diff --git a/docs/install-anaconda.md b/docs/install-anaconda.md
index 4ba6915c47ce027619eb075d9cf8f10f9ac7bc8f..f22d59b2745060de601de88838310ef74010ac69 100644
--- a/docs/install-anaconda.md
+++ b/docs/install-anaconda.md
@@ -8,8 +8,8 @@
conda update --all
conda create -n wetb_py3 python=3.5
source activate wetb_py3
-conda install setuptools_scm future h5py pytables pytest nose sphinx
+conda install setuptools_scm future h5py pytables pytest nose sphinx blosc
conda install scipy pandas matplotlib cython xlrd coverage xlwt openpyxl
-pip install pyscaffold pytest-cov
+pip install pyscaffold pytest-cov --no-deps
```
diff --git a/docs/install-manual-detailed.md b/docs/install-manual-detailed.md
index 81acbbbf1f66f1df6eca725f17ec283dc09f15e6..c18162998e5c0cbfd87564b62b6dd4689875e9ef 100644
--- a/docs/install-manual-detailed.md
+++ b/docs/install-manual-detailed.md
@@ -165,7 +165,7 @@ activate py27
* Install the necessary Python dependencies using the conda package manager:
```
-conda install setuptools_scm future h5py pytables pytest nose sphinx
+conda install setuptools_scm future h5py pytables pytest nose sphinx blosc
conda install scipy pandas matplotlib cython xlrd coverage xlwt openpyxl
```
@@ -173,7 +173,7 @@ conda install scipy pandas matplotlib cython xlrd coverage xlwt openpyxl
easily installed with pip:
```
-pip install pyscaffold pytest-cov
+pip install pyscaffold pytest-cov --no-deps
```
diff --git a/wetb/prepost/Simulations.py b/wetb/prepost/Simulations.py
index 4c5d7bd2c6da30fd153caa1714763a2603d3b88a..5953852f9733b6329fc21d61513edfb75a456512 100755
--- a/wetb/prepost/Simulations.py
+++ b/wetb/prepost/Simulations.py
@@ -1047,7 +1047,8 @@ def launch(cases, runmethod='local', verbose=False, copyback_turb=True,
'linux-script, windows-script, local-ram, none'
raise ValueError(msg)
-def post_launch(cases, save_iter=False, silent=False):
+def post_launch(cases, save_iter=False, silent=False, suffix=None,
+ path_errorlog=None):
"""
Do some basics checks: do all launched cases have a result and LOG file
and are there any errors in the LOG files?
@@ -1153,8 +1154,11 @@ def post_launch(cases, save_iter=False, silent=False):
# but put in one level up, so in the logfiles folder directly
errorlogs.ResultFile = sim_id + '_ErrorLog.csv'
# save the log file analysis in the run_dir instead of the log_dir
- errorlogs.PathToLogs = run_dir# + log_dir
- errorlogs.save()
+ if path_errorlog is None:
+ errorlogs.PathToLogs = run_dir# + log_dir
+ else:
+ errorlogs.PathToLogs = path_errorlog
+ errorlogs.save(suffix=suffix)
# save the error LOG list, this is redundant, since it already exists in
# the general LOG file (but only as a print, not the python variable)
@@ -1167,7 +1171,7 @@ def post_launch(cases, save_iter=False, silent=False):
return cases_fail
-def copy_pbs_in_failedcases(cases_fail, pbs_fail='pbs_in_fail', silent=True):
+def copy_pbs_in_failedcases(cases_fail, path='pbs_in_fail', silent=True):
"""
Copy all the pbs_in files from failed cases to a new directory so it
is easy to re-launch them
@@ -1181,7 +1185,7 @@ def copy_pbs_in_failedcases(cases_fail, pbs_fail='pbs_in_fail', silent=True):
src = os.path.join(run_dir, case['[pbs_in_dir]'], pbs_in_fname)
