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Commit 97f79990 authored by David Verelst's avatar David Verelst
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Merge branch 'master' into 'master'

New module to create automatically the DLB spreadsheets starting from one file.

I've created a module to write the DLB spreadsheets starting from a single file that defines all the cases. It comes handy when a new DLB is required, e.g. for a new wind class.
It is based on the tags approach.
I am not pushing the master excel sheets therefore it is not possible to test it without it..


See merge request !3
parents 0c04022e a94b26c6
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Pipeline #
# -*- coding: utf-8 -*-
"""
Created on Fri Nov 20 10:11:06 2015
@author: tlbl
"""
from __future__ import print_function
from __future__ import division
from __future__ import unicode_literals
from __future__ import absolute_import
# arctan and pi are required because they are in the formulas that are
# evaluated
from numpy import floor, arctan, pi
import pandas as pd
import xlrd
def multi_for(iterables):
"""
Routine to create list with combination of elements.
"""
if not iterables:
yield ()
else:
for item in iterables[0]:
for rest_tuple in multi_for(iterables[1:]):
yield (item,) + rest_tuple
class GeneralDLC(object):
"""
Basic class to generate the DLC spreadsheets. It contains routines to
handle the different types of tags.
* Constants: are fixed in the current DLC, e.g. reference turbulence\
intensity, rotor radius, reference wind speed, ....
* Variables: define the number of cases in a DLC through their combination\
e.g. wind speed, number of turbulence seeds, yaw angle, ....
* Functions: depend on other tags e.g turbulence intensity, file name, ....
"""
def __init__(self):
pass
def remove_from_dict(self, non_defaults, defaults):
for key in non_defaults.keys():
try:
del defaults[key]
except:
pass
return defaults
def add_variables_tag(self, dlc, variables, variables_order):
cases_len = []
for tag in variables_order:
dlc[tag] = []
v = variables[tag]
for i in range(len(v)-1):
try:
v.remove('')
except:
pass
if tag == '[seed]':
cases_len.append(int(v[0]))
else:
cases_len.append(len(v))
cases_index = multi_for(list(map(range, cases_len)))
for irow, row in enumerate(cases_index):
counter = floor(irow/len(variables['[wsp]']))+1
for icol, col in enumerate(row):
if variables_order[icol] == '[seed]':
value = '%4.4i' % (1000*counter + row[variables_order.index('[wsp]')]+1)
else:
value = variables[variables_order[icol]][col]
if not isinstance(value, float) and not isinstance(value, int):
value = str(value)
dlc[variables_order[icol]].append(value)
def add_constants_tag(self, dlc, constants):
for key in constants.keys():
dlc[key] = [constants[key]]*len(dlc['[wsp]'])
def sort_formulas(self, formulas):
# sort formulas based on their dependency
keys_list = sorted(formulas)
for i in range(len(keys_list)):
for ikey, key in enumerate(keys_list):
formula = formulas[key]
for ikey2, key2 in enumerate(keys_list):
if key2 in formula:
if ikey < ikey2:
keys_list.pop(ikey)
keys_list.insert(ikey2, key)
break
return keys_list
def eval_formulas(self, dlc):
for key in dlc.keys():
if isinstance(dlc[key][0], str):
if "[" in dlc[key][0]:
for key2 in dlc.keys():
for iformula, formula in enumerate(dlc[key]):
if key2 in formula:
dlc[key][iformula] = dlc[key][iformula].replace(key2, '%s'%dlc[key2][iformula])
for iformula, formula in enumerate(dlc[key]):
formula = formula.replace(',', '.')
formula = formula.replace(';', ',')
dlc[key][iformula] = eval(formula)
def add_formulas(self, dlc, formulas):
keys_list = self.sort_formulas(formulas)
for fkey in keys_list:
flist = []
for i in range(len(dlc['[wsp]'])):
formula = formulas[fkey]
for key in dlc.keys():
if key in formula:
if formula[0] == '"':
if key == '[wsp]' or key == '[gridgustdelay]':
fmt = '%2.2i'
elif key == '[wdir]' or key == '[G_phi0]':
fmt = '%3.3i'
else:
fmt = '%4.4i'
formula = formula.replace(key, fmt % int(dlc[key][i]))
elif key in formula:
formula = formula.replace(key, '%s' % dlc[key][i])
formula = formula.replace(',', '.')
formula = formula.replace(';', ',')
flist.append(eval(formula))
