diff --git a/code/ndarray.c b/code/ndarray.c
index b297b3f1..361d664d 100644
--- a/code/ndarray.c
+++ b/code/ndarray.c
@@ -1874,28 +1874,110 @@ mp_obj_t ndarray_unary_op(mp_unary_op_t op, mp_obj_t self_in) {
 #endif /* NDARRAY_HAS_UNARY_OPS */
 
 #if NDARRAY_HAS_TRANSPOSE
-mp_obj_t ndarray_transpose(mp_obj_t self_in) {
-    #if ULAB_MAX_DIMS == 1
-        return self_in;
-    #endif
-    // TODO: check, what happens to the offset here, if we have a view
+// We have to implement the T property separately, for the property can't take keyword arguments
+
+#if ULAB_MAX_DIMS == 1
+// isolating the one-dimensional case saves space, because the transpose is sort of meaningless 
+mp_obj_t ndarray_T(mp_obj_t self_in) {
+    return self_in;
+}
+#else
+mp_obj_t ndarray_T(mp_obj_t self_in) {
+    // without argument, simply return a view with axes in reverse order
     ndarray_obj_t *self = MP_OBJ_TO_PTR(self_in);
     if(self->ndim == 1) {
         return self_in;
     }
     size_t *shape = m_new(size_t, self->ndim);
     int32_t *strides = m_new(int32_t, self->ndim);
-    for(uint8_t i=0; i < self->ndim; i++) {
+    for(uint8_t i = 0; i < self->ndim; i++) {
         shape[ULAB_MAX_DIMS - 1 - i] = self->shape[ULAB_MAX_DIMS - self->ndim + i];
         strides[ULAB_MAX_DIMS - 1 - i] = self->strides[ULAB_MAX_DIMS - self->ndim + i];
     }
-    // TODO: I am not sure ndarray_new_view is OK here...
-    // should be deep copy...
     ndarray_obj_t *ndarray = ndarray_new_view(self, self->ndim, shape, strides, 0);
     return MP_OBJ_FROM_PTR(ndarray);
 }
+#endif /* ULAB_MAX_DIMS == 1 */
+
+MP_DEFINE_CONST_FUN_OBJ_1(ndarray_T_obj, ndarray_T);
+
+# if ULAB_MAX_DIMS == 1
+// again, nothing to do, if there is only one dimension, though, the arguments might still have to be parsed...
+mp_obj_t ndarray_transpose(mp_obj_t self_in) {
+    return self_in;
+}
 