- pbs_in_dir_fail = case['[pbs_in_dir]'].replace('pbs_in', pbs_fail)
+ pbs_in_dir_fail = case['[pbs_in_dir]'].replace('pbs_in', path)
dst = os.path.join(run_dir, pbs_in_dir_fail, pbs_in_fname)
if not silent:
@@ -2543,12 +2547,12 @@ class ErrorLogs(object):
# TODO: move to the HAWC2 plugin for cases
- def __init__(self, silent=False, cases=None):
+ def __init__(self, silent=False, cases=None, resultfile='ErrorLog.csv'):
self.silent = silent
# specify folder which contains the log files
self.PathToLogs = ''
- self.ResultFile = 'ErrorLog.csv'
+ self.ResultFile = resultfile
self.cases = cases
@@ -2581,7 +2585,7 @@ class ErrorLogs(object):
self.err_init[' *** ERROR *** Error findin'] = len(self.err_init)
# *** ERROR *** In body actions
self.err_init[' *** ERROR *** In body acti'] = len(self.err_init)
- # *** ERROR *** Command unknown
+ # *** ERROR *** Command unknown and ignored
self.err_init[' *** ERROR *** Command unkn'] = len(self.err_init)
# *** ERROR *** ERROR - More bodies than elements on main_body: tower
self.err_init[' *** ERROR *** ERROR - More'] = len(self.err_init)
@@ -2681,11 +2685,22 @@ class ErrorLogs(object):
tempLog = []
tempLog.append(fname)
exit_correct, found_error = False, False
+
+ subcols_sim = 4
+ subcols_init = 2
# create empty list item for the different messages and line
# number. Include one column for non identified messages
- for j in range(self.init_cols + self.sim_cols + 1):
- tempLog.append('')
- tempLog.append('')
+ for j in range(self.init_cols):
+ # 2 sub-columns per message: nr, msg
+ for k in range(subcols_init):
+ tempLog.append('')
+ for j in range(self.sim_cols):
+ # 4 sub-columns per message: first, last, nr, msg
+ for k in range(subcols_sim):
+ tempLog.append('')
+ # and two more columns at the end for messages of unknown origin
+ tempLog.append('')
+ tempLog.append('')
# if there is a cases object, see how many time steps we expect
if self.cases is not None:
@@ -2729,32 +2744,51 @@ class ErrorLogs(object):
# if string is shorter, we just get a shorter string.
# checking presence in dict is faster compared to checking
# the length of the string
+ # first, last, nr, msg
if msg in self.err_init:
- col_nr = self.err_init[msg]
- # 2nd item is the column position of the message
- tempLog[2*(col_nr+1)] = line
- # line number of the message
- tempLog[2*col_nr+1] += '%i, ' % j
+ # icol=0 -> fname
+ icol = subcols_init*self.err_init[msg] + 1
+ # 0: number of occurances
+ if tempLog[icol] == '':
+ tempLog[icol] = '1'
+ else:
+ tempLog[icol] = str(int(tempLog[icol]) + 1)
+ # 1: the error message itself
+ tempLog[icol+1] = line
found_error = True
# find errors that can occur during simulation
elif msg in self.err_sim:
- col_nr = self.err_sim[msg] + self.init_cols
- # 2nd item is the column position of the message
- tempLog[2*(col_nr+1)] = line
+ icol = subcols_sim*self.err_sim[msg]
+ icol += subcols_init*self.init_cols + 1
# in case stuff already goes wrong on the first time step
if time_step == -1:
time_step = 0
- # line number of the message
- tempLog[2*col_nr+1] += '%i, ' % time_step
+
+ # 1: time step of first occurance
+ if tempLog[icol] == '':
+ tempLog[icol] = '%i' % time_step
+ # 2: time step of last occurance
