From beefb4d74a3badb6a830a4ce8e7fe861d0e8660d Mon Sep 17 00:00:00 2001
From: dave <dave@dtu.dk>
Date: Thu, 18 Feb 2016 10:01:24 +0100
Subject: [PATCH] prepost: turb base names default to None, add xlsx as
optional format to save statistics in
---
wetb/prepost/Simulations.py | 73 ++++++++++++++++++++++++-------------
wetb/prepost/dlcdefs.py | 6 ++-
wetb/prepost/misc.py | 4 +-
3 files changed, 55 insertions(+), 28 deletions(-)
diff --git a/wetb/prepost/Simulations.py b/wetb/prepost/Simulations.py
index d0c0a984..5ad8ee7a 100755
--- a/wetb/prepost/Simulations.py
+++ b/wetb/prepost/Simulations.py
@@ -1314,9 +1314,9 @@ class HtcMaster(object):
self.tags['[mooring_dir]'] = 'mooring/'
self.tags['[hydro_dir]'] = 'htc_hydro/'
self.tags['[pbs_out_dir]'] = 'pbs_out/'
- self.tags['[turb_base_name]'] = 'turb_'
- self.tags['[wake_base_name]'] = 'turb_'
- self.tags['[meand_base_name]'] = 'turb_'
+ self.tags['[turb_base_name]'] = None
+ self.tags['[wake_base_name]'] = None
+ self.tags['[meand_base_name]'] = None
self.tags['[zip_root_files]'] = []
self.tags['[fname_source]'] = []
@@ -1332,9 +1332,9 @@ class HtcMaster(object):
# self.queue = Queue.Queue()
- self.output_dirs = ['[res_dir]', '[log_dir]', '[turb_base_name]',
- '[case_id]', '[wake_base_name]', '[animation_dir]',
- '[meand_base_name]', '[eigenfreq_dir]']
+ self.output_dirs = ['[res_dir]', '[log_dir]', '[turb_dir]',
+ '[case_id]', '[wake_dir]', '[animation_dir]',
+ '[meand_dir]', '[eigenfreq_dir]']
def create_run_dir(self):
"""
@@ -2125,26 +2125,42 @@ class PBS(object):
# if there is a turbulence file data base dir, copy from there
if self.TurbDb:
- tmp = (self.TurbDb, self.turb_base_name, self.TurbDirName)
- self.pbs += "cp -R $PBS_O_WORKDIR/%s%s*.bin %s \n" % tmp
+ turb_dir_src = os.path.join('$PBS_O_WORKDIR', self.TurbDb)
else:
- # turbulence files basenames are defined for the case
- self.pbs += "cp -R $PBS_O_WORKDIR/" + self.TurbDirName + \
- self.turb_base_name + "*.bin ./"+self.TurbDirName + '\n'
+ turb_dir_src = os.path.join('$PBS_O_WORKDIR', self.TurbDirName)
+
+ # the original behaviour makes assumptions on the turbulence box
+ # names: turb_base_name_xxx_u.bin, turb_base_name_xxx_v.bin
+ if self.turb_base_name is not None:
+ turb_src = os.path.join(turb_dir_src, self.turb_base_name)
+ self.pbs += "cp -R %s*.bin %s \n" % (turb_src, self.TurbDirName)
+ # more generally, literally define the names of the boxes for u,v,w
+ # components
+ elif '[turb_fname_u]' in tag_dict:
+ turb_u = os.path.join(turb_dir_src, tag_dict['[turb_fname_u]'])
+ turb_v = os.path.join(turb_dir_src, tag_dict['[turb_fname_v]'])
+ turb_w = os.path.join(turb_dir_src, tag_dict['[turb_fname_w]'])
+ self.pbs += "cp %s %s \n" % (turb_u, self.TurbDirName)
+ self.pbs += "cp %s %s \n" % (turb_v, self.TurbDirName)
+ self.pbs += "cp %s %s \n" % (turb_w, self.TurbDirName)
+ # if there is a turbulence file data base dir, copy from there
if self.wakeDb and self.WakeDirName:
- tmp = (self.wakeDb, self.wake_base_name, self.WakeDirName)
- self.pbs += "cp -R $PBS_O_WORKDIR/%s%s*.bin %s \n" % tmp
+ wake_dir_src = os.path.join('$PBS_O_WORKDIR', self.wakeDb)
elif self.WakeDirName:
- self.pbs += "cp -R $PBS_O_WORKDIR/" + self.WakeDirName + \
- self.wake_base_name + "*.bin ./"+self.WakeDirName + '\n'
+ wake_dir_src = os.path.join('$PBS_O_WORKDIR', self.WakeDirName)
+ if self.wake_base_name is not None:
+ wake_src = os.path.join(wake_dir_src, self.wake_base_name)
+ self.pbs += "cp -R %s*.bin %s \n" % (wake_src, self.WakeDirName)
+ # if there is a turbulence file data base dir, copy from there
if self.meandDb and self.MeanderDirName:
- tmp = (self.meandDb, self.meand_base_name, self.MeanderDirName)
- self.pbs += "cp -R $PBS_O_WORKDIR/%s%s*.bin %s \n" % tmp
+ meand_dir_src = os.path.join('$PBS_O_WORKDIR', self.meandDb)
elif self.MeanderDirName:
- self.pbs += "cp -R $PBS_O_WORKDIR/" + self.MeanderDirName + \
- self.meand_base_name + "*.bin ./"+self.MeanderDirName + '\n'
+ meand_dir_src = os.path.join('$PBS_O_WORKDIR', self.MeanderDirName)
+ if self.meand_base_name is not None:
+ meand_src = os.path.join(meand_dir_src, self.meand_base_name)
+ self.pbs += "cp -R %s*.bin %s \n" % (meand_src, self.MeanderDirName)
# copy and rename input files with given versioned name to the
# required non unique generic version
@@ -3811,7 +3827,7 @@ class Cases(object):
ch_fatigue={}, update=False, add_sensor=None,
chs_resultant=[], i0=0, i1=-1, saveinterval=1000,
csv=True, suffix=None, fatigue_cycles=False, A=None,
- ch_wind=None, save_new_sigs=False):
+ ch_wind=None, save_new_sigs=False, xlsx=False):
"""
Calculate statistics and save them in a pandas dataframe. Save also
every 500 cases the statistics file.
