax)
# Loop over timesteps
for i in np.arange(0,5000,5):
# Set the axis labels
ax.set_xlabel('r [km]')
import pySALEPlot as psp
import matplotlib.pyplot as plt
import numpy as np
# This example plotting script designed to plot
# a vertical pressure profile of the Chicxulub example
# Open the datafile
#model=psp.opendatfile('/media/sf_Public/data/job-1_6km/jdata.dat')
model = psp.opendatfile('./data/job-9i/jdata.dat')
# Set the distance units to mm
model.setScale('km')
[model.tru[u].truInfo() for u in range(model.tracer_numu)]
step0 = model.readStep('TrM', 0)
stepTrT0 = model.readStep('TrT', 0)
# Set up a pyplot figure
fig = plt.figure(figsize=(20, 10))
ax = fig.add_subplot(111, aspect='equal')
# Set the axis labels
ax.set_xlabel('r [km]')
ax.set_ylabel('z [km]')
# Set the axis limits
rad_km = 50
depth_km = 30
III =0
field1 = 'Pre'
field2 = 'V_y'
field3 = 'Den'
field4 = 'TPS'
field5 = 'Syy'
tstart = 1 # Start at t>0 such that there IS a shock present
tfin = 56
tintv = 1
for directory in dirs:
modelv150 = psp.opendatfile('{}/v150/jdata.dat'.format(directory)) # Open datafile
modelv200 = psp.opendatfile('{}/v200/jdata.dat'.format(directory)) # Open datafile
modelv250 = psp.opendatfile('{}/v250/jdata.dat'.format(directory)) # Open datafile
modelv300 = psp.opendatfile('{}/v300/jdata.dat'.format(directory)) # Open datafile
modelv350 = psp.opendatfile('{}/v350/jdata.dat'.format(directory)) # Open datafile
modelv450 = psp.opendatfile('{}/v450/jdata.dat'.format(directory)) # Open datafile
modelv550 = psp.opendatfile('{}/v550/jdata.dat'.format(directory)) # Open datafile
modelv650 = psp.opendatfile('{}/v650/jdata.dat'.format(directory)) # Open datafile
modelv750 = psp.opendatfile('{}/v750/jdata.dat'.format(directory)) # Open datafile
modelv850 = psp.opendatfile('{}/v850/jdata.dat'.format(directory)) # Open datafile
modelv950 = psp.opendatfile('{}/v950/jdata.dat'.format(directory)) # Open datafile
models = [modelv150,modelv200,modelv250,modelv300,modelv350,modelv450,modelv550,modelv650,modelv750,modelv850,modelv950]
modelS = (['v150','v200','v250','v300','v350','v450','v550','v650','v750','v850','v950'])
VI = ([150,200,250,300,350,450,550,650,750,850,950])
[model.setScale('mm') for model in models]
III = 0
'name_file3',
'name_file4')
label_name = ('Y$_{d0}$ = 100 kPa',
'Y$_{d0}$ = 10 kPa',
'Y$_{d0}$ = 1 kPa',
'Y$_{d0}$ = 0.1 kPa')
colour = ('#f58f00', '#f35757', '#617BB7','#E06AAF')