+ tempLog[icol+1] = '%i' % time_step
+ # 3: number of occurances
+ if tempLog[icol+2] == '':
+ tempLog[icol+2] = '1'
+ else:
+ tempLog[icol+2] = str(int(tempLog[icol+2]) + 1)
+ # 4: the error message itself
+ tempLog[icol+3] = line
+
found_error = True
iterations[time_step,2] = 1
# method of last resort, we have no idea what message
elif line[:10] == ' *** ERROR' or line[:10]==' ** WARNING':
- tempLog[-2] = line
+ icol = subcols_sim*self.sim_cols
+ icol += subcols_init*self.init_cols + 1
# line number of the message
- tempLog[-1] = j
+ tempLog[icol] = j
+ # and message
+ tempLog[icol+1] = line
found_error = True
# in case stuff already goes wrong on the first time step
if time_step == -1:
@@ -2863,11 +2897,11 @@ class ErrorLogs(object):
else:
self.save(appendlog=appendlog)
- def save(self, appendlog=False):
+ def save(self, appendlog=False, suffix=None):
# write the results in a file, start with a header
- contents = 'file name;' + 'lnr;msg;'*(self.init_cols)
- contents += 'iter_nr;msg;'*(self.sim_cols)
+ contents = 'file name;' + 'nr;msg;'*(self.init_cols)
+ contents += 'first_tstep;last_tstep;nr;msg;'*(self.sim_cols)
contents += 'lnr;msg;'
# and add headers for elapsed time, nr of iterations, and sec/iteration
contents += 'Elapsted time;last time step;Simulation time;'
@@ -2882,7 +2916,11 @@ class ErrorLogs(object):
contents = contents + '\n'
# write csv file to disk, append to facilitate more logfile analysis
- fname = os.path.join(self.PathToLogs, str(self.ResultFile))
+ if isinstance(suffix, str):
+ tmp = self.ResultFile.replace('.csv', '_%s.csv' % suffix)
+ fname = os.path.join(self.PathToLogs, tmp)
+ else:
+ fname = os.path.join(self.PathToLogs, str(self.ResultFile))
if not self.silent:
print('Error log analysis saved at:')
print(fname)
@@ -3318,7 +3356,7 @@ class WeibullParameters(object):
def compute_env_of_env(envelope, dlc_list, Nx=300, Nsectors=12, Ntheta=181):
"""
- The function computes load envelopes for given channels and a groups of
+ The function computes load envelopes for given channels and a groups of
load cases starting from the envelopes computed for single simulations.
The output is the envelope of the envelopes of the single simulations.
This total envelope is projected on defined polar directions.
@@ -3326,7 +3364,7 @@ def compute_env_of_env(envelope, dlc_list, Nx=300, Nsectors=12, Ntheta=181):
Parameters
----------
- envelope : dict, dictionaries of interpolated envelopes of a given
+ envelope : dict, dictionaries of interpolated envelopes of a given
channel (it's important that each entry of the dictonary
contains a matrix of the same dimensions). The dictonary
is organized by load case
@@ -3335,28 +3373,28 @@ def compute_env_of_env(envelope, dlc_list, Nx=300, Nsectors=12, Ntheta=181):
Nx : int, default=300
Number of points for the envelope interpolation
-
+
Nsectors: int, default=12
Number of sectors in which the total envelope will be divided. The
default is every 30deg
-
+
Ntheta; int, default=181
Number of angles in which the envelope is interpolated in polar
coordinates.
-
+
Returns
-------
- envelope : array (Nsectors x 6),
+ envelope : array (Nsectors x 6),
Total envelope projected on the number of angles defined in Nsectors.
