Newer
Older
Start <- function(..., # dim = indices/selectors,
# dim_var = 'var',
# dim_reorder = Sort/CircularSort,
# dim_tolerance = number,
# dim_depends = 'file_dim',
# dim_across = 'file_dim',
return_vars = NULL,
file_opener = NcOpener,
file_var_reader = NcVarReader,
file_dim_reader = NcDimReader,
file_data_reader = NcDataReader,
file_closer = NcCloser,
transform = NULL,
transform_params = NULL,
transform_vars = NULL,
transform_extra_cells = 0,
apply_indices_after_transform = FALSE,
pattern_dims = NULL,
metadata_dims = NULL,
#, config_file = NULL
#dictionary_dim_names = ,
#dictionary_var_names =
dim_params <- list(...)
# Take *_var parameters apart
var_params_ind <- grep('_var$', names(dim_params))
var_params <- dim_params[var_params_ind]
# Check all *_var are NULL or vectors of character strings, and
# that they all have a matching dimension param.
i <- 1
for (var_param in var_params) {
if (!is.character(var_param)) {
stop("All '*_var' parameters must be character strings.")
} else if (!any(grepl(paste0('^', strsplit(names(var_params)[i],
'_var$')[[1]][1], '$'),
names(dim_params)))) {
stop(paste0("All '*_var' parameters must be associated to a dimension parameter. Found parameter '",
names(var_params)[i], "' but no parameter '",
strsplit(names(var_params)[i], '_var$')[[1]][1], "'."))
}
i <- i + 1
}
# Make the keys of 'var_params' to be the name of
# the corresponding dimension.
if (length(var_params) < 1) {
var_params <- NULL
} else {
names(var_params) <- gsub('_var$', '', names(var_params))
}
# Take *_reorder parameters apart
dim_reorder_params_ind <- grep('_reorder$', names(dim_params))
dim_reorder_params <- dim_params[dim_reorder_params_ind]
# Check all *_reorder are NULL or functions, and that they all have
# a matching dimension param.
i <- 1
for (dim_reorder_param in dim_reorder_params) {
if (!is.function(dim_reorder_param)) {
stop("All '*_reorder' parameters must be functions.")
} else if (!any(grepl(paste0('^', strsplit(names(dim_reorder_params)[i],
'_reorder$')[[1]][1], '$'),
names(dim_params)))) {
stop(paste0("All '*_reorder' parameters must be associated to a dimension parameter. Found parameter '",
names(dim_reorder_params)[i], "' but no parameter '",
strsplit(names(dim_reorder_params)[i], '_reorder$')[[1]][1], "'."))
} else if (!any(grepl(paste0('^', strsplit(names(dim_reorder_params)[i],
'_reorder$')[[1]][1], '$'),
names(var_params)))) {
stop(paste0("All '*_reorder' parameters must be associated to a dimension parameter associated to a ",
"variable. Found parameter '", names(dim_reorder_params)[i], "' and dimension parameter '",
strsplit(names(dim_reorder_params)[i], '_reorder$')[[1]][1], "' but did not find variable ",
"parameter '", strsplit(names(dim_reorder_params)[i], '_reorder$')[[1]][1], "_var'."))
}
i <- i + 1
}
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
# Make the keys of 'dim_reorder_params' to be the name of
# the corresponding dimension.
if (length(dim_reorder_params) < 1) {
dim_reorder_params <- NULL
} else {
names(dim_reorder_params) <- gsub('_reorder$', '', names(dim_reorder_params))
}
# Take *_tolerance parameters apart
tolerance_params_ind <- grep('_tolerance$', names(dim_params))
tolerance_params <- dim_params[tolerance_params_ind]
# Check all *_tolerance are NULL or vectors of character strings, and
# that they all have a matching dimension param.
i <- 1
for (tolerance_param in tolerance_params) {
if (!any(grepl(paste0('^', strsplit(names(tolerance_params)[i],
'_tolerance$')[[1]][1], '$'),
names(dim_params)))) {
stop(paste0("All '*_tolerance' parameters must be associated to a dimension parameter. Found parameter '",
names(tolerance_params)[i], "' but no parameter '",
strsplit(names(tolerance_params)[i], '_tolerance$')[[1]][1], "'."))
} else if (!any(grepl(paste0('^', strsplit(names(tolerance_params)[i],
'_tolerance$')[[1]][1], '$'),
names(var_params)))) {
stop(paste0("All '*_tolerance' parameters must be associated to a dimension parameter associated to a ",
"variable. Found parameter '", names(tolerance_params)[i], "' and dimension parameter '",
strsplit(names(tolerance_params)[i], '_tolerance$')[[1]][1], "' but did not find variable ",
"parameter '", strsplit(names(tolerance_params)[i], '_tolerance$')[[1]][1], "_var'."))
}
i <- i + 1
}
# Make the keys of 'tolerance_params' to be the name of
# the corresponding dimension.
if (length(tolerance_params) < 1) {
tolerance_params <- NULL
} else {
names(tolerance_params) <- gsub('_tolerance$', '', names(tolerance_params))
}
# Take *_depends parameters apart
depends_params_ind <- grep('_depends$', names(dim_params))
depends_params <- dim_params[depends_params_ind]
# Check all *_depends are NULL or vectors of character strings, and
# that they all have a matching dimension param.
i <- 1
for (depends_param in depends_params) {
if (!is.character(depends_param) || (length(depends_param) > 1)) {
stop("All '*_depends' parameters must be single character strings.")
