12283078613

Committed 11 Dec 2024 06:59PM UTC coverage: 78.249% (-0.6%) from 78.802%

Build # 12283078613

Build Type

Pull #308

github

Committed by

dzalkind

Commit Message

Merge remote-tracking branch 'origin/DLC_RefactorCaseInputs' into DLC_RefactorCaseInputs

Pull Request Pull Request #308: DLC Generation - Refactor and New Cases

Run Details

446 of 665 new or added lines in 9 files covered. (67.07%)

3 existing lines in 3 files now uncovered.

21416 of 27369 relevant lines covered (78.25%)

0.78 hits per line

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84.17

/weis/aeroelasticse/CaseGen_General.py

import os, itertools
import numpy as np
from weis.aeroelasticse.FileTools import save_yaml

def save_case_matrix(matrix_out, change_vars, dir_matrix, filename_ext=''):
    # save matrix file
    if type(change_vars[0]) is tuple:
        n_header_lines = len(change_vars[0])
    else:
        change_vars = [(var,) for var in change_vars]
        n_header_lines = 1

    n_cases = np.shape(matrix_out)[0]
    matrix_out = np.hstack((np.asarray([[i] for i in range(n_cases)]), matrix_out))

    change_vars = [('Case_ID',)+('',)*(n_header_lines-1)] + change_vars
    # col_len = [max([len(val) for val in matrix_out[:,j]] + [len(change_vars[j][0]), len(change_vars[j][1])]) for j in range(len(change_vars))]
    col_len = [max([len(str(val)) for val in matrix_out[:,j]] + [len(change_vars[j][header_i]) for header_i in range(n_header_lines)]) for j in range(len(change_vars))]

    text_out = []
    for header_i in range(n_header_lines):
        text_out.append(''.join([val.center(col+2) for val, col in zip([var[header_i] for var in change_vars], col_len)])+'\n')

    for row in matrix_out:
        row_str = ''
        for val, col in zip(row, col_len):
            if val is not str:
                val = str(val)
            row_str += val.center(col+2)
        row_str += '\n'
        text_out.append(row_str)

    if not os.path.exists(dir_matrix):
        os.makedirs(dir_matrix)
    ofh = open(os.path.join(dir_matrix,f'case_matrix{filename_ext}.txt'),'w')
    for row in text_out:
        ofh.write(row)
    ofh.close()

def save_case_matrix_yaml(matrix_out, change_vars, dir_matrix, case_names, filename_ext=''):

    matrix_out_yaml = {}
    for var in change_vars:
        matrix_out_yaml[var] = []
    matrix_out_yaml['Case_ID'] = []
    matrix_out_yaml['Case_Name'] = []

    for i, row in enumerate(matrix_out):
        matrix_out_yaml['Case_ID'].append(i)
        matrix_out_yaml['Case_Name'].append(case_names[i])
        for val, var in zip(row, change_vars):
            if type(val) is list:
                if len(val) == 1:
                    val = val[0]
            if type(val) in [np.float32, np.float64, np.single, np.double, np.longdouble]:
                val = float(val)
            elif type(val) in [np.int8, np.int16, np.int32, np.int64, np.uint8, np.uint16, np.uint32, np.uint64, np.intc, np.uintc, np.uint]:
                val = int(val)
            elif type(val) in [np.array, np.ndarray]:
                val = val.tolist()
            elif type(val) in [np.str_]:
                val = str(val)
            # elif len(val) > 0:
            #     val = val.tolist()
            matrix_out_yaml[var].append(val)

    if not os.path.exists(dir_matrix):
        os.makedirs(dir_matrix)

    save_yaml(dir_matrix, f'case_matrix{filename_ext}.yaml', matrix_out_yaml)

def case_naming(n_cases, namebase=None):
    # case naming
    case_name = [('%d'%i).zfill(len('%d'%(n_cases-1))) for i in range(n_cases)]
    if namebase:
        case_name = [namebase+'_'+caseid for caseid in case_name]

    return case_name

def convert_str(val):
    def try_type(val, data_type):
        try:
            data_type(val)
            return True
        except:
            return False
#        return isinstance(val, data_type)  ### this doesn't work b/c of numpy data types; they're not instances of base types
    def try_list(val):
        try:
            val[0]
            return True
        except:
            return False

    if try_type(val, int) and int(val) == float(val):
        return int(val)
    elif try_type(val, float):
        return float(val)
    elif val=='True':
        return True
    elif val=='False':
        return False
    elif try_type(val,str):
        return str(val)
    # elif type(val)!=str and try_list(val):
    #     return ", ".join(['{:}'.format(i) for i in val])
    else:
        return val

def CaseGen_General(case_inputs, dir_matrix='', namebase='', save_matrix=True, filename_ext=''):
    """ Cartesian product to enumerate over all combinations of set of variables that are changed together"""