The envelope is projected in Mx and My and the other cross-sectional
moments and forces are fetched accordingly (at the same time step where
the corresponding Mx and My are occuring)
"""
-
+
# Group all the single DLCs
- cloud = np.zeros(((Nx+1)*len(envelope),6))
+ cloud = np.zeros(((Nx+1)*len(envelope),6))
for i in range(len(envelope)):
cloud[(Nx+1)*i:(Nx+1)*(i+1),:] = envelope[dlc_list[i]]
# Compute total Hull of all the envelopes
@@ -3367,10 +3405,10 @@ def compute_env_of_env(envelope, dlc_list, Nx=300, Nsectors=12, Ntheta=181):
cc_x,cc_up,cc_low,cc_int= int_envelope(cc[:,0], cc[:,1], Nx=Nx)
# Project full envelope on given direction
cc_proj = proj_envelope(cc_x, cc_up, cc_low, cc_int, Nx, Nsectors, Ntheta)
-
+
env_proj = np.zeros([len(cc_proj),6])
env_proj[:,:2] = cc_proj
-
+
# Based on Mx and My, gather the remaining cross-sectional forces and
# moments
for ich in range(2, 6):
@@ -3378,18 +3416,18 @@ def compute_env_of_env(envelope, dlc_list, Nx=300, Nsectors=12, Ntheta=181):
s1 = np.array(cloud[hull.vertices[0], ich]).reshape(-1, 1)
s0 = np.append(s0, s1, axis=0)
cc = np.append(cc, s0, axis=1)
-
+
_,_,_,extra_sensor = int_envelope(cc[:,0],cc[:,ich],Nx)
- es = np.atleast_2d(np.array(extra_sensor[:,1])).T
+ es = np.atleast_2d(np.array(extra_sensor[:,1])).T
cc_int = np.append(cc_int,es,axis=1)
-
+
for isec in range(Nsectors):
ids = (np.abs(cc_int[:,0]-cc_proj[isec,0])).argmin()
env_proj[isec,ich] = (cc_int[ids-1,ich]+cc_int[ids,ich]+\
cc_int[ids+1,ich])/3
-
+
return env_proj
-
+
def int_envelope(ch1,ch2,Nx):
# Function to interpolate envelopes and output arrays of same length
@@ -3411,8 +3449,8 @@ def int_envelope(ch1,ch2,Nx):
lower = np.concatenate((np.array([ch1[indmin:],ch2[indmin:]]).T,
np.array([ch1[:indmax+1],ch2[:indmax+1]]).T),
axis=0)
-
-
+
+
int_1 = np.linspace(min(upper[:,0].min(),lower[:,0].min()),
max(upper[:,0].max(),lower[:,0].max()),Nx/2+1)
upper = np.flipud(upper)
@@ -3435,20 +3473,20 @@ def proj_envelope(env_x, env_up, env_low, env, Nx, Nsectors, Ntheta):
theta_int = np.linspace(-np.pi,np.pi,Ntheta)
sectors = np.linspace(-np.pi,np.pi,Nsectors+1)
proj = np.zeros([Nsectors,2])
-
+
R_up = np.sqrt(env_x**2+env_up**2)
theta_up = np.arctan2(env_up,env_x)
-
+
R_low = np.sqrt(env_x**2+env_low**2)
theta_low = np.arctan2(env_low,env_x)
-
+
R = np.concatenate((R_up,R_low))
theta = np.concatenate((theta_up,theta_low))
R = R[np.argsort(theta)]
theta = np.sort(theta)
-
+
R_int = np.interp(theta_int,theta,R,period=2*np.pi)
-
+
for i in range(Nsectors):
if sectors[i]>=-np.pi and sectors[i+1]<-np.pi/2:
indices = np.where(np.logical_and(theta_int >= sectors[i],
@@ -3478,17 +3516,17 @@ def proj_envelope(env_x, env_up, env_low, env, Nx, Nsectors, Ntheta):
maxR = R_int[indices].max()
proj[i,0] = maxR*np.cos(sectors[i])
proj[i,1] = maxR*np.sin(sectors[i])
-
- ind = np.where(sectors==0)
+
+ ind = np.where(sectors==0)
proj[ind,0] = env[:,0].max()
- ind = np.where(sectors==np.pi/2)
+ ind = np.where(sectors==np.pi/2)
proj[ind,1] = env[:,1].max()
- ind = np.where(sectors==-np.pi)
+ ind = np.where(sectors==-np.pi)
proj[ind,0] = env[:,0].min()
- ind = np.where(sectors==-np.pi/2)
+ ind = np.where(sectors==-np.pi/2)
proj[ind,1] = env[:,1].min()
return proj
@@ -3577,6 +3615,7 @@ class Cases(object):
self.loadstats = kwargs.get('loadstats', False)
self.rem_failed = kwargs.get('rem_failed', True)
self.config = kwargs.get('config', {})
+ self.complib = kwargs.get('complib', 'blosc')
# determine the input argument scenario
if len(args) == 1:
if type(args[0]).__name__ == 'dict':
@@ -3652,7 +3691,7 @@ class Cases(object):
self.cases.pop(k)
def launch(self, runmethod='local', verbose=False, copyback_turb=True,
- silent=False, check_log=True):
+ silent=False, check_log=True):
"""
Launch all cases
"""
@@ -3660,7 +3699,8 @@ class Cases(object):
launch(self.cases, runmethod=runmethod, verbose=verbose, silent=silent,
check_log=check_log, copyback_turb=copyback_turb)
- def post_launch(self, save_iter=False, copy_pbs_failed=True):
+ def post_launch(self, save_iter=False, copy_pbs_failed=True, suffix=None,
+ path_errorlog=None, silent=False):
"""
Post Launching Maintenance
@@ -3668,11 +3708,12 @@ class Cases(object):
accounted for.