# Open the data files.
for i in range(4):
# Read simulation files
# Replace name of the files as appropriate
model=psp.opendatfile(moddir[i]+'/jdata.dat', tracermassvol=True)
model.addRestartFile(moddir[i]+'regrid/jdata.dat')
# Define simulation constants
rho = # Target density
delta = # Impactor density
U = # Impact velocity
a = # Impactor radius
m = 4./3.*np.pi*delta*a**3. # Impactor mass (if spherical)
# Define numerical constants
# Initial guess for constants
c1 = # Approximation of C1 constant
k = # Approximation of k constant
mu = # Approximation of mu constant
p = # Approximation of p constant
import numpy as np
import scipy as sc
import scipy.stats as stats
import pySALEPlot as psp
import matplotlib.pyplot as plt
field1 = 'Pre'
field2 = 'V_y'
field3 = 'Den'
field4 = 'TPS'
field5 = 'Tmp'
dirname= 'shockfronts'
model = psp.opendatfile('./jdata.dat') # Open datafile
psp.mkdir_p('./shockfronts')
model.setScale('mm')
tstart = 1 # Start at t>0 such that there IS a shock present
tfin = 250
tintv = 1
YC = model.yc
XC = model.xc
TME = np.zeros(( int((tfin-tstart+1)/tintv) )) # time
YSF = np.zeros(( int((tfin-tstart+1)/tintv) )) # Shock Front Y position
PBD = np.zeros(( int((tfin-tstart+1)/tintv) )) # Shock in Particle Bed array. 1 is yes 0 is no
QUP = np.zeros(( int((tfin-tstart+1)/tintv) )) # Quasi steady state Particle velocity
Us = np.zeros(( int((tfin-tstart+1)/(5*tintv))+1 ))
Up = np.zeros(( int((tfin-tstart+1)/(5*tintv))+1 )) # Shock and particle velocities calculated every 5 timesteps
Time = np.zeros(( int((tfin-tstart+1)/(5*tintv))+1 )) # Equivalent time every 5 timesteps (=.1 us)
layers.append(-1 * 10**16)
print('DONE\n')
# make sure Results.dat exists
open('Results.dat', 'a').close()
filetest = open('Results.dat', 'r')
filetest.close()
#============================================================
# Peak Values Search Starts Here
#============================================================
#Find the peak pressures of all tracers
print('Extracting Peak Pressure')
model1 = psp.opendatfile(peak_file)
model1.setScale('km')
step1 = model1.readStep('TrP', model1.nsteps - 1)
pres = np.append(np.zeros(0), step1.TrP / 10**9)
print('Using timestep {0} of {1} with {2} tracers'.format(
model1.nsteps - 1, peak_file, len(pres)))
print('DONE\n')
# extract the materials and weights
print('Extracting Materials...')
model = psp.opendatfile(data_file)
model.setScale('km')
step = model.readStep('TrT', 0)
xx_0 = np.append(np.zeros(0), step.xmark)
yy_0 = np.append(np.zeros(0), step.ymark)
P_avg = np.mean(P[j-1:j+1])
if (P_avg<0.2*P_Quasi and JJ == 0):
JJ = j
return II,JJ
field1 = 'Pre'
field2 = 'V_x'
field3 = 'V_y'
field4 = 'Den'
field5 = 'Syy'
dirname='./del-t' # Directory name for the output files
modelv150 = psp.opendatfile('./v150/jdata.dat') # Open datafile
modelv250 = psp.opendatfile('./v250/jdata.dat') # Open datafile
modelv350 = psp.opendatfile('./v350/jdata.dat') # Open datafile
modelv450 = psp.opendatfile('./v450/jdata.dat') # Open datafile
modelv550 = psp.opendatfile('./v550/jdata.dat') # Open datafile
modelv650 = psp.opendatfile('./v650/jdata.dat') # Open datafile
modelv750 = psp.opendatfile('./v750/jdata.dat') # Open datafile
modelv850 = psp.opendatfile('./v850/jdata.dat') # Open datafile
modelv950 = psp.opendatfile('./v950/jdata.dat') # Open datafile
modelv1050 = psp.opendatfile('./v1050/jdata.dat') # Open datafile
models = [modelv150,modelv250,modelv350,modelv450,modelv550,modelv650,modelv750,modelv850,modelv950,modelv1050]
VI = ([150,250,350,450,550,650,750,850,950,1050])
[model.setScale('mm') for model in models]
N = 10
t1 = .2
for j in range(j_i, j_f, -1):
P_avg = np.mean(P[j - 1:j + 1])
if (P_avg < 0.2 * P_Quasi and JJ == 0):
JJ = j
return II, JJ
field1 = 'Pre'
field2 = 'V_x'
field3 = 'V_y'
field4 = 'Den'
field5 = 'Syy'
dirname = './del-t' # Directory name for the output files
modelv150 = psp.opendatfile('./v150/jdata.dat') # Open datafile