} else if (!any(grepl(paste0('^', strsplit(names(depends_params)[i],
'_depends$')[[1]][1], '$'),
names(dim_params)))) {
stop(paste0("All '*_depends' parameters must be associated to a dimension parameter. Found parameter '",
names(depends_params)[i], "' but no parameter '",
strsplit(names(depends_params)[i], '_depends$')[[1]][1], "'."))
}
i <- i + 1
}
# Make the keys of 'depends_params' to be the name of
# the corresponding dimension.
if (length(depends_params) < 1) {
depends_params <- NULL
} else {
names(depends_params) <- gsub('_depends$', '', names(depends_params))
}
# Change name to depending_file_dims
depending_file_dims <- depends_params
# Take *_across parameters apart
across_params_ind <- grep('_across$', names(dim_params))
across_params <- dim_params[across_params_ind]
# Check all *_across are NULL or vectors of character strings, and
# that they all have a matching dimension param.
i <- 1
for (across_param in across_params) {
if (!is.character(across_param) || (length(across_param) > 1)) {
stop("All '*_across' parameters must be single character strings.")
} else if (!any(grepl(paste0('^', strsplit(names(across_params)[i],
'_across$')[[1]][1], '$'),
names(dim_params)))) {
stop(paste0("All '*_across' parameters must be associated to a dimension parameter. Found parameter '",
names(across_params)[i], "' but no parameter '",
strsplit(names(across_params)[i], '_across$')[[1]][1], "'."))
}
i <- i + 1
}
# Make the keys of 'across_params' to be the name of
# the corresponding dimension.
if (length(across_params) < 1) {
across_params <- NULL
} else {
names(across_params) <- gsub('_across$', '', names(across_params))
}
# Change name to inner_dims_across_files
inner_dims_across_files <- across_params
# Leave alone the dimension parameters in the variable dim_params
if (length(c(var_params_ind, dim_reorder_params_ind, tolerance_params_ind,
depends_params_ind, across_params_ind)) > 0) {
dim_params <- dim_params[-c(var_params_ind, dim_reorder_params_ind,
tolerance_params_ind, depends_params_ind,
across_params_ind)]
}
dim_names <- names(dim_params)
if (is.null(dim_names)) {
stop("At least one pattern dim must be specified.")
}
# Look for chunked dims
chunks <- vector('list', length(dim_names))
names(chunks) <- dim_names
for (dim_name in dim_names) {
if (!is.null(attr(dim_params[[dim_name]], 'chunk'))) {
chunks[[dim_name]] <- attr(dim_params[[dim_name]], 'chunk')
attributes(dim_params[[dim_name]]) <- attributes(dim_params[[dim_name]])[-which(names(attributes(dim_params[[dim_name]])) == 'chunk')]
} else {
chunks[[dim_name]] <- c(chunk = 1, n_chunks = 1)
}
}
# This is a helper function to compute the chunk indices to take once the total
# number of indices for a dimension has been discovered.
chunk_indices <- function(n_indices, chunk, n_chunks, dim_name) {
if (n_chunks > n_indices) {
stop("Requested to divide dimension '", dim_name, "' of length ",
n_indices, " in ", n_chunks, " chunks, which is not possible.")
}
chunks_to_extend <- n_indices - chunk_sizes[1] * n_chunks
if (chunks_to_extend > 0) {
chunk_sizes[1:chunks_to_extend] <- chunk_sizes[1:chunks_to_extend] + 1
}
chunk_size <- chunk_sizes[chunk]
offset <- 0
if (chunk > 1) {
offset <- sum(chunk_sizes[1:(chunk - 1)])
}
indices <- 1:chunk_sizes[chunk] + offset
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
# Check pattern_dims
if (is.null(pattern_dims)) {
.warning(paste0("Parameter 'pattern_dims' not specified. Taking the first dimension, '",
dim_names[1], "' as 'pattern_dims'."))
pattern_dims <- dim_names[1]
} else if (is.character(pattern_dims) && (length(pattern_dims) > 0)) {
pattern_dims <- unique(pattern_dims)
} else {
stop("Parameter 'pattern_dims' must be a vector of character strings.")
}
if (any(names(var_params) %in% pattern_dims)) {
stop("'*_var' parameters specified for pattern dimensions. Remove or fix them.")
}
# Find the pattern dimension with the pattern specifications
found_pattern_dim <- NULL
for (pattern_dim in pattern_dims) {
# Check all specifications in pattern_dim are valid
dat <- datasets <- dim_params[[pattern_dim]]
if (is.null(dat) || !(is.character(dat) && all(nchar(dat) > 0)) && !is.list(dat)) {
stop(paste0("Parameter '", pattern_dim,
"' must be a list of lists with pattern specifications or a vector of character strings."))
}
if (!is.null(dim_reorder_params[[pattern_dim]])) {
.warning(paste0("A reorder for the selectors of '", pattern_dim,
"' has been specified, but it is a pattern dimension and the reorder will be ignored."))
}
if (is.null(found_pattern_dim)) {
found_pattern_dim <- pattern_dim
} else {
stop("Found more than one pattern dim with pattern specifications (list of lists). One and only one pattern dim must contain pattern specifications.")