"""
# TODO: integrate global post_launch in here
- self.cases_fail = post_launch(self.cases, save_iter=save_iter)
+ self.cases_fail = post_launch(self.cases, save_iter=save_iter,
+ suffix=suffix, path_errorlog=path_errorlog)
if copy_pbs_failed:
- copy_pbs_in_failedcases(self.cases_fail, pbs_in_fail='pbs_in_fail',
- silent=self.silent)
+ copy_pbs_in_failedcases(self.cases_fail, path='pbs_in_fail',
+ silent=silent)
if self.rem_failed:
self.remove_failed()
@@ -3813,7 +3854,7 @@ class Cases(object):
return
def cases2df(self):
- """Convert the cases dict to a DataFrame and save as excel sheet"""
+ """Convert the cases dict to a DataFrame and check data types"""
tag_set = []
@@ -4331,7 +4372,7 @@ class Cases(object):
fname = os.path.join(respath, resfile + '_postres.h5')
print(' saving post-processed res: %s...' % fname, end='')
df_new_sigs.to_hdf(fname, 'table', mode='w', format='table',
- complevel=9, complib='blosc')
+ complevel=9, complib=self.complib)
print('done!')
del df_new_sigs
@@ -4476,7 +4517,8 @@ class Cases(object):
# TODO: test this first
fname = os.path.join(post_dir, sim_id + '_statistics' + ext)
dfs = misc.dict2df(df_dict2, fname, save=save, update=update,
- csv=csv, xlsx=xlsx, check_datatypes=False)
+ csv=csv, xlsx=xlsx, check_datatypes=False,
+ complib=self.complib)
df_dict2 = None
df_dict = None
@@ -4498,7 +4540,8 @@ class Cases(object):
# TODO: test this first
fname = os.path.join(post_dir, sim_id + '_statistics' + ext)
dfs = misc.dict2df(df_dict2, fname, save=save, update=update,
- csv=csv, xlsx=xlsx, check_datatypes=False)
+ csv=csv, xlsx=xlsx, check_datatypes=False,
+ complib=self.complib)
return dfs
@@ -4548,18 +4591,18 @@ class Cases(object):
print('updating statistics: %s ...' % (post_dir + sim_id), end='')
try:
dfs.to_hdf('%s.h5' % fpath, 'table', mode='r+', append=True,
- format='table', complevel=9, complib='blosc')
+ format='table', complevel=9, complib=self.complib)
except IOError:
print('Can not update, file does not exist. Saving instead'
'...', end='')
dfs.to_hdf('%s.h5' % fpath, 'table', mode='w',
- format='table', complevel=9, complib='blosc')
+ format='table', complevel=9, complib=self.complib)
else:
print('saving statistics: %s ...' % (post_dir + sim_id), end='')
if csv:
dfs.to_csv('%s.csv' % fpath)
dfs.to_hdf('%s.h5' % fpath, 'table', mode='w',
- format='table', complevel=9, complib='blosc')
+ format='table', complevel=9, complib=self.complib)
print('DONE!!\n')
@@ -4765,7 +4808,8 @@ class Cases(object):
# make consistent data types, and convert to DataFrame
fname = os.path.join(post_dir, sim_id + '_Leq')
df_Leq = misc.dict2df(dict_Leq, fname, save=save, update=update,
- csv=csv, check_datatypes=True, xlsx=xlsx)
+ csv=csv, check_datatypes=True, xlsx=xlsx,
+ complib=self.complib)
# only keep the ones that do not have nan's (only works with index)
return df_Leq
@@ -4887,7 +4931,8 @@ class Cases(object):
# make consistent data types, and convert to DataFrame
fname = os.path.join(post_dir, sim_id + '_AEP')
df_AEP = misc.dict2df(dict_AEP, fname, update=update, csv=csv,
- save=save, check_datatypes=True, xlsx=xlsx)
+ save=save, check_datatypes=True, xlsx=xlsx,
+ complib=self.complib)
return df_AEP
@@ -5094,8 +5139,8 @@ class Cases(object):
def compute_envelope(self, sig, ch_list, int_env=False, Nx=300):
"""
- The function computes load envelopes for given signals and a single
- load case. Starting from Mx and My moments, the other cross-sectional
+ The function computes load envelopes for given signals and a single
+ load case. Starting from Mx and My moments, the other cross-sectional
forces are identified.