modelv250 = psp.opendatfile('./v250/jdata.dat') # Open datafile
modelv350 = psp.opendatfile('./v350/jdata.dat') # Open datafile
modelv450 = psp.opendatfile('./v450/jdata.dat') # Open datafile
modelv550 = psp.opendatfile('./v550/jdata.dat') # Open datafile
modelv650 = psp.opendatfile('./v650/jdata.dat') # Open datafile
modelv750 = psp.opendatfile('./v750/jdata.dat') # Open datafile
modelv850 = psp.opendatfile('./v850/jdata.dat') # Open datafile
modelv950 = psp.opendatfile('./v950/jdata.dat') # Open datafile
modelv1050 = psp.opendatfile('./v1050/jdata.dat') # Open datafile
models = [
modelv150, modelv250, modelv350, modelv450, modelv550, modelv650,
modelv750, modelv850, modelv950, modelv1050
]
VI = ([150, 250, 350, 450, 550, 650, 750, 850, 950, 1050])
def main(path, folders, paths, method, thresholdf, g):
'''
description:
loading of the data + all calculation in the function wrap
inputs:
path: directory contaning all the models
folders: folders containing all the models
paths: saving directory
method: 2 or 3 dots
outputs:
Three .txt files are saved:
one text file that contains the depth, diameter and volume of the excavated
cavity, name : modelname + '_excavated.txt'
one text file that contains the tracers and their original position
name : modelname + '_tracersXY_excavated.txt'
one text file that contains the boundary between excavated and non excavated
materials (i.e, the hinge streamline)
name : modelname + '_tracersXY_contour_excavated.txt'
'''
# Change path to working directory
os.chdir(path)
# select folders in directory
#folders = glob.glob(search)
for modelname in folders:
patht = path + modelname
os.chdir(patht)
# print modelname
print modelname
model = psp.opendatfile('jdata.dat')
(Ve, de, Re, X, Y, Xc, Yc, timesteps, tracer_idx, n, v, angle, xpos,
tair, xland) = wrap(model, method, thresholdf, g)
# create plots directory
path_data = paths + modelname + "/excavated/"
if not os.path.exists(path_data):
os.makedirs(path_data)
os.chdir(path_data)
# DATA
header_txt = "Volume_exc;depth_exc;diameter_exc"
# we need to define the name of the txt file that will be saved
fname = modelname + '_excavated.txt'
# time, depth, diameter, volume
output = np.column_stack((Ve, de, Re*2.))
np.savetxt(fname, output, header=header_txt,
delimiter=';', fmt=['%1.6e', '%1.6e', '%1.6e'])
# DATA TRACERS XY ALL
fname = modelname + '_tracersXY_excavated.txt'
header_txt = "X;Y"
output = np.column_stack((X, Y))
np.savetxt(fname, output, header=header_txt,
delimiter=';', fmt=['%1.6e', '%1.6e'])
# DATA TRACERS XY contours
fname = modelname + '_tracersXY_contour_excavated.txt'
header_txt = "XC;YC"
output = np.column_stack((Xc, Yc))
np.savetxt(fname, output, header=header_txt,
delimiter=';', fmt=['%1.6e', '%1.6e'])
# tracers
path_ej = paths + modelname + "/ejtracers/"
if not os.path.exists(path_ej):
os.makedirs(path_ej)
os.chdir(path_ej)
header_txt = "tracer_idx;timesteps;v;angle;xpos;tair;xland"
# we need to define the name of the txt file that will be saved
fname_ej = modelname + '_ejtracers.txt'
# time, depth, diameter, volume
output = np.column_stack((tracer_idx, timesteps, v, angle, xpos,
tair, xland))
np.savetxt(fname_ej, output, header=header_txt,
delimiter=';', fmt=['%1.6e', '%1.6e', '%1.6e',
'%1.6e', '%1.6e', '%1.6e', '%1.6e'])
header_txt = "ntracers"
# we need to define the name of the txt file that will be saved
fname_ej = modelname + '_ntracers.txt'
# time, depth, diameter, volume
output = n
np.savetxt(fname_ej, output, header=header_txt,
delimiter=';', fmt='%1.6e')
# close model file
model.closeFile()
def main(path, folders, paths, mode, id_mat, transient, idx_manual=0):
'''
description:
calculate all final crater dimensions for 1-layer targets
inputs:
path: path containing folders with models (jdata in each modelled case)
folders: all models
paths: saving directory
mode: mostly equal to 0 (if artifacts along the boundary, can be set to 1)
id_mat: material id (0: all, 1: projectile, 2: first layer, 3: second ...)