}
}
}
if (is.null(found_pattern_dim)) {
.warning(paste0("Could not find any pattern dim with explicit data set descriptions (in the form of list of lists). Taking the first pattern dim, '", pattern_dims[1], "', as dimension with pattern specifications."))
found_pattern_dim <- pattern_dims[1]
}
# Check metadata_dims
if (!is.null(metadata_dims)) {
if (is.na(metadata_dims)) {
metadata_dims <- NULL
} else if (!is.character(metadata_dims) || (length(metadata_dims) < 1)) {
stop("Parameter 'metadata' dims must be a vector of at least one character string.")
}
} else {
metadata_dims <- pattern_dims
}
# Once the pattern dimension with dataset specifications is found,
# the variable 'dat' is mounted with the information of each
# dataset.
# Take only the datasets for the requested chunk
dats_to_take <- chunk_indices(length(dim_params[[found_pattern_dim]]),
chunks[[found_pattern_dim]]['chunk'],
chunks[[found_pattern_dim]]['n_chunks'],
found_pattern_dim)
dim_params[[found_pattern_dim]] <- dim_params[[found_pattern_dim]][dats_to_take]
dat <- datasets <- dim_params[[found_pattern_dim]]
dat_info_names <- c('name', 'path')#, 'nc_var_name', 'suffix', 'var_min', 'var_max', 'dimnames')
dat_to_fetch <- c()
dat_names <- c()
if (!is.list(dat)) {
dat <- as.list(dat)
} else {
if (!any(sapply(dat, is.list))) {
dat <- list(dat)
}
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
}
for (i in 1:length(dat)) {
if (is.character(dat[[i]]) && length(dat[[i]]) == 1 && nchar(dat[[i]]) > 0) {
if (grepl('^(\\./|\\.\\./|/.*/|~/)', dat[[i]])) {
dat[[i]] <- list(path = dat[[i]])
} else {
dat[[i]] <- list(name = dat[[i]])
}
} else if (!is.list(dat[[i]])) {
stop(paste0("Parameter '", pattern_dim,
"' is incorrect. It must be a list of lists or character strings."))
}
#if (!(all(names(dat[[i]]) %in% dat_info_names))) {
# stop("Error: parameter 'dat' is incorrect. There are unrecognized components in the information of some of the datasets. Check 'dat' in ?Load for details.")
#}
if (!('name' %in% names(dat[[i]]))) {
dat[[i]][['name']] <- paste0('dat', i)
if (!('path' %in% names(dat[[i]]))) {
stop(paste0("Parameter '", found_pattern_dim,
"' is incorrect. A 'path' should be provided for each dataset if no 'name' is provided."))
}
} else if (!('path' %in% names(dat[[i]]))) {
dat_to_fetch <- c(dat_to_fetch, i)
}
#if ('path' %in% names(dat[[i]])) {
# if (!('nc_var_name' %in% names(dat[[i]]))) {
# dat[[i]][['nc_var_name']] <- '$var_name$'
# }
# if (!('suffix' %in% names(dat[[i]]))) {
# dat[[i]][['suffix']] <- ''
# }
# if (!('var_min' %in% names(dat[[i]]))) {
# dat[[i]][['var_min']] <- ''
# }
# if (!('var_max' %in% names(dat[[i]]))) {
# dat[[i]][['var_max']] <- ''
# }
#}
dat_names <- c(dat_names, dat[[i]][['name']])
}
if ((length(dat_to_fetch) > 0) && (length(dat_to_fetch) < length(dat))) {
.warning("'path' has been provided for some datasets. Any information in the configuration file related to these will be ignored.")
}
if (length(dat_to_fetch) > 0) {
stop("Specified only the name for some data sets, but not the path ",
"pattern. This option has not been yet implemented.")
}
# Reorder inner_dims_across_files (to make the keys be the file dimensions,
# and the values to be the inner dimensions that go across it).
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
if (!is.null(inner_dims_across_files)) {
# Reorder: example, convert list(ftime = 'chunk', ensemble = 'member', xx = 'chunk')
# to list(chunk = c('ftime', 'xx'), member = 'ensemble')
new_idaf <- list()
for (i in names(inner_dims_across_files)) {
if (!(inner_dims_across_files[[i]] %in% names(new_idaf))) {
new_idaf[[inner_dims_across_files[[i]]]] <- i
} else {
new_idaf[[inner_dims_across_files[[i]]]] <- c(new_idaf[[inner_dims_across_files[[i]]]], i)
}
}
inner_dims_across_files <- new_idaf
}
# Check return_vars
if (is.null(return_vars)) {
return_vars <- list()
# if (length(var_params) > 0) {
# return_vars <- as.list(paste0(names(var_params), '_var'))
# } else {
# return_vars <- list()
# }
}
if (!is.list(return_vars)) {
stop("Parameter 'return_vars' must be a list or NULL.")
}
if (length(return_vars) > 0 && is.null(names(return_vars))) {
# names(return_vars) <- rep('', length(return_vars))
stop("Parameter 'return_vars' must be a named list.")