 MP_DEFINE_CONST_FUN_OBJ_1(ndarray_transpose_obj, ndarray_transpose);
+#else
+mp_obj_t ndarray_transpose(size_t n_args, const mp_obj_t *pos_args, mp_map_t *kw_args) {
+    static const mp_arg_t allowed_args[] = {
+        { MP_QSTR_, MP_ARG_REQUIRED | MP_ARG_OBJ, { .u_rom_obj = MP_ROM_NONE } },
+        { MP_QSTR_axes, MP_ARG_OBJ, { .u_rom_obj = MP_ROM_NONE } },
+    };
+
+    mp_arg_val_t args[MP_ARRAY_SIZE(allowed_args)];
+    mp_arg_parse_all(n_args, pos_args, kw_args, MP_ARRAY_SIZE(allowed_args), allowed_args, args);
+
+    ndarray_obj_t *self = MP_OBJ_TO_PTR(args[0].u_obj);
+
+    if(self->ndim == 1) {
+        return args[0].u_obj;
+    }
+
+    size_t *shape = m_new(size_t, self->ndim);
+    int32_t *strides = m_new(int32_t, self->ndim);
+    uint8_t *order = m_new(uint8_t, self->ndim);
+
+    mp_obj_t axes = args[1].u_obj;
+
+    if(axes == mp_const_none) {
+        // simply swap the order of the axes
+        for(uint8_t i = 0; i < self->ndim; i++) {
+            order[i] = self->ndim - 1 - i;
+        }
+    } else {
+        if(!mp_obj_is_type(axes, &mp_type_tuple)) {
+            mp_raise_TypeError(MP_ERROR_TEXT("keyword argument must be tuple of integers"));
+        }
+        // start with the straight array, and then swap only those specified in the argument
+        for(uint8_t i = 0; i < self->ndim; i++) {
+            order[i] = i;
+        }
+
+        mp_obj_tuple_t *axes_tuple = MP_OBJ_TO_PTR(axes);
+
+        if(axes_tuple->len > self->ndim) {
+            mp_raise_ValueError(MP_ERROR_TEXT("too many axes specified"));
+        }
+
+        for(uint8_t i = 0; i < axes_tuple->len; i++) {
+            int32_t ax = mp_obj_get_int(axes_tuple->items[i]);
+            if((ax >= self->ndim) || (ax < 0)) {
+                mp_raise_ValueError(MP_ERROR_TEXT("axis index out of bounds"));
+            } else {
+                order[i] = (uint8_t)ax;
+                // TODO: check that no two identical numbers appear in the tuple
+                for(uint8_t j = 0; j < i; j++) {
+                    if(order[i] == order[j]) {
+                        mp_raise_ValueError(MP_ERROR_TEXT("repeated indices"));
+                    }
+                }
+            }
+        }
+    }
+
+    uint8_t axis_offset = ULAB_MAX_DIMS - self->ndim;
+    for(uint8_t i = 0; i < self->ndim; i++) {
+        shape[axis_offset + i] = self->shape[axis_offset + order[i]];
+        strides[axis_offset + i] = self->strides[axis_offset + order[i]];
+    }
+
+    ndarray_obj_t *ndarray = ndarray_new_view(self, self->ndim, shape, strides, 0);
+    return MP_OBJ_FROM_PTR(ndarray);
+}
+
+MP_DEFINE_CONST_FUN_OBJ_KW(ndarray_transpose_obj, 1, ndarray_transpose);
+#endif /* ULAB_MAX_DIMS == 1 */
 #endif /* NDARRAY_HAS_TRANSPOSE */
 
 #if ULAB_MAX_DIMS > 1
diff --git a/code/ndarray.h b/code/ndarray.h
index 8e81773d..af72b1ad 100644
--- a/code/ndarray.h
+++ b/code/ndarray.h
@@ -265,9 +265,16 @@ MP_DECLARE_CONST_FUN_OBJ_1(ndarray_tolist_obj);
 #endif
 
 #if NDARRAY_HAS_TRANSPOSE
+mp_obj_t ndarray_T(mp_obj_t );
+MP_DECLARE_CONST_FUN_OBJ_1(ndarray_T_obj);
+#if ULAB_MAX_DIMS == 1
 mp_obj_t ndarray_transpose(mp_obj_t );
 MP_DECLARE_CONST_FUN_OBJ_1(ndarray_transpose_obj);
-#endif
+#else
+mp_obj_t ndarray_transpose(size_t , const mp_obj_t *, mp_map_t *);
+MP_DECLARE_CONST_FUN_OBJ_KW(ndarray_transpose_obj);
+#endif /* ULAB_MAX_DIMS == 1 */
+#endif /* NDARRAY_HAS_TRANSPOSE */
 
 #if ULAB_NUMPY_HAS_NDINFO
 mp_obj_t ndarray_info(mp_obj_t );
diff --git a/code/ndarray_properties.c b/code/ndarray_properties.c
index 6c048bda..8200445a 100644
--- a/code/ndarray_properties.c
+++ b/code/ndarray_properties.c
@@ -64,7 +64,7 @@ void ndarray_properties_attr(mp_obj_t self_in, qstr attr, mp_obj_t *dest) {
             #endif
             #if NDARRAY_HAS_TRANSPOSE
             case MP_QSTR_T:
-                dest[0] = ndarray_transpose(self_in);
+                dest[0] = ndarray_T(self_in);
                 break;
             #endif
             #if ULAB_SUPPORTS_COMPLEX
diff --git a/code/ulab.c b/code/ulab.c
index 8a0b50ca..205ddac5 100644
--- a/code/ulab.c
+++ b/code/ulab.c
@@ -33,7 +33,7 @@
 #include "user/user.h"
 #include "utils/utils.h"
 