transient: 0 (by volume)
: 1 (by the maximum depth along the crater cavity)
outputs:
1 .txt file with all crater dimensions every saved timesteps
1. txt file with all transient crater dimensions
1. txt file with all final crater dimensions
each of these text files are saved in different folders
so 3 txt files are created per models
'''
# Change path to working directory
os.chdir(path)
# loop through models in folders
for modelname in folders:
# change directory to
patht = path + modelname
os.chdir(patht)
# print modelname
print(modelname)
# open model with pySALEplot
model = psp.opendatfile('jdata.dat')
# calculate all final crater dimensions
time, depth, mdepth, diam, vol, ec, ls, pf, alt, drim, Vrim = craterdimensions(
model, mode, id_mat)
####################################################
# CALCULATE CRATER DIMENSIONS DURING CRATER EVOLUTION (EACH STEP)
####################################################
# create plots directory if not existing
path_data = paths + modelname + "/evolution/"
if not os.path.exists(path_data):
os.makedirs(path_data)
os.chdir(path_data)
# export data to .txt file
header_txt = "time\tdepth\tmdepth\tdiameter\tvolume\tls\tec\tpf\talt\tdrim\tVrim"
# we need to define the name of the txt file that will be saved
fname = modelname + '_data.txt'
# output file
output = np.column_stack(
(time, depth, mdepth, diam, vol, ls, ec, pf, alt, drim, Vrim))
np.savetxt(fname,
output,
header=header_txt,
delimiter='\t',
fmt=[
'%1.6e', '%1.6e', '%1.6e', '%1.6e', '%1.6e', '%1.6e',
'%1.6e', '%1.6e', '%1.6e', '%1.6e', '%1.6e'
])
####################################################
# CALCULATE CRATER DIMENSIONS AT THE TRANSIENT CRATER
####################################################
# create plots directory if not existing
path_data = paths + modelname + "/transient/"
if not os.path.exists(path_data):
os.makedirs(path_data)
os.chdir(path_data)
fname = modelname + '_tr.txt'
header_txt = "tr_time\ttr_depth\ttr_diameter\ttr_vol\talt\td_rim\tV_rim\tidx"
# the transient crater diameter is defined at the maximum volume
if transient == 0:
idx_tr = np.nanargmax(vol)
else:
idx_tr = np.nanargmax(mdepth) # if maximum depth is used
# transient crater values are stored in another .txt file and folder
if mode == 0:
output2 = np.column_stack(
(time[idx_tr], depth[idx_tr], diam[idx_tr], vol[idx_tr],
alt[idx_tr], drim[idx_tr], Vrim[idx_tr], idx_tr))
np.savetxt(fname,
output2,
header=header_txt,
delimiter='\t',
fmt=[
'%1.6e', '%1.6e', '%1.6e', '%1.6e', '%1.6e',
'%1.6e', '%1.6e', '%1.6e'
])
else:
output2 = np.column_stack(
(time[idx_tr], mdepth[idx_tr], diam[idx_tr], vol[idx_tr],
alt[idx_tr], drim[idx_tr], Vrim[idx_tr], idx_tr))
np.savetxt(fname,
output2,
header=header_txt,
delimiter='\t',
fmt=[
'%1.6e', '%1.6e', '%1.6e', '%1.6e', '%1.6e',
'%1.6e', '%1.6e', '%1.6e'
])
####################################################
# CALCULATE CRATER DIMENSIONS AT THE FINAL CRATER
####################################################
# it should take the value at t/tr = 10 and not as the mean of the last 5 values, it could make some of the other codes easier
# the problem that I should not take any values maybe I should say that it should be at least
# create plots directory if not existing
path_data = paths + modelname + "/final/"
if not os.path.exists(path_data):
os.makedirs(path_data)
os.chdir(path_data)
# at t/tr for different times
tnorm = time / time[idx_tr]
# save for t/tr = 2, 3, 4, 5, 7.5 and 10.0
tnorm_fname = ['020', '030', '040', '050', '070', '100']