Parameters
@@ -5104,20 +5149,20 @@ class Cases(object):
sig : list, time-series signal
ch_list : list, list of channels for enevelope computation
-
+
int_env : boolean, default=False
- If the logic parameter is True, the function will interpolate the
+ If the logic parameter is True, the function will interpolate the
envelope on a given number of points
Nx : int, default=300
- Number of points for the envelope interpolation
-
+ Number of points for the envelope interpolation
+
Returns
-------
- envelope : dictionary,
+ envelope : dictionary,
The dictionary has entries refered to the channels selected.
- Inside the dictonary under each entry there is a matrix with 6
+ Inside the dictonary under each entry there is a matrix with 6
columns, each for the sectional forces and moments
"""
@@ -5135,13 +5180,13 @@ class Cases(object):
closed_contour = np.append(cloud[hull.vertices,:],
cloud[hull.vertices[0],:].reshape(1,2),
axis=0)
-
+
# Interpolate envelope for a given number of points
if int_env:
_,_,_,closed_contour_int = int_envelope(closed_contour[:,0],
- closed_contour[:,1],Nx)
-
-
+ closed_contour[:,1],Nx)
+
+
# Based on Mx and My envelope, the other cross-sectional moments
# and forces components are identified and appended to the initial
# envelope
@@ -5154,16 +5199,16 @@ class Cases(object):
if int_env:
_,_,_,extra_sensor = int_envelope(closed_contour[:,0],
closed_contour[:,ich],Nx)
- es = np.atleast_2d(np.array(extra_sensor[:,1])).T
+ es = np.atleast_2d(np.array(extra_sensor[:,1])).T
closed_contour_int = np.append(closed_contour_int,es,axis=1)
if int_env:
envelope[ch[0]] = closed_contour_int
else:
envelope[ch[0]] = closed_contour
-
+
return envelope
-
+
def int_envelope(ch1,ch2,Nx):
# Function to interpolate envelopes and output arrays of same length
diff --git a/wetb/prepost/dlcdefs.py b/wetb/prepost/dlcdefs.py
index e7ef0a6a43b75347d75473d136007016c6f3032c..df704758291dded2e75773f9b6c47a709e473113 100644
--- a/wetb/prepost/dlcdefs.py
+++ b/wetb/prepost/dlcdefs.py
@@ -240,8 +240,8 @@ def tags_defaults(master):
return master
-def excel_stabcon(proot, fext='xlsx', pignore=None, sheet=0,
- pinclude=None, silent=False):
+def excel_stabcon(proot, fext='xlsx', pignore=None, pinclude=None, sheet=0,
+ silent=False):
"""
Read all MS Excel files that hold load case definitions according to
the team STABCON definitions. Save each case in a list according to the
@@ -251,6 +251,9 @@ def excel_stabcon(proot, fext='xlsx', pignore=None, sheet=0,
are added to be compatible with the tag convention in the Simulations
module.