    # put case dict into lists
    change_vars = sorted(case_inputs.keys())
    change_vals = [case_inputs[var]['vals'] for var in change_vars]
    change_group = [case_inputs[var]['group'] for var in change_vars]

    # find number of groups and length of groups
    group_set = list(set(change_group))
    group_len = [len(change_vals[change_group.index(i)]) for i in group_set]

    # case matrix, as indices
    group_idx = [range(n) for n in group_len]
    matrix_idx = list(itertools.product(*group_idx))

    # index of each group
    matrix_group_idx = [np.where([group_i == group_j for group_j in change_group])[0].tolist() for group_i in group_set]

    # build final matrix of variable values
    matrix_out = []
    for i, row in enumerate(matrix_idx):
        row_out = [None]*len(change_vars)
        for j, val in enumerate(row):
            for g in matrix_group_idx[j]:
                row_out[g] = change_vals[g][val]
        matrix_out.append(row_out)
    try:
        matrix_out = np.asarray(matrix_out, dtype=str)
    except:
        matrix_out = np.asarray(matrix_out)
    n_cases = np.shape(matrix_out)[0]

    # case naming
    case_name = case_naming(n_cases, namebase=namebase)
    
    # Save case matrix
    if save_matrix:
        if not dir_matrix:
            dir_matrix = os.getcwd()
        try:
            save_case_matrix(matrix_out, change_vars, dir_matrix, filename_ext=filename_ext)
            save_case_matrix_yaml(matrix_out, change_vars, dir_matrix, case_name, filename_ext=filename_ext)
        except: 
            save_case_matrix_yaml(matrix_out, change_vars, dir_matrix, case_name, filename_ext=filename_ext)

    case_list = []
    for i in range(n_cases):
        case_list_i = {}
        for j, var in enumerate(change_vars):
            case_list_i[var] = convert_str(matrix_out[i,j])
        case_list.append(case_list_i)