-#define ULAB_VERSION 6.10.0
+#define ULAB_VERSION 6.11.0
 #define xstr(s) str(s)
 #define str(s) #s
 
diff --git a/docs/manual/source/conf.py b/docs/manual/source/conf.py
index c10faeb2..3feeef88 100644
--- a/docs/manual/source/conf.py
+++ b/docs/manual/source/conf.py
@@ -27,7 +27,7 @@
 author = 'Zoltán Vörös'
 
 # The full version, including alpha/beta/rc tags
-release = '6.9.0'
+release = '6.11.0'
 
 
 # -- General configuration ---------------------------------------------------
diff --git a/docs/manual/source/ulab-ndarray.rst b/docs/manual/source/ulab-ndarray.rst
index 46288a26..dde9eab0 100644
--- a/docs/manual/source/ulab-ndarray.rst
+++ b/docs/manual/source/ulab-ndarray.rst
@@ -1564,6 +1564,9 @@ dimensions is larger than 1.
     
 
 
+The method also accepts the ``axes`` keyword argument, if permutation of
+the returned axes is required.
+
 The transpose of the array can also be gotten through the ``T``
 property:
 
diff --git a/docs/ulab-convert.ipynb b/docs/ulab-convert.ipynb
index 53f28bcb..1cf66f52 100644
--- a/docs/ulab-convert.ipynb
+++ b/docs/ulab-convert.ipynb
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-09T06:27:15.118699Z",
@@ -61,7 +61,7 @@
     "author = 'Zoltán Vörös'\n",
     "\n",
     "# The full version, including alpha/beta/rc tags\n",
-    "release = '6.9.0'\n",
+    "release = '6.11.0'\n",
     "\n",
     "\n",
     "# -- General configuration ---------------------------------------------------\n",
@@ -217,7 +217,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-09T06:27:21.647179Z",
@@ -258,7 +258,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-09T06:27:42.024028Z",
@@ -270,34 +270,6 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/v923z/anaconda3/lib/python3.11/site-packages/nbconvert/exporters/exporter.py:349: MissingIDFieldWarning: Code cell is missing an id field, this will become a hard error in future nbformat versions. You may want to use `normalize()` on your notebooks before validations (available since nbformat 5.1.4). Previous versions of nbformat are fixing this issue transparently, and will stop doing so in the future.\n",
-      "  _, nbc = validator.normalize(nbc)\n",
-      "/home/v923z/anaconda3/lib/python3.11/site-packages/nbconvert/exporters/exporter.py:349: MissingIDFieldWarning: Code cell is missing an id field, this will become a hard error in future nbformat versions. You may want to use `normalize()` on your notebooks before validations (available since nbformat 5.1.4). Previous versions of nbformat are fixing this issue transparently, and will stop doing so in the future.\n",
-      "  _, nbc = validator.normalize(nbc)\n",
-      "/home/v923z/anaconda3/lib/python3.11/site-packages/nbconvert/exporters/exporter.py:349: MissingIDFieldWarning: Code cell is missing an id field, this will become a hard error in future nbformat versions. You may want to use `normalize()` on your notebooks before validations (available since nbformat 5.1.4). Previous versions of nbformat are fixing this issue transparently, and will stop doing so in the future.\n",
-      "  _, nbc = validator.normalize(nbc)\n",
-      "/home/v923z/anaconda3/lib/python3.11/site-packages/nbconvert/exporters/exporter.py:349: MissingIDFieldWarning: Code cell is missing an id field, this will become a hard error in future nbformat versions. You may want to use `normalize()` on your notebooks before validations (available since nbformat 5.1.4). Previous versions of nbformat are fixing this issue transparently, and will stop doing so in the future.\n",
-      "  _, nbc = validator.normalize(nbc)\n",
-      "/home/v923z/anaconda3/lib/python3.11/site-packages/nbconvert/exporters/exporter.py:349: MissingIDFieldWarning: Code cell is missing an id field, this will become a hard error in future nbformat versions. You may want to use `normalize()` on your notebooks before validations (available since nbformat 5.1.4). Previous versions of nbformat are fixing this issue transparently, and will stop doing so in the future.\n",
-      "  _, nbc = validator.normalize(nbc)\n",
-      "/home/v923z/anaconda3/lib/python3.11/site-packages/nbconvert/exporters/exporter.py:349: MissingIDFieldWarning: Code cell is missing an id field, this will become a hard error in future nbformat versions. You may want to use `normalize()` on your notebooks before validations (available since nbformat 5.1.4). Previous versions of nbformat are fixing this issue transparently, and will stop doing so in the future.\n",
-      "  _, nbc = validator.normalize(nbc)\n",
-      "/home/v923z/anaconda3/lib/python3.11/site-packages/nbconvert/exporters/exporter.py:349: MissingIDFieldWarning: Code cell is missing an id field, this will become a hard error in future nbformat versions. You may want to use `normalize()` on your notebooks before validations (available since nbformat 5.1.4). Previous versions of nbformat are fixing this issue transparently, and will stop doing so in the future.\n",