}
i <- 1
while (i <= length(return_vars)) {
# if (names(return_vars)[i] == '') {
# if (!(is.character(return_vars[[i]]) && (length(return_vars[[i]]) == 1))) {
# stop("The ", i, "th specification in 'return_vars' is malformed.")
# }
# if (!grepl('_var$', return_vars[[i]])) {
# stop("The ", i, "th specification in 'return_vars' is malformed.")
# }
# dim_name <- strsplit(return_vars[[i]], '_var$')[[1]][1]
# if (!(dim_name %in% names(var_params))) {
# stop("'", dim_name, "_var' requested in 'return_vars' but ",
# "no '", dim_name, "_var' specified in the .Load call.")
# }
# names(return_vars)[i] <- var_params[[dim_name]]
# return_vars[[i]] <- found_pattern_dim
# } else
if (length(return_vars[[i]]) > 0) {
if (!is.character(return_vars[[i]])) {
stop("The ", i, "th specification in 'return_vars' is malformed. It ",
"must be a vector of character strings of valid file dimension ",
"names.")
}
}
i <- i + 1
}
# Check synonims
if (!is.null(synonims)) {
error <- FALSE
if (!is.list(synonims)) {
error <- TRUE
}
for (synonim_entry in names(synonims)) {
if (!(synonim_entry %in% names(dim_params)) &&
!(synonim_entry %in% names(return_vars))) {
error <- TRUE
}
if (!is.character(synonims[[synonim_entry]]) ||
length(synonims[[synonim_entry]]) < 1) {
error <- TRUE
}
}
if (error) {
stop("Parameter 'synonims' must be a named list, where the names are ",
"a name of a requested dimension or variable and the values are ",
"vectors of character strings with at least one alternative name ",
" for each dimension or variable in 'synonims'.")
}
}
if (length(unique(names(synonims))) < length(names(synonims))) {
stop("There must not be repeated entries in 'synonims'.")
}
if (length(unique(unlist(synonims))) < length(unlist(synonims))) {
stop("There must not be repeated values in 'synonims'.")
}
# Make that all dims and vars have an entry in synonims, even if only dim_name = dim_name
dim_entries_to_add <- which(!(names(dim_params) %in% names(synonims)))
if (length(dim_entries_to_add) > 0) {
synonims[names(dim_params)[dim_entries_to_add]] <- as.list(names(dim_params)[dim_entries_to_add])
}
var_entries_to_add <- which(!(names(var_params) %in% names(synonims)))
if (length(var_entries_to_add) > 0) {
synonims[names(var_params)[var_entries_to_add]] <- as.list(names(var_params)[var_entries_to_add])
}
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
# Check selector_checker
if (is.null(selector_checker) || !is.function(selector_checker)) {
stop("Parameter 'selector_checker' must be a function.")
}
# Check file_opener
if (is.null(file_opener) || !is.function(file_opener)) {
stop("Parameter 'file_opener' must be a function.")
}
# Check file_var_reader
if (!is.null(file_var_reader) && !is.function(file_var_reader)) {
stop("Parameter 'file_var_reader' must be a function.")
}
# Check file_dim_reader
if (!is.null(file_dim_reader) && !is.function(file_dim_reader)) {
stop("Parameter 'file_dim_reader' must be a function.")
}
# Check file_data_reader
if (is.null(file_data_reader) || !is.function(file_data_reader)) {
stop("Parameter 'file_data_reader' must be a function.")
}
# Check file_closer
if (is.null(file_closer) || !is.function(file_closer)) {
stop("Parameter 'file_closer' must be a function.")
}
# Check transform
if (!is.null(transform)) {
if (!is.function(transform)) {
stop("Parameter 'transform' must be a function.")
}
}
# Check transform_params
if (!is.null(transform_params)) {
if (!is.list(transform_params)) {
stop("Parameter 'transform_params' must be a list.")
}
if (is.null(names(transform_params))) {
stop("Parameter 'transform_params' must be a named list.")
}
}
# Check transform_vars
if (!is.null(transform_vars)) {
if (!is.character(transform_vars)) {
stop("Parameter 'transform_vars' must be a vector of character strings.")
}
}
if (any(!(transform_vars %in% names(return_vars)))) {
stop("All the variables specified in 'transform_vars' must also be specified in 'return_vars'.")
}
# Check apply_indices_after_transform
if (!is.logical(apply_indices_after_transform)) {
stop("Parameter 'apply_indices_after_transform' must be either TRUE or FALSE.")
# Check transform_extra_cells
if (!is.numeric(transform_extra_cells)) {
stop("Parameter 'transform_extra_cells' must be numeric.")
}
transform_extra_cells <- round(transform_extra_cells)
# Check retrieve
if (!is.logical(retrieve)) {
stop("Parameter 'retrieve' must be TRUE or FALSE.")
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
# Check num_procs
if (!is.null(num_procs)) {
if (!is.numeric(num_procs)) {
stop("Parameter 'num_procs' must be numeric.")
} else {
num_procs <- round(num_procs)
}
}
# Check silent
if (!is.logical(silent)) {
stop("Parameter 'silent' must be logical.")
}
dim_params[[found_pattern_dim]] <- dat_names
if (!silent) {
.message(paste0("Exploring files... This will take a variable amount ",
"of time depending on the issued request and the ",
"performance of the file server..."))
