[numpy] add trunc

integration_tests/CMakeLists.txt

@@ -596,6 +596,7 @@ RUN(NAME elemental_09        LABELS cpython llvm c NOFAST)
 RUN(NAME elemental_10        LABELS cpython llvm c NOFAST)
 RUN(NAME elemental_11        LABELS cpython llvm c NOFAST)
 RUN(NAME elemental_12        LABELS cpython llvm c NOFAST)
+RUN(NAME elemental_13        LABELS cpython llvm c NOFAST)
 RUN(NAME test_random         LABELS cpython llvm NOFAST)
 RUN(NAME test_os             LABELS cpython llvm c NOFAST)
 RUN(NAME test_builtin        LABELS cpython llvm c)

integration_tests/elemental_13.py

@@ -0,0 +1,64 @@
+from lpython import f32, f64
+from numpy import trunc, empty, sqrt, reshape, int32, float32, float64
+
+
+def elemental_trunc64():
+    i: i32
+    j: i32
+    k: i32
+    l: i32
+    eps: f32
+    eps = f32(1e-6)
+
+    arraynd: f64[32, 16, 8, 4] = empty((32, 16, 8, 4), dtype=float64)
+
+    newshape: i32[1] = empty(1, dtype = int32)
+    newshape[0] = 16384
+
+    for i in range(32):
+        for j in range(16):
+            for k in range(8):
+                for l in range(4):
+                    arraynd[i, j, k, l] = f64((-1)**l) * sqrt(float(i + j + j + l))
+
+    observed: f64[32, 16, 8, 4] = empty((32, 16, 8, 4), dtype=float64)
+    observed = trunc(arraynd)
+
+    observed1d: f64[16384] = empty(16384, dtype=float64)
+    observed1d = reshape(observed, newshape)
+
+    array: f64[16384] = empty(16384, dtype=float64)
+    array = reshape(arraynd, newshape)
+
+    for i in range(16384):
+        assert f32(abs(trunc(array[i]) - observed1d[i])) <= eps
+
+
+def elemental_trunc32():
+    i: i32
+    j: i32
+    k: i32
+    l: i32
+    eps: f32
+    eps = f32(1e-6)
+
+    arraynd: f32[32, 16, 8, 4] = empty((32, 16, 8, 4), dtype=float32)
+
+    for i in range(32):
+        for j in range(16):
+            for k in range(8):
+                for l in range(4):
+                    arraynd[i, j, k, l] = f32(f64((-1)**l) * sqrt(float(i + j + j + l)))
+
+    observed: f32[32, 16, 8, 4] = empty((32, 16, 8, 4), dtype=float32)
+    observed = trunc(arraynd)
+
+    for i in range(32):
+        for j in range(16):
+            for k in range(8):
+                for l in range(4):
+                    assert abs(trunc(arraynd[i, j, k, l]) - observed[i, j, k, l]) <= eps
+
+
+elemental_trunc64()
+elemental_trunc32() 

src/libasr/runtime/lfortran_intrinsics.c

@@ -971,6 +971,18 @@ LFORTRAN_API double_complex_t _lfortran_zatanh(double_complex_t x)
     return catanh(x);
 }
 
+// trunc -----------------------------------------------------------------------
+
+LFORTRAN_API float _lfortran_strunc(float x)
+{
+    return truncf(x);
+}
+
+LFORTRAN_API double _lfortran_dtrunc(double x)
+{
+    return trunc(x);
+}
+
 // phase --------------------------------------------------------------------
 
 LFORTRAN_API float _lfortran_cphase(float_complex_t x)

src/libasr/runtime/lfortran_intrinsics.h

@@ -168,6 +168,8 @@ LFORTRAN_API float _lfortran_satanh(float x);
 LFORTRAN_API double _lfortran_datanh(double x);
 LFORTRAN_API float_complex_t _lfortran_catanh(float_complex_t x);
 LFORTRAN_API double_complex_t _lfortran_zatanh(double_complex_t x);
+LFORTRAN_API float _lfortran_strunc(float x);
+LFORTRAN_API double _lfortran_dtrunc(double x);
 LFORTRAN_API float _lfortran_cphase(float_complex_t x);
 LFORTRAN_API double _lfortran_zphase(double_complex_t x);
 LFORTRAN_API bool _lpython_str_compare_eq(char** s1, char** s2);

src/runtime/lpython_intrinsic_numpy.py

@@ -410,3 +410,23 @@ def ceil(x: f32) -> f32:
     if x <= f32(0) or x == resultf:
         return resultf
     return resultf + f32(1)
+
+########## trunc ##########
+
+@ccall
+def _lfortran_dtrunc(x: f64) -> f64:
+    pass
+
+@overload
+@vectorize
+def trunc(x: f64) -> f64:
+    return _lfortran_dtrunc(x)
+
+@ccall
+def _lfortran_strunc(x: f32) -> f32:
+    pass
+
+@overload
+@vectorize
+def trunc(x: f32) -> f32:
+    return _lfortran_strunc(x)

tests/reference/asr-array_01_decl-39cf894.json

@@ -6,7 +6,7 @@
     "outfile": null,
     "outfile_hash": null,
     "stdout": "asr-array_01_decl-39cf894.stdout",
-    "stdout_hash": "137a0c427925ba7da2e7151f2cf52bfa9a64fede11fe8d2653f20b64",
+    "stdout_hash": "2aa47467473392c970bb1ddde961e3007d4c157bb0ea507b5e0db4a4",
     "stderr": null,
     "stderr_hash": null,
     "returncode": 0

tests/reference/asr-array_01_decl-39cf894.stderr

@@ -0,0 +1,11 @@
+warning: The module 'numpy' located in $DIR/src/bin/../runtime/lpython_intrinsic_numpy.py cannot be loaded
+ --> tests/../integration_tests/array_01_decl.py:2:1
+  |
+2 | from numpy import empty, int16, int32, int64, float32, float64, complex64, complex128
+  | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ imported here
+
+semantic error: Decorator: vertorize is not supported
+   --> $DIR/src/bin/../runtime/lpython_intrinsic_numpy.py:421:2
+    |
+421 | @vertorize
+    |  ^^^^^^^^^