-      "  _, nbc = validator.normalize(nbc)\n",
-      "/home/v923z/anaconda3/lib/python3.11/site-packages/nbconvert/exporters/exporter.py:349: MissingIDFieldWarning: Code cell is missing an id field, this will become a hard error in future nbformat versions. You may want to use `normalize()` on your notebooks before validations (available since nbformat 5.1.4). Previous versions of nbformat are fixing this issue transparently, and will stop doing so in the future.\n",
-      "  _, nbc = validator.normalize(nbc)\n",
-      "/home/v923z/anaconda3/lib/python3.11/site-packages/nbconvert/exporters/exporter.py:349: MissingIDFieldWarning: Code cell is missing an id field, this will become a hard error in future nbformat versions. You may want to use `normalize()` on your notebooks before validations (available since nbformat 5.1.4). Previous versions of nbformat are fixing this issue transparently, and will stop doing so in the future.\n",
-      "  _, nbc = validator.normalize(nbc)\n",
-      "/home/v923z/anaconda3/lib/python3.11/site-packages/nbconvert/exporters/exporter.py:349: MissingIDFieldWarning: Code cell is missing an id field, this will become a hard error in future nbformat versions. You may want to use `normalize()` on your notebooks before validations (available since nbformat 5.1.4). Previous versions of nbformat are fixing this issue transparently, and will stop doing so in the future.\n",
-      "  _, nbc = validator.normalize(nbc)\n",
-      "/home/v923z/anaconda3/lib/python3.11/site-packages/nbconvert/exporters/exporter.py:349: MissingIDFieldWarning: Code cell is missing an id field, this will become a hard error in future nbformat versions. You may want to use `normalize()` on your notebooks before validations (available since nbformat 5.1.4). Previous versions of nbformat are fixing this issue transparently, and will stop doing so in the future.\n",
-      "  _, nbc = validator.normalize(nbc)\n",
-      "/home/v923z/anaconda3/lib/python3.11/site-packages/nbconvert/exporters/exporter.py:349: MissingIDFieldWarning: Code cell is missing an id field, this will become a hard error in future nbformat versions. You may want to use `normalize()` on your notebooks before validations (available since nbformat 5.1.4). Previous versions of nbformat are fixing this issue transparently, and will stop doing so in the future.\n",
-      "  _, nbc = validator.normalize(nbc)\n",
-      "/home/v923z/anaconda3/lib/python3.11/site-packages/nbconvert/exporters/exporter.py:349: MissingIDFieldWarning: Code cell is missing an id field, this will become a hard error in future nbformat versions. You may want to use `normalize()` on your notebooks before validations (available since nbformat 5.1.4). Previous versions of nbformat are fixing this issue transparently, and will stop doing so in the future.\n",
-      "  _, nbc = validator.normalize(nbc)\n",
-      "/home/v923z/anaconda3/lib/python3.11/site-packages/nbconvert/exporters/exporter.py:349: MissingIDFieldWarning: Code cell is missing an id field, this will become a hard error in future nbformat versions. You may want to use `normalize()` on your notebooks before validations (available since nbformat 5.1.4). Previous versions of nbformat are fixing this issue transparently, and will stop doing so in the future.\n",
-      "  _, nbc = validator.normalize(nbc)\n",
       "/home/v923z/anaconda3/lib/python3.11/site-packages/nbconvert/exporters/exporter.py:349: MissingIDFieldWarning: Code cell is missing an id field, this will become a hard error in future nbformat versions. You may want to use `normalize()` on your notebooks before validations (available since nbformat 5.1.4). Previous versions of nbformat are fixing this issue transparently, and will stop doing so in the future.\n",
       "  _, nbc = validator.normalize(nbc)\n"
      ]
diff --git a/docs/ulab-ndarray.ipynb b/docs/ulab-ndarray.ipynb
index c7518c26..eca54340 100644
--- a/docs/ulab-ndarray.ipynb
+++ b/docs/ulab-ndarray.ipynb
@@ -2237,6 +2237,13 @@
     "print('shape of a:', a.shape)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The method also accepts the `axes` keyword argument, if permutation of the returned axes is required."
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -3731,11 +3738,8 @@
   }
  ],
  "metadata": {
-  "interpreter": {
-   "hash": "ce9a02f9f7db620716422019cafa4bc1786ca85daa298b819f6da075e7993842"
-  },
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "base",
    "language": "python",
    "name": "python3"
   },
@@ -3749,7 +3753,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5"
+   "version": "3.11.7"
   },
   "toc": {
    "base_numbering": 1,
diff --git a/tests/1d/numpy/universal_functions.py b/tests/1d/numpy/universal_functions.py
index c41cf948..a72d73d1 100644
--- a/tests/1d/numpy/universal_functions.py
+++ b/tests/1d/numpy/universal_functions.py
@@ -7,142 +7,94 @@
     import numpy as np
     import scipy as spy
     