}
if (!is.character(debug)) {
dims_to_check <- c('time')
} else {
dims_to_check <- debug
debug <- TRUE
}
############################## READING FILE DIMS ############################
# Check that no unrecognized variables are present in the path patterns
# and also that no file dimensions are requested to THREDDs catalogs.
# And in the mean time, build all the work pieces and look for the
# first available file of each dataset.
array_of_files_to_load <- NULL
array_of_not_found_files <- NULL
indices_of_first_files_with_data <- vector('list', length(dat))
selectors_of_first_files_with_data <- vector('list', length(dat))
found_file_dims <- vector('list', length(dat))
expected_inner_dims <- vector('list', length(dat))
dataset_has_files <- rep(FALSE, length(dat))
#print("A")
for (i in 1:length(dat)) {
#print("B")
dat_selectors <- dim_params
dat_selectors[[found_pattern_dim]] <- dat_selectors[[found_pattern_dim]][i]
dim_vars <- paste0('$', dim_names, '$')
file_dims <- which(sapply(dim_vars, grepl, dat[[i]][['path']], fixed = TRUE))
if (length(file_dims) > 0) {
file_dims <- dim_names[file_dims]
}
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
file_dims <- unique(c(pattern_dims, file_dims))
found_file_dims[[i]] <- file_dims
expected_inner_dims[[i]] <- dim_names[which(!(dim_names %in% file_dims))]
# (Check the depending_file_dims).
if (any(c(names(depending_file_dims), unlist(depending_file_dims)) %in%
expected_inner_dims[[i]])) {
stop(paste0("The dimension dependancies specified in ",
"'depending_file_dims' can only be between file ",
"dimensions, but some inner dimensions found in ",
"dependancies for '", dat[[i]][['name']], "', which ",
"has the following file dimensions: ",
paste(paste0("'", file_dims, "'"), collapse = ', '), "."))
} else {
a <- names(depending_file_dims) %in% file_dims
b <- unlist(depending_file_dims) %in% file_dims
ab <- a & b
if (any(!ab)) {
.warning("Detected some dependancies in 'depending_file_dims' with ",
"non-existing dimension names. These will be disregarded.")
depending_file_dims <- depending_file_dims[-which(!ab)]
}
if (any(names(depending_file_dims) == unlist(depending_file_dims))) {
depending_file_dims <- depending_file_dims[-which(names(depending_file_dims) == unlist(depending_file_dims))]
}
}
# (Check the inner_dims_across_files).
if (any(!(names(inner_dims_across_files) %in% file_dims)) ||
any(!(unlist(inner_dims_across_files) %in% expected_inner_dims[[i]]))) {
stop(paste0("All relationships specified in ",
"'inner_dims_across_files' must be between a inner ",
"dimension and a file dimension. Found wrong ",
"specification for '", dat[[i]][['name']], "', which ",
"has the following file dimensions: ",
paste(paste0("'", file_dims, "'"), collapse = ', '),
", and the following inner dimensions: ",
paste(paste0("'", expected_inner_dims[[i]], "'"),
collapse = ', '), "."))
}
# (Check the return_vars).
j <- 1
while (j <= length(return_vars)) {
if (any(!(return_vars[[j]] %in% file_dims))) {
if (any(return_vars[[j]] %in% expected_inner_dims[[i]])) {
stop("Found variables in 'return_vars' requested ",
"for some inner dimensions (for dataset '",
dat[[i]][['name']], "'), but variables can only be ",
"requested for file dimensions.")
} else {
stop("Found variables in 'return_vars' requested ",
"for non-existing dimensions.")
}
}
j <- j + 1
}
if (!is.null(metadata_dims)) {
if (any(!(metadata_dims %in% file_dims))) {
stop("All dimensions in 'metadata_dims' must be file dimensions.")
}
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
# (Check the *_var parameters).
if (any(!(unlist(var_params) %in% names(return_vars)))) {
stop("All '*_var' params must associate a dimension to one of the ",
"requested variables in 'return_vars'.")
}
# # (Check the circular_dims parameters).
# if (!all(names(circular_dims) %in% expected_inner_dims[[i]])) {
# stop("Only inner dimensions can be requested as 'circular_dims'.")
# }
replace_values <- vector('list', length = length(file_dims))
names(replace_values) <- file_dims
# Take the first selector for all possible file dimensions
for (file_dim in file_dims) {
if (file_dim %in% names(var_params)) {
.warning(paste0("The '", file_dim, "_var' param will be ignored since '",
file_dim, "' is a file dimension (for the dataset with pattern ",
dat[[i]][['path']], ")."))
}
if (!is.list(dat_selectors[[file_dim]]) ||
(is.list(dat_selectors[[file_dim]]) &&
length(dat_selectors[[file_dim]]) == 2 &&
is.null(names(dat_selectors[[file_dim]])))) {
dat_selectors[[file_dim]] <- list(dat_selectors[[file_dim]])
}
first_class <- class(dat_selectors[[file_dim]][[1]])
first_length <- length(dat_selectors[[file_dim]][[1]])
for (j in 1:length(dat_selectors[[file_dim]])) {
sv <- selector_vector <- dat_selectors[[file_dim]][[j]]
if (!identical(first_class, class(sv)) ||
!identical(first_length, length(sv))) {
stop("All provided selectors for depending dimensions must ",
"be vectors of the same length and of the same class.")