+ The opt_tags case list is sorted according to the Excel file names, and
+ follows the same ordering as in each of the different Excel files.
+
Parameters
----------
@@ -272,25 +275,32 @@ def excel_stabcon(proot, fext='xlsx', pignore=None, sheet=0,
Name or index of the Excel sheet to be considered. By default, the
first sheet (index=0) is taken.
+ Returns
+ -------
+
+ opt_tags : list of dicts
+ A list of case dictionaries, where each case dictionary holds all
+ the tag/value key pairs for a single given case.
+
"""
if not silent:
print('looking for DLC spreadsheet definitions at:')
print(proot)
- df_list = misc.read_excel_files(proot, fext=fext, pignore=pignore,
+ dict_dfs = misc.read_excel_files(proot, fext=fext, pignore=pignore,
sheet=sheet, pinclude=pinclude,
silent=silent)
if not silent:
- print('found %i Excel file(s), ' % len(df_list), end='')
+ print('found %i Excel file(s), ' % len(dict_dfs), end='')
k = 0
- for df in df_list:
+ for df in dict_dfs:
k += len(df)
if not silent:
print('in which a total of %s cases are defined.' % k)
opt_tags = []
- for (dlc, df) in viewitems(df_list):
+ for (dlc, df) in sorted(viewitems(dict_dfs)):
# replace ';' with False, and Nan(='') with True
# this is more easy when testing for the presence of stuff compared
# to checking if a value is either True/False or ''/';'
diff --git a/wetb/prepost/h2_vs_hs2.py b/wetb/prepost/h2_vs_hs2.py
index 5dcc64cff5759a0958a0228027b283840f5617bc..5f69fcaced878660ce6177333171c071446d5338 100644
--- a/wetb/prepost/h2_vs_hs2.py
+++ b/wetb/prepost/h2_vs_hs2.py
@@ -459,7 +459,7 @@ class Sims(object):
return tune_tags
- def post_processing(self, statistics=True, resdir=None,
+ def post_processing(self, statistics=True, resdir=None, complib='blosc',
calc_mech_power=False):
"""
Parameters
@@ -478,7 +478,7 @@ class Sims(object):
# logfile analysis is written to a csv file in logfiles directory
# =========================================================================
# load the file saved in post_dir
- cc = sim.Cases(post_dir, self.sim_id, rem_failed=False)
+ cc = sim.Cases(post_dir, self.sim_id, rem_failed=False, complib=complib)
if resdir is None:
# we keep the run_dir as defined during launch
@@ -771,6 +771,29 @@ class MappingsH2HS2(object):
def _body_structure_modes_hs(self, fname):
self.body_freq_hs = hs2.results().load_cmb_df(fname)
+ def save(self, fpath, fname_prefix):
+ """Save all the HAWC2 mappings created to fixed width text files
+ similar to HAWCStab2.
+ """
+
+ fname = '%shawc2_ss_mean_power_curve.txt' % fname_prefix
+ tmp = self.pwr_h2_mean.copy()
+ tmp.set_index('windspeed', inplace=True)
+ tmp.index.name = 'windspeed'
+ header = ''.join(['%16s' % k for k in self.pwr_h2_mean.columns])
+ header = ' windspeed' + header
+ np.savetxt(os.path.join(fpath, fname), tmp.to_records(), header=header,
+ fmt='% 01.06e ')
+
+ fname = '%shawc2_ss_std_power_curve.txt' % fname_prefix
+ tmp = self.pwr_h2_mean.copy()
+ tmp.set_index('windspeed', inplace=True)
+ tmp.index.name = 'windspeed'
+ header = ''.join(['%16s' % k for k in self.pwr_h2_mean.columns])
+ header = ' windspeed' + header
+ np.savetxt(os.path.join(fpath, fname), tmp.to_records(), header=header,
+ fmt='% 01.06e ')
+
class Plots(object):
"""
diff --git a/wetb/prepost/misc.py b/wetb/prepost/misc.py
index 73aca12551262ff28b8124ab3f3d6deb5f8a3032..b0bd74982c05a716bea95f61a6c49a122b8ef956 100644
--- a/wetb/prepost/misc.py
+++ b/wetb/prepost/misc.py
@@ -716,10 +716,9 @@ def read_excel_files(proot, fext='xlsx', pignore=None, sheet=0,
Returns
-------
- df_list : list
- A list of pandas DataFrames. Each DataFrame corresponds to the
- contents of a single Excel file that was found in proot or one of
- its sub-directories
+ df_list : dictionary
+ A dictionary with the Excel file name (excluding 'fext') as key, and
+ the corresponding pandas DataFrame as value.