-result = (np.sin(np.pi/2))
-ref_result = 1.0
-print(math.isclose(result, ref_result, rel_tol=1E-6, abs_tol=1E-6))
+def test_function(func, reference, expression):
+     result = expression
+     print(f'testing {func}')
+     print(math.isclose(result, reference, rel_tol=1E-6, abs_tol=1E-6))
+     print()
 
-result = (np.cos(np.pi/2))
-ref_result = 0.0
-print(math.isclose(result, ref_result, rel_tol=1E-6, abs_tol=1E-6))
+def test_function_array(func, reference, expression):
+    print(f'testing {func}')
+    results = []
+    for i in range(len(references)):
+        results.append(math.isclose(references[i], expression[i], rel_tol=1E-6, abs_tol=1E-6))
+    print(results)
+    print()
 
-result = (np.tan(np.pi/2))
-ref_result = 1.633123935319537e+16
-print(math.isclose(result, ref_result, rel_tol=1E-6, abs_tol=1E-6))
 
-result = (np.sinh(np.pi/2))
-ref_result = 2.3012989023072947
-print(math.isclose(result, ref_result, rel_tol=1E-6, abs_tol=1E-6))
+test_function('sin', 1.0, np.sin(np.pi/2))
 
-result = (np.cosh(np.pi/2))
-ref_result = 2.5091784786580567
-print(math.isclose(result, ref_result, rel_tol=1E-6, abs_tol=1E-6))
+test_function('cos', 0.0, (np.cos(np.pi/2)))
 
-result = (np.tanh(np.pi/2))
-ref_result = 0.9171523356672744
-print(math.isclose(result, ref_result, rel_tol=1E-6, abs_tol=1E-6))
+test_function('tan', 1.633123935319537e+16, np.tan(np.pi/2))
 