for iv, tnormv in enumerate([2.0, 3.0, 4.0, 5.0, 7.0, 10.0]):
__, stp1 = find_nearest(tnorm, tnormv)
fname = modelname + '_final' + tnorm_fname[iv] + '.txt'
header_txt = "f_time\tf_depth\tf_diameter\tf_vol\tf_alt\tf_drim\tf_Vrim"
# if it did not reach the final crater, then nothing should be save in the final folder
if tnorm[np.where(~np.isnan(diam))[0][-1]] >= tnormv - 0.20:
# final crater values are stored in another .txt file and folder
if mode == 0:
output2 = np.column_stack(
(np.nanmean(time[stp1]), np.nanmean(depth[stp1]),
np.nanmean(diam[stp1]), np.nanmean(vol[stp1]),
np.nanmean(alt[stp1]), np.nanmean(drim[stp1]),
np.nanmean(Vrim[stp1])))
np.savetxt(fname,
output2,
header=header_txt,
delimiter='\t',
fmt=[
'%1.6e', '%1.6e', '%1.6e', '%1.6e', '%1.6e',
'%1.6e', '%1.6e'
])
else:
output2 = np.column_stack(
(np.nanmean(time[stp1]), np.nanmean(mdepth[stp1]),
np.nanmean(diam[stp1]), np.nanmean(vol[stp1]),
np.nanmean(alt[stp1]), np.nanmean(drim[stp1]),
np.nanmean(Vrim[stp1])))
np.savetxt(fname,
output2,
header=header_txt,
delimiter='\t',
fmt=[
'%1.6e', '%1.6e', '%1.6e', '%1.6e', '%1.6e',
'%1.6e', '%1.6e'
])
else:
if mode == 0:
output2 = np.column_stack((np.nan, np.nan, np.nan, np.nan,
np.nan, np.nan, np.nan))
np.savetxt(fname,
output2,
header=header_txt,
delimiter='\t',
fmt=[
'%1.6e', '%1.6e', '%1.6e', '%1.6e', '%1.6e',
'%1.6e', '%1.6e'
])
else:
output2 = np.column_stack((np.nan, np.nan, np.nan, np.nan,
np.nan, np.nan, np.nan))
np.savetxt(fname,
output2,
header=header_txt,
delimiter='\t',
fmt=[
'%1.6e', '%1.6e', '%1.6e', '%1.6e', '%1.6e',
'%1.6e', '%1.6e'
])
####################################################################
# CALCULATE CRATER DIMENSIONS AT THE FINAL CRATER (MANUAL)
####################################################################
# it should take the value at t/tr = 10 and not as the mean of the last 5 values, it could make some of the other codes easier
# the problem that I should not take any values maybe I should say that it should be at least
# create plots directory if not existing
path_data = paths + modelname + "/manual/"
if not os.path.exists(path_data):
os.makedirs(path_data)
os.chdir(path_data)
# only run the script if idx_manual is specified
if idx_manual > 0:
stp1 = idx_manual
fname = modelname + '_final.txt'
header_txt = "f_time\tf_depth\tf_diameter\tf_vol\tf_alt\tf_drim\tf_Vrim"
if mode == 0:
output2 = np.column_stack(
(np.nanmean(time[stp1]), np.nanmean(depth[stp1]),
np.nanmean(diam[stp1]), np.nanmean(vol[stp1]),
np.nanmean(alt[stp1]), np.nanmean(drim[stp1]),
np.nanmean(Vrim[stp1])))
np.savetxt(fname,
output2,
header=header_txt,
delimiter='\t',
fmt=[
'%1.6e', '%1.6e', '%1.6e', '%1.6e', '%1.6e',
'%1.6e', '%1.6e'
])
else:
output2 = np.column_stack(
(np.nanmean(time[stp1]), np.nanmean(mdepth[stp1]),
np.nanmean(diam[stp1]), np.nanmean(vol[stp1]),
np.nanmean(alt[stp1]), np.nanmean(drim[stp1]),
np.nanmean(Vrim[stp1])))
np.savetxt(fname,
output2,
header=header_txt,
delimiter='\t',
fmt=[
'%1.6e', '%1.6e', '%1.6e', '%1.6e', '%1.6e',
'%1.6e', '%1.6e'
])
else:
None
# close model file
model.closeFile()
def craterProfiles(folders, path, paths, idx, mode):
'''
description:
return the profile of the crater for the transient crater (mode = 1),
the final crater (mode = 2), or for a chosen time step (mode = 3, and idx = stp)
input:
mode = 1 # transient crater
mode = 2 # final crater
mode = 3 # any other craters
if mode = 1 or 2, idx does not count
if mode = 3, the values in idx will be taken
example:
folders = ['C00P20F06_L250','C00P20F06_L500']
