test_that(".prep_cmd_INPUT works on base R DTM", { ## base R matrix ## out <- .prep_cmd_INPUT( dtm = dtm.bse, cw = cw, cv = NULL, wv = fake_word_vectors, missing = "stop" ) expect_s4_class(out$DTM, "dgCMatrix") expect_identical(dim(out$wem), wv.dims) }) test_that(".prep_cmd_INPUT works on dgCMatrix DTM", { ## dgCMatrix matrix ## out <- .prep_cmd_INPUT( dtm = dtm.dgc, cw = cw, cv = NULL, wv = fake_word_vectors, missing = "stop" ) expect_s4_class(out$DTM, "dgCMatrix") expect_identical(dim(out$wem), wv.dims) }) test_that(".prep_cmd_INPUT works on dfm DTM", { ## quanteda dfm//dgCMatrix matrix ## out <- .prep_cmd_INPUT( dtm = dtm.dfm, cw = cw, cv = NULL, wv = fake_word_vectors, missing = "stop" ) expect_s4_class(out$DTM, "dgCMatrix") expect_identical(dim(out$wem), wv.dims) }) test_that(".prep_cmd_INPUT works on tm DTM", { ## tm//simple_triplet_matrix matrix ## out <- .prep_cmd_INPUT( dtm = dtm.tm, cw = cw, cv = NULL, wv = fake_word_vectors, missing = "stop" ) expect_s4_class(out$DTM, "dgCMatrix") expect_identical(dim(out$wem), wv.dims) }) test_that(".prep_cmd_INPUT adds OOV words on different DTM types", { ## base R matrix ## out <- .prep_cmd_INPUT( dtm = dtm.bse, cw = cw.oov, cv = NULL, wv = fake_word_vectors_oov, missing = "stop" ) expect_s4_class(out$DTM, "dgCMatrix") expect_identical(dim(out$wem), wv.oov.dims) ## dgCMatrix matrix ## out <- .prep_cmd_INPUT( dtm = dtm.dgc, cw = cw.oov, cv = NULL, wv = fake_word_vectors_oov, missing = "stop" ) expect_s4_class(out$DTM, "dgCMatrix") expect_identical(dim(out$wem), wv.oov.dims) ## dfm//dgCMatrix matrix ## out <- .prep_cmd_INPUT( dtm = dtm.dfm, cw = cw.oov, cv = NULL, wv = fake_word_vectors_oov, missing = "stop" ) expect_s4_class(out$DTM, "dgCMatrix") expect_identical(dim(out$wem), wv.oov.dims) ## tm//simple_triplet_matrix matrix ## out <- .prep_cmd_INPUT( dtm = dtm.tm, cw = cw.oov, cv = NULL, wv = fake_word_vectors_oov, missing = "stop" ) expect_s4_class(out$DTM, "dgCMatrix") expect_identical(dim(out$wem), wv.oov.dims) }) test_that(".prep_cmd_INPUT adds concept vectors on different DTM types", { ## base R matrix ## out <- .prep_cmd_INPUT( dtm = dtm.bse, cw = NULL, cv = get_centroid(anchor.solo.c, fake_word_vectors), wv = fake_word_vectors, missing = "stop" ) expect_s4_class(out$DTM, "dgCMatrix") expect_identical(dim(out$wem), wv.cv.dims) ## dgCMatrix matrix ## out <- .prep_cmd_INPUT( dtm = dtm.dgc, cw = NULL, cv = get_centroid(anchor.solo.c, fake_word_vectors), wv = fake_word_vectors, missing = "stop" ) expect_s4_class(out$DTM, "dgCMatrix") expect_identical(dim(out$wem), wv.cv.dims) ## dfm//dgCMatrix matrix ## out <- .prep_cmd_INPUT( dtm = dtm.dfm, cw = NULL, cv = get_centroid(anchor.solo.c, fake_word_vectors), wv = fake_word_vectors_oov, missing = "stop" ) expect_s4_class(out$DTM, "dgCMatrix") expect_identical(dim(out$wem), wv.cv.dims) ## tm//simple_triplet_matrix matrix ## out <- .prep_cmd_INPUT( dtm = dtm.tm, cw = NULL, cv = get_centroid(anchor.solo.c, fake_word_vectors), wv = fake_word_vectors_oov, missing = "stop" ) expect_s4_class(out$DTM, "dgCMatrix") expect_identical(dim(out$wem), wv.cv.dims) }) test_that(".prep_cmd_INPUT adds concept vectors and OOV words on different DTM types", { ## base R matrix ## out <- .prep_cmd_INPUT( dtm = dtm.bse, cw = cw.oov, cv = get_centroid(anchor.solo.c, fake_word_vectors), wv = fake_word_vectors_oov, missing = "stop" ) expect_s4_class(out$DTM, "dgCMatrix") expect_identical(dim(out$wem), wv.cv.cw.dims) ## dgCMatrix matrix ## out <- .prep_cmd_INPUT( dtm = dtm.dgc, cw = cw.oov, cv = get_centroid(anchor.solo.c, fake_word_vectors), wv = fake_word_vectors_oov, missing = "stop" ) expect_s4_class(out$DTM, "dgCMatrix") expect_identical(dim(out$wem), wv.cv.cw.dims) ## dfm//dgCMatrix matrix ## out <- .prep_cmd_INPUT( dtm = dtm.dfm, cw = cw.oov, cv = get_centroid(anchor.solo.c, fake_word_vectors), wv = fake_word_vectors_oov, missing = "stop" ) expect_s4_class(out$DTM, "dgCMatrix") expect_identical(dim(out$wem), wv.cv.cw.dims) ## tm//simple_triplet_matrix matrix ## out <- .prep_cmd_INPUT( dtm = dtm.tm, cw = cw.oov, cv = get_centroid(anchor.solo.c, fake_word_vectors), wv = fake_word_vectors_oov, missing = "stop" ) expect_s4_class(out$DTM, "dgCMatrix") expect_identical(dim(out$wem), wv.cv.cw.dims) })