    return case_list, case_name

1	import os, itertools	1✔
2	import numpy as np	1✔
3	from weis.aeroelasticse.FileTools import save_yaml	1✔
4
5	def save_case_matrix(matrix_out, change_vars, dir_matrix, filename_ext=''):	1✔
6	# save matrix file
7	if type(change_vars[0]) is tuple:	1✔
8	n_header_lines = len(change_vars[0])	1✔
9	else:
10	change_vars = [(var,) for var in change_vars]	×
11	n_header_lines = 1	×
12
13	n_cases = np.shape(matrix_out)[0]	1✔
14	matrix_out = np.hstack((np.asarray([[i] for i in range(n_cases)]), matrix_out))	1✔
15
16	change_vars = [('Case_ID',)+('',)*(n_header_lines-1)] + change_vars	1✔
17	# col_len = [max([len(val) for val in matrix_out[:,j]] + [len(change_vars[j][0]), len(change_vars[j][1])]) for j in range(len(change_vars))]
18	col_len = [max([len(str(val)) for val in matrix_out[:,j]] + [len(change_vars[j][header_i]) for header_i in range(n_header_lines)]) for j in range(len(change_vars))]	1✔
19
20	text_out = []	1✔
21	for header_i in range(n_header_lines):	1✔
22	text_out.append(''.join([val.center(col+2) for val, col in zip([var[header_i] for var in change_vars], col_len)])+'\n')	1✔
23
24	for row in matrix_out:	1✔
25	row_str = ''	1✔
26	for val, col in zip(row, col_len):	1✔
27	if val is not str:	1✔
28	val = str(val)	1✔
29	row_str += val.center(col+2)	1✔
30	row_str += '\n'	1✔
31	text_out.append(row_str)	1✔
32
33	if not os.path.exists(dir_matrix):	1✔
34	os.makedirs(dir_matrix)	1✔
35	ofh = open(os.path.join(dir_matrix,f'case_matrix{filename_ext}.txt'),'w')	1✔
36	for row in text_out:	1✔
37	ofh.write(row)	1✔
38	ofh.close()	1✔
39
40	def save_case_matrix_yaml(matrix_out, change_vars, dir_matrix, case_names, filename_ext=''):	1✔
41
42	matrix_out_yaml = {}	1✔
43	for var in change_vars:	1✔
44	matrix_out_yaml[var] = []	1✔
45	matrix_out_yaml['Case_ID'] = []	1✔
46	matrix_out_yaml['Case_Name'] = []	1✔
47
48	for i, row in enumerate(matrix_out):	1✔
49	matrix_out_yaml['Case_ID'].append(i)	1✔
50	matrix_out_yaml['Case_Name'].append(case_names[i])	1✔
51	for val, var in zip(row, change_vars):	1✔
52	if type(val) is list:	1✔
53	if len(val) == 1:	×
54	val = val[0]	×
55	if type(val) in [np.float32, np.float64, np.single, np.double, np.longdouble]:	1✔
56	val = float(val)	×
57	elif type(val) in [np.int8, np.int16, np.int32, np.int64, np.uint8, np.uint16, np.uint32, np.uint64, np.intc, np.uintc, np.uint]:	1✔
58	val = int(val)	×
59	elif type(val) in [np.array, np.ndarray]:	1✔
60	val = val.tolist()	×
61	elif type(val) in [np.str_]:	1✔
62	val = str(val)	1✔
63	# elif len(val) > 0:
64	# val = val.tolist()
65	matrix_out_yaml[var].append(val)	1✔
66
67	if not os.path.exists(dir_matrix):	1✔
68	os.makedirs(dir_matrix)	×
69
70	save_yaml(dir_matrix, f'case_matrix{filename_ext}.yaml', matrix_out_yaml)	1✔
71
72	def case_naming(n_cases, namebase=None):	1✔
73	# case naming
74	case_name = [('%d'%i).zfill(len('%d'%(n_cases-1))) for i in range(n_cases)]	1✔
75	if namebase:	1✔
76	case_name = [namebase+'_'+caseid for caseid in case_name]	1✔
77
78	return case_name	1✔
79
80	def convert_str(val):	1✔
81	def try_type(val, data_type):	1✔
82	try:	1✔
83	data_type(val)	1✔
84	return True	1✔
85	except:	1✔
86	return False	1✔
87	# return isinstance(val, data_type) ### this doesn't work b/c of numpy data types; they're not instances of base types
88	def try_list(val):	1✔
89	try:	×
90	val[0]	×
91	return True	×
92	except:	×
93	return False	×
94
95	if try_type(val, int) and int(val) == float(val):	1✔
96	return int(val)	1✔
97	elif try_type(val, float):	1✔
98	return float(val)	1✔
99	elif val=='True':	1✔
100	return True	1✔
101	elif val=='False':	1✔
102	return False	1✔
103	elif try_type(val,str):	1✔
104	return str(val)	1✔
105	# elif type(val)!=str and try_list(val):
106	# return ", ".join(['{:}'.format(i) for i in val])
107	else:
UNCOV 108	return val	×
109
110	def CaseGen_General(case_inputs, dir_matrix='', namebase='', save_matrix=True, filename_ext=''):	1✔
111	""" Cartesian product to enumerate over all combinations of set of variables that are changed together"""
112
113	# put case dict into lists
114	change_vars = sorted(case_inputs.keys())	1✔
115	change_vals = [case_inputs[var]['vals'] for var in change_vars]	1✔
116	change_group = [case_inputs[var]['group'] for var in change_vars]	1✔
117
118	# find number of groups and length of groups
119	group_set = list(set(change_group))	1✔
120	group_len = [len(change_vals[change_group.index(i)]) for i in group_set]	1✔
121
122	# case matrix, as indices
123	group_idx = [range(n) for n in group_len]	1✔
124	matrix_idx = list(itertools.product(*group_idx))	1✔
125
126	# index of each group
127	matrix_group_idx = [np.where([group_i == group_j for group_j in change_group])[0].tolist() for group_i in group_set]	1✔
128
129	# build final matrix of variable values
130	matrix_out = []	1✔
131	for i, row in enumerate(matrix_idx):	1✔
132	row_out = [None]*len(change_vars)	1✔
133	for j, val in enumerate(row):	1✔
134	for g in matrix_group_idx[j]:	1✔
135	row_out[g] = change_vals[g][val]	1✔
136	matrix_out.append(row_out)	1✔
137	try:	1✔
138	matrix_out = np.asarray(matrix_out, dtype=str)	1✔
139	except:	×
140	matrix_out = np.asarray(matrix_out)	×
141	n_cases = np.shape(matrix_out)[0]	1✔
142
143	# case naming
144	case_name = case_naming(n_cases, namebase=namebase)	1✔
145
146	# Save case matrix
147	if save_matrix:	1✔
148	if not dir_matrix:	1✔
149	dir_matrix = os.getcwd()	×
150	try:	1✔
151	save_case_matrix(matrix_out, change_vars, dir_matrix, filename_ext=filename_ext)	1✔
152	save_case_matrix_yaml(matrix_out, change_vars, dir_matrix, case_name, filename_ext=filename_ext)	1✔
153	except:	×
NEW 154	save_case_matrix_yaml(matrix_out, change_vars, dir_matrix, case_name, filename_ext=filename_ext)	×
155
156	case_list = []	1✔
157	for i in range(n_cases):	1✔
158	case_list_i = {}	1✔
159	for j, var in enumerate(change_vars):	1✔
160	case_list_i[var] = convert_str(matrix_out[i,j])	1✔
161	case_list.append(case_list_i)	1✔
162
163
164	return case_list, case_name	1✔

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