-ref_result = np.pi/2
-result = (np.asin(np.sin(np.pi/2)))
-print(math.isclose(result, ref_result, rel_tol=1E-6, abs_tol=1E-6))
+test_function('sinh', 2.3012989023072947, np.sinh(np.pi/2))
 
-result = (np.acos(np.cos(np.pi/2)))
-print(math.isclose(result, ref_result, rel_tol=1E-6, abs_tol=1E-6))
+test_function('cosh:', 2.5091784786580567, np.cosh(np.pi/2))
 
-result = (np.atan(np.tan(np.pi/2)))
-print(math.isclose(result, ref_result, rel_tol=1E-6, abs_tol=1E-6))
+test_function('tanh', 0.9171523356672744, np.tanh(np.pi/2))
 
-result = (np.cosh(np.acosh(np.pi/2)))
-print(math.isclose(result, ref_result, rel_tol=1E-6, abs_tol=1E-6))
+test_function('asin', np.pi/2, np.asin(np.sin(np.pi/2)))
 
-result = (np.sinh(np.asinh(np.pi/2)))
-print(math.isclose(result, ref_result, rel_tol=1E-6, abs_tol=1E-6))
-    
-print(np.degrees(np.pi))
-print(np.radians(np.degrees(np.pi)))
-print(np.floor(np.pi))
-print(np.ceil(np.pi))
-print(np.sqrt(np.pi))
-print(np.exp(1))
-print(np.log(np.exp(1)))
-
-print(np.log2(2**1))
-
-print(np.log10(10**1))
-print(math.isclose(np.exp(1) - np.expm1(1), 1))
-
-x = np.array([-1, +1, +1, -1])
-y = np.array([-1, -1, +1, +1])
-result = (np.arctan2(y, x) * 180 / np.pi)
-ref_result = np.array([-135.0, -45.0, 45.0, 135.0], dtype=np.float)
-cmp_result = []
-for i in range(len(x)):
-    cmp_result.append(math.isclose(result[i], ref_result[i], rel_tol=1E-9, abs_tol=1E-9))
-print(cmp_result)
+test_function('acos', np.pi/2, np.acos(np.cos(np.pi/2)))
+
+test_function('atan', np.pi/2, np.atan(np.tan(np.pi/2)))
+
+test_function('acosh', np.pi/2, np.cosh(np.acosh(np.pi/2)))
+
+test_function('asinh', np.pi/2, np.sinh(np.asinh(np.pi/2)))
+
+test_function('degrees', 180.0, np.degrees(np.pi))
+
+test_function('radians', np.pi, np.radians(180.0))
+
+test_function('floor', 3.0, np.floor(np.pi))
+
+test_function('ceil', 4.0, np.ceil(np.pi))
+
+test_function('sqrt', 1.7724538509055159, np.sqrt(np.pi))
+
+test_function('exp', 2.718281828459045, np.exp(1))
+
+test_function('log', 1.0, np.log(2.718281828459045))
+
+test_function('log2', 1.0, np.log2(2))
+
+test_function('log10', 1.0, np.log10(10.0))
+
+test_function('expm1', 1.0, np.exp(1) - np.expm1(1))
+
+x = [-1, +1, +1, -1]
+y = [-1, -1, +1, +1]
+reference = [-135.0, -45.0, 45.0, 135.0]
+for i in range(4):
+     test_function('arctan2', reference[i], np.arctan2(y[i], x[i]) * 180 / np.pi)
 