path = '/media/nilscp/Cloud1/SENS/PORFRIC/results/'
paths = '/media/nilscp/Zell/Collapse/plots2/'
#transient
idx = 0
mode = 1
craterProfiles(folders, path, paths, idx, mode)
#final
idx = 0
mode = 2
craterProfiles(folders, path, paths, idx, mode)
#arbitrary (timestep = 4)
idx = 4
mode = 3
craterProfiles(folders, path, paths, idx, mode)
'''
# we can loop through models
for ix, modelname in enumerate(folders):
# change to working directory
patht = paths + modelname
os.chdir(patht)
# print modelname
print(modelname)
# id_mat
id_mat = 0
# load jdata.data
model = psp.opendatfile(path + modelname + '/jdata.dat')
# Get the y-index of the pre-surface
oridy = np.where(model.yy == 0.)[0][0]
# get the time step (in sec)
den1 = model.readStep('Den', 1)
timestep = den1.time
# get the total time of the simulation
total_time = model.laststep * timestep
# get the index at when the transient crater is reached
tr_time, __, __, __, __, __, __, idx_tr = np.loadtxt(paths +
modelname +
'/transient/' +
modelname +
'_tr.txt')
idx_tr = idx_tr.astype('int')
# get the total time of the simulation (in normalized time)
total_time_norm = total_time / tr_time
# default normalized time
default_ntime = np.array([2.0, 3.0, 4.0, 5.0, 7.0, 10.0])
default_ntime = default_ntime.astype('int')
default_nfname = np.array(['020', '030', '040', '050', '070', '100'])
# where we have actually data for
real_ntime = default_ntime[default_ntime <= total_time_norm]
real_nfname = default_nfname[default_ntime <= total_time_norm]
# load data depending on the mode (if transient only)
if mode == 1:
####################################################
# TRANSIENT CRATER
####################################################
den = model.readStep('Den', idx_tr)
step = copy.deepcopy(den)
(rrim, altr) = get_cross_section(model, step, id_mat, oridy)
path_to_save = paths + modelname + '/transient/'
if not os.path.exists(path_to_save):
os.makedirs(path_to_save)
os.chdir(path_to_save)
fname = modelname + '_XYtransientprofile.txt'
header_txt = "distance\tdepth"
output = np.column_stack((rrim, altr))
np.savetxt(fname,
output,
header=header_txt,
delimiter='\t',
fmt=['%1.6e', '%1.6e'])
elif mode == 3:
####################################################
# SELECTED CRATER
####################################################
den = model.readStep('Den', idx)
step = copy.deepcopy(den)
(rrim, altr) = get_cross_section(model, step, id_mat, oridy)
path_to_save = paths + modelname + '/arbitrary/'
if not os.path.exists(path_to_save):
os.makedirs(path_to_save)
os.chdir(path_to_save)
fname = modelname + '_XY' + str(idx) + '_profile.txt'
header_txt = "distance\tdepth"
output = np.column_stack((rrim, altr))
np.savetxt(fname,
output,
header=header_txt,
delimiter='\t',
fmt=['%1.6e', '%1.6e'])
else: # mode == 2
####################################################
# FINAL CRATER at different normalized time
####################################################
for ir, r in enumerate(real_ntime):
idx = r * idx_tr
den = model.readStep('Den', idx)
step = copy.deepcopy(den)
(rrim, altr) = get_cross_section(model, step, id_mat, oridy)
path_to_save = paths + modelname + '/final/'
if not os.path.exists(path_to_save):
os.makedirs(path_to_save)
os.chdir(path_to_save)
fname = modelname + '_XYfinalprofile' + real_nfname[ir] + '.txt'
header_txt = "distance\tdepth"
output = np.column_stack((rrim, altr))
np.savetxt(fname,
output,
header=header_txt,
delimiter='\t',
fmt=['%1.6e', '%1.6e'])
# close model file
model.closeFile()
print("transient/final crater profiles are saved")