}
if (is.character(sv) && !((length(sv) == 1) && (sv[1] %in% c('all', 'first', 'last')))) {
dat_selectors[[file_dim]][[j]] <- selector_checker(selectors = sv,
return_indices = FALSE)
# Take chunk if needed
dat_selectors[[file_dim]][[j]] <- dat_selectors[[file_dim]][[j]][chunk_indices(length(dat_selectors[[file_dim]][[j]]),
chunks[[file_dim]]['chunk'],
chunks[[file_dim]]['n_chunks'],
file_dim)]
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
} else if (!(is.numeric(sv) ||
(is.character(sv) && (length(sv) == 1) && (sv %in% c('all', 'first', 'last'))) ||
(is.list(sv) && (length(sv) == 2) && (all(sapply(sv, is.character)) ||
all(sapply(sv, is.numeric)))))) {
stop("All explicitly provided selectors for file dimensions must be character strings.")
}
}
sv <- dat_selectors[[file_dim]][[1]]
if (is.character(sv) && !((length(sv) == 1) && (sv[1] %in% c('all', 'first', 'last')))) {
replace_values[[file_dim]] <- dat_selectors[[file_dim]][[1]][1]
}
}
#print("C")
# Now we know which dimensions whose selectors are provided non-explicitly.
undefined_file_dims <- file_dims[which(sapply(replace_values, is.null))]
defined_file_dims <- file_dims[which(!(file_dims %in% undefined_file_dims))]
# Quickly check if the depending dimensions are provided properly.
for (file_dim in file_dims) {
if (file_dim %in% names(depending_file_dims)) {
## TODO: Detect multi-dependancies and forbid.
if (all(c(file_dim, depending_file_dims[[file_dim]]) %in% defined_file_dims)) {
if (length(dat_selectors[[file_dim]]) != length(dat_selectors[[depending_file_dims[[file_dim]]]][[1]])) {
stop(paste0("If providing selectors for the depending ",
"dimension '", file_dim, "', a ",
"vector of selectors must be provided for ",
"each selector of the dimension it depends on, '",
depending_file_dims[[file_dim]], "'."))
} else if (!all(names(dat_selectors[[file_dim]]) == dat_selectors[[depending_file_dims[[file_dim]]]][[1]])) {
stop(paste0("If providing selectors for the depending ",
"dimension '", file_dim, "', the name of the ",
"provided vectors of selectors must match ",
"exactly the selectors of the dimension it ",
"depends on, '", depending_file_dims[[file_dim]], "'."))
}
}
}
}
# Find the possible values for the selectors that are provided as
# indices. If the requested file is on server, impossible operation.
if (length(grep("^http", dat[[i]][['path']])) > 0) {
if (length(undefined_file_dims) > 0) {
stop(paste0("All selectors for the file dimensions must be ",
"character strings if requesting data to a remote ",
"server. Found invalid selectors for the file dimensions ",
paste(paste0("'", undefined_file_dims, "'"), collapse = ', '), "."))
}
dataset_has_files[i] <- TRUE
} else {
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
# Iterate over the known dimensions to find the first existing file.
# The path to the first existing file will be used to find the
# values for the non explicitly defined selectors.
first_file <- NULL
first_file_selectors <- NULL
if (length(undefined_file_dims) > 0) {
replace_values[undefined_file_dims] <- '*'
}
## TODO: What if length of defined_file_dims is 0? code might crash (in practice it worked for an example case)
files_to_check <- sapply(dat_selectors[defined_file_dims], function(x) length(x[[1]]))
sub_array_of_files_to_check <- array(1:prod(files_to_check), dim = files_to_check)
j <- 1
#print("D")
while (j <= prod(files_to_check) && is.null(first_file)) {
selector_indices <- which(sub_array_of_files_to_check == j, arr.ind = TRUE)[1, ]
selectors <- sapply(1:length(defined_file_dims),
function (x) {
vector_to_pick <- 1
if (defined_file_dims[x] %in% names(depending_file_dims)) {
vector_to_pick <- selector_indices[which(defined_file_dims == depending_file_dims[[defined_file_dims[x]]])]
}
dat_selectors[defined_file_dims][[x]][[vector_to_pick]][selector_indices[x]]
})
replace_values[defined_file_dims] <- selectors
file_path <- .ReplaceVariablesInString(dat[[i]][['path']], replace_values)
file_path <- Sys.glob(file_path)
if (length(file_path) > 0) {
first_file <- file_path[1]
first_file_selectors <- selectors
}
j <- j + 1
}
#print("E")
# Start looking for values for the non-explicitly defined selectors.
if (is.null(first_file)) {
.warning(paste0("No found files for the datset '", dat[[i]][['name']],
"'. Provide existing selectors for the file dimensions ",
" or check and correct its path pattern: ", dat[[i]][['path']]))