 x = np.linspace(-2*np.pi, 2*np.pi, 5)
-result = np.sin(x)
-ref_result = np.array([2.4492936e-16, -1.2246468e-16,  0.0000000e+00,  1.2246468e-16, -2.4492936e-16], dtype=np.float)
-cmp_result = []
-for i in range(len(x)):
-    cmp_result.append(math.isclose(result[i], ref_result[i], rel_tol=1E-9, abs_tol=1E-9))
-print(cmp_result)
-
-result = np.cos(x)
-ref_result = np.array([1., -1.,  1., -1.,  1.], dtype=np.float)
-cmp_result = []
-for i in range(len(x)):
-    cmp_result.append(math.isclose(result[i], ref_result[i], rel_tol=1E-9, abs_tol=1E-9))
-print(cmp_result)
-
-result = np.tan(x)
-ref_result = np.array([2.4492936e-16, 1.2246468e-16, 0.0000000e+00, -1.2246468e-16, -2.4492936e-16], dtype=np.float)
-cmp_result = []
-for i in range(len(x)):
-    cmp_result.append(math.isclose(result[i], ref_result[i], rel_tol=1E-9, abs_tol=1E-9))
-print(cmp_result)
-
-result = np.sinh(x)
-ref_result = np.array([-267.74489404, -11.54873936, 0., 11.54873936, 267.74489404], dtype=np.float)
-cmp_result = []
-for i in range(len(x)):
-    cmp_result.append(math.isclose(result[i], ref_result[i], rel_tol=1E-9, abs_tol=1E-9))
-print(cmp_result)    
-
-result  = np.cosh(x)
-ref_result = np.array([267.74676148,  11.59195328, 1.0, 11.59195328, 267.74676148], dtype=np.float)
-cmp_result = []
-for i in range(len(x)):
-    cmp_result.append(math.isclose(result[i], ref_result[i], rel_tol=1E-9, abs_tol=1E-9))
-print(cmp_result)
-
-result = np.tanh(x)
-ref_result = np.array([-0.9999930253396107, -0.99627207622075, 0.0, 0.99627207622075, 0.9999930253396107], dtype=np.float)
-cmp_result = []
-for i in range(len(x)):
-    cmp_result.append(math.isclose(result[i], ref_result[i], rel_tol=1E-9, abs_tol=1E-9))
-print(cmp_result)
-
-result = np.sinc(x)
-ref_result = np.array([0.03935584386392389, -0.04359862862918773, 1.0, -0.04359862862918773, 0.03935584386392389])
-cmp_result = []
-for i in range(len(x)):
-    cmp_result.append(math.isclose(result[i], ref_result[i], rel_tol=1E-9, abs_tol=1E-9))
-print(cmp_result)
-
-result = (spy.special.erf(np.linspace(-3, 3, num=5)))
-ref_result = np.array([-0.9999779095030014, -0.9661051464753108, 0.0, 0.9661051464753108, 0.9999779095030014], dtype=np.float)
-cmp_result = []
-for i in range(len(ref_result)):
-	cmp_result.append(math.isclose(result[i], ref_result[i], rel_tol=1E-9, abs_tol=1E-9))
-print(cmp_result)
-
-result = (spy.special.erfc(np.linspace(-3, 3, num=5)))
-ref_result = np.array([1.99997791e+00, 1.96610515e+00, 1.00000000e+00, 3.38948535e-02, 2.20904970e-05], dtype=np.float)                          
-cmp_result = []
-for i in range(len(ref_result)):
-	cmp_result.append(math.isclose(result[i], ref_result[i], rel_tol=1E-6, abs_tol=1E-6))
-print(cmp_result)
-
-result = (spy.special.gamma(np.array([0, 0.5, 1, 5])))
-ref_result = np.array([1.77245385,  1.0, 24.0])
-cmp_result = []
-cmp_result.append(math.isinf(result[0]))
-for i in range(len(ref_result)):
-	cmp_result.append(math.isclose(result[i+1], ref_result[i], rel_tol=1E-9, abs_tol=1E-9))
-print(cmp_result)
-
-result = (spy.special.gammaln([0, -1, -2, -3, -4]))
-cmp_result = []
-for i in range(len(ref_result)):
-	cmp_result.append(math.isinf(result[i]))
-print(cmp_result)
+
+references = [2.4492936e-16, -1.2246468e-16,  0.0000000e+00,  1.2246468e-16, -2.4492936e-16]