dlc[fkey] = flist
class GenerateDLCCases(GeneralDLC):
"""
Class to generate Excell sheets for each DLB case starting from a single
Excell sheet.
Parameters
----------
filename: str
Name of the excel spreadsheet containing the definition of all the
cases to generate.
folder: str
Name of the folder in which to save the DLB cases.
Example
-------
DLB = GenerateDLCCases()
DLB.execute()
"""
def execute(self, filename='DLCs.xlsx', folder=''):
book = xlrd.open_workbook(filename)
nsheets = book.nsheets
# Loop through all the sheets. Each sheet correspond to a DLC.
for isheet in range(1, nsheets):
# Read all the initialization constants and functions in the
# first sheet
general_constants = {}
general_functions = {}
sheet = book.sheets()[0]
for i in range(1, sheet.ncols):
if sheet.cell_value(9, i) != '':
general_constants[str(sheet.cell_value(9, i))] = \
sheet.cell_value(10, i)
if sheet.cell_value(13, i) != '':
general_functions[str(sheet.cell_value(13, i))] = \
sheet.cell_value(14, i)
sheet = book.sheets()[isheet]
print('Sheet #%i' % isheet, sheet.name)
# Read the actual sheet.
constants = {}
variables = {}
formulas = {}
variables_order = []
# Loop through the columns
for i in range(sheet.ncols):
if sheet.cell_value(1, i) is not None:
tag = str(sheet.cell_value(1, i))
if tag is not '':
if sheet.cell_value(0, i) == 'C':
constants[tag] = sheet.cell_value(2, i)
if sheet.cell_value(0, i) == 'V':
variables_order.append(tag)
variables[tag] = \
[sheet.cell_value(j, i) for j in range(2, sheet.nrows)]
if sheet.cell_value(0, i) == 'F':
formulas[tag] = str(sheet.cell_value(2, i))
dlc = {}
general_constants = self.remove_from_dict(variables,
general_constants)
general_constants = self.remove_from_dict(constants,
general_constants)
general_functions = self.remove_from_dict(formulas,
general_functions)
self.add_variables_tag(dlc, variables, variables_order)
self.add_constants_tag(dlc, general_constants)
self.add_constants_tag(dlc, constants)
self.add_formulas(dlc, formulas)
self.add_formulas(dlc, general_functions)
self.eval_formulas(dlc)
df = pd.DataFrame(dlc)
df.to_excel(folder+sheet.name+'.xls', index=False)
class RunTest():
"""
Class to perform basic testing of the GenerateDLCCases class. It writes the
spreadsheets and compare them with a reference set.
"""
def execute(self):
from pandas.util.testing import assert_frame_equal
a = GenerateDLCCases()
a.execute()
book = xlrd.open_workbook('DLCs.xlsx')
nsheets = book.nsheets
for isheet in range(1, nsheets):
sheet = book.sheets()[isheet]
print('Sheet #%i' % isheet, sheet.name)
book1 = pd.read_excel('Reference/'+sheet.name+'.xlsx')
book2 = pd.read_excel(sheet.name+'.xls')
book2 = book2[book1.columns]
assert_frame_equal(book1, book2, check_dtype=False)
if __name__ == '__main__':
DLB = GenerateDLCCases()
DLB.execute()
pass
......@@ -320,8 +320,10 @@ def excel_stabcon(proot, fext='xlsx', pignore=None, sheet=0,
tags_dict['[res_dir]'] = 'res/%s/' % dlc_case
tags_dict['[log_dir]'] = 'logfiles/%s/' % dlc_case
tags_dict['[htc_dir]'] = 'htc/%s/' % dlc_case
tags_dict['[case_id]'] = tags_dict['[Case id.]']
tags_dict['[time_stop]'] = tags_dict['[time stop]']
if '[Case id.]' in tags_dict.keys():
tags_dict['[case_id]'] = tags_dict['[Case id.]']
if '[time stop]' in tags_dict.keys():
tags_dict['[time_stop]'] = tags_dict['[time stop]']
try:
tags_dict['[turb_base_name]'] = tags_dict['[Turb base name]']
except KeyError:
......
......@@ -1013,19 +1013,34 @@ class LoadResults(object):
# TODO: general signal method, this is not HAWC2 specific, move out
def calc_fatigue(self, signal, no_bins=46, m=[3, 4, 6, 8, 10, 12], neq=1):
"""
signal is 1D
Parameters
----------
signal: 1D array
One dimentional array containing the signal.
no_bins: int
Number of bins for the binning of the amplitudes.
m: list
Values of the slope of the SN curve.
neq: int
Number of equivalent cycles
Returns
-------
eq: list
Damage equivalent loads for each m value.
"""
try:
sig_rf = rainflow_astm(signal)
except:
except (TypeError) as e:
print(e)
return []
if len(sig_rf) < 1 and not sig_rf:
return []
hist_data, x, bin_avg = rfc_hist(sig_rf, no_bins)
m = np.atleast_1d(m)
eq = []
......
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