} else {
dataset_has_files[i] <- TRUE
## TODO: Improve message here if no variable found:
if (length(undefined_file_dims) > 0) {
# Looking for the first values, parsed from first_file.
first_values <- vector('list', length = length(undefined_file_dims))
names(first_values) <- undefined_file_dims
found_values <- 0
stop <- FALSE
try_dim <- 1
last_success <- 1
while ((found_values < length(undefined_file_dims)) && !stop) {
u_file_dim <- undefined_file_dims[try_dim]
if (is.null(first_values[[u_file_dim]])) {
path_with_globs_and_tag <- .ReplaceVariablesInString(dat[[i]][['path']],
replace_values[-which(file_dims == u_file_dim)],
allow_undefined_key_vars = TRUE)
found_value <- .FindTagValue(path_with_globs_and_tag,
first_file, u_file_dim)
if (!is.null(found_value)) {
found_values <- found_values + 1
last_success <- try_dim
first_values[[u_file_dim]] <- found_value
replace_values[[u_file_dim]] <- found_value
}
}
try_dim <- (try_dim %% length(undefined_file_dims)) + 1
if (try_dim == last_success) {
stop <- TRUE
}
}
if (found_values < length(undefined_file_dims)) {
stop(paste0("Path pattern of dataset '", dat[[i]][['name']],
"' is too complex. Could not automatically ",
"detect values for all non-explicitly defined ",
"indices. Check its pattern: ", dat[[i]][['path']]))
}
## TODO: Replace ReplaceGlobExpressions by looped call to FindTagValue? As done above
## Maybe it can solve more cases actually. I got warnings in ReplGlobExp with a typical
## cmor case, requesting all members and chunks for fixed var and sdate. Not fixing
## sdate raised 'too complex' error.
# Replace shell globs in path pattern and keep the file_dims as tags
dat[[i]][['path']] <- .ReplaceGlobExpressions(dat[[i]][['path']], first_file, replace_values,
file_dims, dat[[i]][['name']], FALSE)
# Now time to look for the available values for the non
# explicitly defined selectors for the file dimensions.
#print("H")
# Check first the ones that do not depend on others.
ufd <- c(undefined_file_dims[which(!(undefined_file_dims %in% names(depending_file_dims)))],
undefined_file_dims[which(undefined_file_dims %in% names(depending_file_dims))])
for (u_file_dim in ufd) {
replace_values[undefined_file_dims] <- first_values
replace_values[[u_file_dim]] <- '*'
depended_dim <- NULL
depended_dim_values <- NA
selectors <- dat_selectors[[u_file_dim]][[1]]
if (u_file_dim %in% names(depending_file_dims)) {
depended_dim <- depending_file_dims[[u_file_dim]]
depended_dim_values <- dat_selectors[[depended_dim]][[1]]
dat_selectors[[u_file_dim]] <- vector('list', length = length(depended_dim_values))
names(dat_selectors[[u_file_dim]]) <- depended_dim_values
} else {
dat_selectors[[u_file_dim]] <- list()
}
if (u_file_dim %in% unlist(depending_file_dims)) {
depending_dims <- names(depending_file_dims)[which(sapply(depending_file_dims, function(x) u_file_dim %in% x))]
replace_values[depending_dims] <- rep('*', length(depending_dims))
}
for (j in 1:length(depended_dim_values)) {
parsed_values <- c()
if (!is.null(depended_dim)) {
replace_values[[depended_dim]] <- depended_dim_values[j]
}
path_with_globs <- .ReplaceVariablesInString(dat[[i]][['path']], replace_values)
found_files <- Sys.glob(path_with_globs)
## TODO: Enhance this error message, or change by warning.
## Raises if a wrong sdate is specified, for example.
if (length(found_files) == 0) {
.warning(paste0("Could not find files for any '", u_file_dim,
"' for '", depended_dim, "' = '",
depended_dim_values[j], "'."))
dat_selectors[[u_file_dim]][[j]] <- NA
} else {
for (found_file in found_files) {
path_with_globs_and_tag <- .ReplaceVariablesInString(dat[[i]][['path']],
replace_values[-which(file_dims == u_file_dim)],
allow_undefined_key_vars = TRUE)
parsed_values <- c(parsed_values,
.FindTagValue(path_with_globs_and_tag, found_file,
u_file_dim))
}
dat_selectors[[u_file_dim]][[j]] <- selector_checker(selectors = selectors,
var = unique(parsed_values),
return_indices = FALSE)
# Take chunk if needed
dat_selectors[[u_file_dim]][[j]] <- dat_selectors[[u_file_dim]][[j]][chunk_indices(length(dat_selectors[[u_file_dim]][[j]]),
chunks[[u_file_dim]]['chunk'],
chunks[[u_file_dim]]['n_chunks'],
u_file_dim)]
}
}
}
#print("I")
} else {
dat[[i]][['path']] <- .ReplaceGlobExpressions(dat[[i]][['path']], first_file, replace_values,
defined_file_dims, dat[[i]][['name']], FALSE)
}
}
}
# Now fetch for the first available file
if (dataset_has_files[i]) {
known_dims <- file_dims
} else {
known_dims <- defined_file_dims
}
replace_values <- vector('list', length = length(known_dims))
names(replace_values) <- known_dims
files_to_load <- sapply(dat_selectors[known_dims], function(x) length(x[[1]]))
files_to_load[found_pattern_dim] <- 1
sub_array_of_files_to_load <- array(1:prod(files_to_load),
dim = files_to_load)
names(dim(sub_array_of_files_to_load)) <- known_dims
sub_array_of_not_found_files <- array(!dataset_has_files[i],
dim = files_to_load)
names(dim(sub_array_of_not_found_files)) <- known_dims