"""
@@ -1025,7 +1024,8 @@ def df_dict_check_datatypes(df_dict):
def dict2df(df_dict, fname, save=True, update=False, csv=False, colsort=None,
- check_datatypes=False, rowsort=None, csv_index=False, xlsx=False):
+ check_datatypes=False, rowsort=None, csv_index=False, xlsx=False,
+ complib='blosc'):
"""
Convert the df_dict to df and save/update if required. If converting
to df fails, pickle the object. Optionally save as csv too.
@@ -1089,12 +1089,12 @@ def dict2df(df_dict, fname, save=True, update=False, csv=False, colsort=None,
print('updating: %s ...' % (fname), end='')
try:
dfs.to_hdf('%s.h5' % fname, 'table', mode='r+', append=True,
- format='table', complevel=9, complib='blosc')
+ format='table', complevel=9, complib=complib)
except IOError:
print('Can not update, file does not exist. Saving instead'
'...', end='')
dfs.to_hdf('%s.h5' % fname, 'table', mode='w',
- format='table', complevel=9, complib='blosc')
+ format='table', complevel=9, complib=complib)
else:
print('saving: %s ...' % (fname), end='')
if csv:
@@ -1102,7 +1102,7 @@ def dict2df(df_dict, fname, save=True, update=False, csv=False, colsort=None,
if xlsx:
dfs.to_excel('%s.xlsx' % fname, index=csv_index)
dfs.to_hdf('%s.h5' % fname, 'table', mode='w',
- format='table', complevel=9, complib='blosc')
+ format='table', complevel=9, complib=complib)
print('DONE!!\n')
diff --git a/wetb/prepost/windIO.py b/wetb/prepost/windIO.py
index 170e6e1d8f943ec3fa02b87556b3cb3774b65774..589a8c4e6c1854801a6ac04ba8b1b7aac4c233fa 100755
--- a/wetb/prepost/windIO.py
+++ b/wetb/prepost/windIO.py
@@ -901,21 +901,33 @@ class LoadResults(ReadHawc2):
def ReadOutputAtTime(fname):
"""Distributed blade loading as generated by the HAWC2 output_at_time
- command.
+ command. From HAWC2 12.3-beta and onwards, there are 7 header columns,
+ earlier version only have 3.
+
+ Parameters
+ ----------
+
+ fname : str
+
+ header_lnr : int, default=3
+ Line number of the header (column names) (1-based counting).
"""
+# data = pd.read_fwf(fname, skiprows=3, header=None)
+# pd.read_table(fname, sep=' ', skiprows=3)
+# data.index.names = cols
+
# because the formatting is really weird, we need to sanatize it a bit
with opent(fname, 'r') as f:
# read the header from line 3
- f.readline()
- f.readline()
- header = f.readline().replace('\r', '').replace('\n', '')
+ for k in range(7):
+ line = f.readline()
+ if line[0:12].lower().replace('#', '').strip() == 'radius_s':
+ header_lnr = k + 1
+ break
+ header = line.replace('\r', '').replace('\n', '')
cols = [k.strip().replace(' ', '_') for k in header.split('#')[1:]]
-# data = pd.read_fwf(fname, skiprows=3, header=None)
-# pd.read_table(fname, sep=' ', skiprows=3)
-# data.index.names = cols
-
- data = np.loadtxt(fname, skiprows=3)
+ data = np.loadtxt(fname, skiprows=header_lnr)
return pd.DataFrame(data, columns=cols)