@@ -3862,6 +3878,10 @@ class Cases(object):
csv : boolean, default=False
In addition to a h5 file, save the statistics also in csv format.
+ xlsx : boolean, default=False
+ In addition to a h5 file, save the statistics also in MS Excel xlsx
+ format.
+
Returns
-------
@@ -4250,7 +4270,7 @@ 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, check_datatypes=False)
+ csv=csv, xlsx=xlsx, check_datatypes=False)
df_dict2 = None
df_dict = None
@@ -4272,7 +4292,7 @@ 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, check_datatypes=False)
+ csv=csv, xlsx=xlsx, check_datatypes=False)
return dfs
@@ -4388,7 +4408,8 @@ class Cases(object):
def fatigue_lifetime(self, dfs, neq, res_dir='res/', fh_lst=None, years=20.,
dlc_folder="dlc%s_iec61400-1ed3/", extra_cols=[],
- save=False, update=False, csv=False, new_sim_id=False):
+ save=False, update=False, csv=False, new_sim_id=False,
+ xlsx=False):
"""
Cacluate the fatigue over a selection of cases and indicate how many
hours each case contributes to its life time.
@@ -4533,14 +4554,14 @@ 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)
+ csv=csv, check_datatypes=True, xlsx=xlsx)
# only keep the ones that do not have nan's (only works with index)
return df_Leq
def AEP(self, dfs, fh_lst=None, ch_powe=None, extra_cols=[], update=False,
res_dir='res/', dlc_folder="dlc%s_iec61400-1ed3/", csv=False,
- new_sim_id=False, save=False, years=20.0):
+ new_sim_id=False, save=False, years=20.0, xlsx=False):
"""
Calculate the Annual Energy Production (AEP) for DLC1.2 cases.
@@ -4655,7 +4676,7 @@ 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)
+ save=save, check_datatypes=True, xlsx=xlsx)
return df_AEP
diff --git a/wetb/prepost/dlcdefs.py b/wetb/prepost/dlcdefs.py
index 2d439c14..822b20e5 100644
--- a/wetb/prepost/dlcdefs.py
+++ b/wetb/prepost/dlcdefs.py
@@ -321,7 +321,11 @@ def excel_stabcon(proot, fext='xlsx', pignore=None, sheet=0,
tags_dict['[htc_dir]'] = 'htc/%s/' % dlc_case
tags_dict['[case_id]'] = tags_dict['[Case id.]']
tags_dict['[time_stop]'] = tags_dict['[time stop]']
- tags_dict['[turb_base_name]'] = tags_dict['[Turb base name]']
+ try:
+ tags_dict['[turb_base_name]'] = tags_dict['[Turb base name]']
+ except KeyError:
+ tags_dict['[turb_base_name]'] = None
+ tags_dict['[Turb base name]'] = None
tags_dict['[DLC]'] = tags_dict['[Case id.]'].split('_')[0][3:]
tags_dict['[pbs_out_dir]'] = 'pbs_out/%s/' % dlc_case
tags_dict['[pbs_in_dir]'] = 'pbs_in/%s/' % dlc_case
diff --git a/wetb/prepost/misc.py b/wetb/prepost/misc.py
index c7b3a067..441e20c1 100644
--- a/wetb/prepost/misc.py
+++ b/wetb/prepost/misc.py
@@ -1012,7 +1012,7 @@ 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):
+ check_datatypes=False, rowsort=None, csv_index=False, xlsx=False):
"""
Convert the df_dict to df and save/update if required. If converting
to df fails, pickle the object. Optionally save as csv too.
@@ -1086,6 +1086,8 @@ def dict2df(df_dict, fname, save=True, update=False, csv=False, colsort=None,
print('saving: %s ...' % (fname), end='')
if csv:
dfs.to_csv('%s.csv' % fname, index=csv_index)
+ 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')
--
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