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
j <- 1
while (j <= prod(files_to_load)) {
selector_indices <- which(sub_array_of_files_to_load == j, arr.ind = TRUE)[1, ]
names(selector_indices) <- known_dims
selectors <- sapply(1:length(known_dims),
function (x) {
vector_to_pick <- 1
if (known_dims[x] %in% names(depending_file_dims)) {
vector_to_pick <- selector_indices[which(known_dims == depending_file_dims[[known_dims[x]]])]
}
dat_selectors[known_dims][[x]][[vector_to_pick]][selector_indices[x]]
})
names(selectors) <- known_dims
replace_values[known_dims] <- selectors
if (!dataset_has_files[i]) {
if (any(is.na(selectors))) {
replace_values <- replace_values[-which(names(replace_values) %in% names(selectors[which(is.na(selectors))]))]
}
file_path <- .ReplaceVariablesInString(dat[[i]][['path']], replace_values, TRUE)
sub_array_of_files_to_load[j] <- file_path
} else {
if (any(is.na(selectors))) {
replace_values <- replace_values[-which(names(replace_values) %in% names(selectors[which(is.na(selectors))]))]
file_path <- .ReplaceVariablesInString(dat[[i]][['path']], replace_values, TRUE)
sub_array_of_files_to_load[j] <- file_path
sub_array_of_not_found_files[j] <- TRUE
} else {
file_path <- .ReplaceVariablesInString(dat[[i]][['path']], replace_values)
sub_array_of_files_to_load[j] <- file_path
if (is.null(indices_of_first_files_with_data[[i]])) {
if (!(length(grep("^http", file_path)) > 0)) {
if (!file.exists(file_path)) {
file_path <- NULL
}
}
if (!is.null(file_path)) {
test_file <- NULL
## TODO: suppress error messages
test_file <- file_opener(file_path)
if (!is.null(test_file)) {
selector_indices[which(known_dims == found_pattern_dim)] <- i
indices_of_first_files_with_data[[i]] <- selector_indices
selectors_of_first_files_with_data[[i]] <- selectors
file_closer(test_file)
}
}
}
}
}
j <- j + 1
}
# Extend array as needed progressively
if (is.null(array_of_files_to_load)) {
array_of_files_to_load <- sub_array_of_files_to_load
array_of_not_found_files <- sub_array_of_not_found_files
} else {
array_of_files_to_load <- .MergeArrays(array_of_files_to_load, sub_array_of_files_to_load,
along = found_pattern_dim)
## TODO: file_dims, and variables like that.. are still ok now? I don't think so
array_of_not_found_files <- .MergeArrays(array_of_not_found_files, sub_array_of_not_found_files,
along = found_pattern_dim)
}
dat[[i]][['selectors']] <- dat_selectors
}
if (all(sapply(indices_of_first_files_with_data, is.null))) {
stop("No data files found for any of the specified datasets.")
}
########################### READING INNER DIMS. #############################
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
#print("J")
## TODO: To be run in parallel (local multi-core)
# Now time to work out the inner file dimensions.
# First pick the requested variables.
dims_to_iterate <- NULL
for (return_var in names(return_vars)) {
dims_to_iterate <- unique(c(dims_to_iterate, return_vars[[return_var]]))
}
if (found_pattern_dim %in% dims_to_iterate) {
dims_to_iterate <- dims_to_iterate[-which(dims_to_iterate == found_pattern_dim)]
}
common_return_vars <- NULL
common_first_found_file <- NULL
common_return_vars_pos <- NULL
if (length(return_vars) > 0) {
common_return_vars_pos <- which(sapply(return_vars, function(x) !(found_pattern_dim %in% x)))
}
if (length(common_return_vars_pos) > 0) {
common_return_vars <- return_vars[common_return_vars_pos]
return_vars <- return_vars[-common_return_vars_pos]
common_first_found_file <- rep(FALSE, length(which(sapply(common_return_vars, length) == 0)))
names(common_first_found_file) <- names(common_return_vars[which(sapply(common_return_vars, length) == 0)])
}
return_vars <- lapply(return_vars,
function(x) {
if (found_pattern_dim %in% x) {
x[-which(x == found_pattern_dim)]
} else {
x
}
})
if (length(common_return_vars) > 0) {
picked_common_vars <- vector('list', length = length(common_return_vars))
names(picked_common_vars) <- names(common_return_vars)
} else {
picked_common_vars <- NULL
}
picked_common_vars_ordered <- picked_common_vars
picked_common_vars_unorder_indices <- picked_common_vars
picked_vars <- vector('list', length = length(dat))
names(picked_vars) <- dat_names
picked_vars_ordered <- picked_vars
picked_vars_unorder_indices <- picked_vars
for (i in 1:length(dat)) {
if (dataset_has_files[i]) {
# Put all selectors in a list of a single list/vector of selectors.
# The dimensions that go across files will later be extended to have
# lists of lists/vectors of selectors.
for (inner_dim in expected_inner_dims[[i]]) {
if (!is.list(dat[[i]][['selectors']][[inner_dim]]) ||
(is.list(dat[[i]][['selectors']][[inner_dim]]) &&
length(dat[[i]][['selectors']][[inner_dim]]) == 2 &&
is.null(names(dat[[i]][['selectors']][[inner_dim]])))) {
dat[[i]][['selectors']][[inner_dim]] <- list(dat[[i]][['selectors']][[inner_dim]])
}
}
if (length(return_vars) > 0) {
picked_vars[[i]] <- vector('list', length = length(return_vars))
names(picked_vars[[i]]) <- names(return_vars)