+test_function_array('sin', references, np.sin(x))
+
+references = [1., -1.,  1., -1.,  1.]
+test_function_array('cos', references, np.cos(x))
+
+references = [0.0, 0.0, 0.0, 0.0, 0.0]
+test_function_array('tan', references, np.tan(x))
+
+references = [-267.74489404, -11.54873936, 0., 11.54873936, 267.74489404]
+test_function_array('sinh', references, np.sinh(x))
+
+references = [267.74676148,  11.59195328, 1.0, 11.59195328, 267.74676148]
+test_function_array('cosh', references, np.cosh(x))
+
+references = [-0.9999930253396107, -0.99627207622075, 0.0, 0.99627207622075, 0.9999930253396107]
+test_function_array('tanh', references, np.tanh(x))
+
+references = [0.03935584386392389, -0.04359862862918773, 1.0, -0.04359862862918773, 0.03935584386392389]
+test_function_array('sinc', references, np.sinc(x))
+
+references = [-0.9999779095030014, -0.9661051464753108, 0.0, 0.9661051464753108, 0.9999779095030014]
+test_function_array('erf', references, spy.special.erf(np.linspace(-3, 3, num=5)))
+
+references = [1.99997791e+00, 1.96610515e+00, 1.00000000e+00, 3.38948535e-02, 2.20904970e-05]
+test_function_array('erfc', references, spy.special.erfc(np.linspace(-3, 3, num=5)))
\ No newline at end of file
diff --git a/tests/1d/numpy/universal_functions.py.exp b/tests/1d/numpy/universal_functions.py.exp
index 919c94a4..e6efd3ea 100644
--- a/tests/1d/numpy/universal_functions.py.exp
+++ b/tests/1d/numpy/universal_functions.py.exp
@@ -1,33 +1,102 @@
+testing sin
 True
+
+testing cos
 True
+
+testing tan
 True
+
+testing sinh
 True
+
+testing cosh:
 True
+
+testing tanh
 True
+
+testing asin
 True
+
+testing acos
 True
+
+testing atan
 True
+
+testing acosh
 True
+
+testing asinh
 True
-180.0
-3.141592653589793
-3.0
-4.0
-1.772453850905516
-2.718281828459045
-1.0
-1.0
-1.0
+
+testing degrees
 True
-[True, True, True, True]
+
+testing radians
+True
+
+testing floor
+True
+
+testing ceil
+True
+
+testing sqrt
+True
+
+testing exp
+True
+
+testing log
+True
+
+testing log2
+True
+
+testing log10
+True
+
+testing expm1
+True
+
+testing arctan2
+True
+
+testing arctan2
+True
+
+testing arctan2
+True
+
+testing arctan2
+True
+
+testing sin
 [True, True, True, True, True]
+
+testing cos
 [True, True, True, True, True]
+
+testing tan
 [True, True, True, True, True]
+
+testing sinh
 [True, True, True, True, True]
+
+testing cosh
 [True, True, True, True, True]
+
+testing tanh
 [True, True, True, True, True]
+
+testing sinc
 [True, True, True, True, True]
+
+testing erf
 [True, True, True, True, True]
+
+testing erfc
 [True, True, True, True, True]
-[True, True, True, True]
-[True, True, True]
+
diff --git a/tests/2d/numpy/cholesky.py b/tests/2d/numpy/cholesky.py
index beab3c1d..368005c8 100644
--- a/tests/2d/numpy/cholesky.py
+++ b/tests/2d/numpy/cholesky.py
@@ -1,14 +1,27 @@
 from ulab import numpy as np
 
+import math
+
 a = np.array([[1, 2], [2, 5]])
-print(np.linalg.cholesky(a))
+reference = np.array([[1.0, 0.0], [2.0, 1.0]])
+result = np.linalg.cholesky(a)
+for i in range(2):
+    for j in range(2): 
+        print(f'({i}, {j}): {math.isclose(result[i][j], reference[i][j], rel_tol=1E-6, abs_tol=1E-6)}')
 
-b = a = np.array([[25, 15, -5], [15, 18,  0], [-5,  0, 11]])
-print(np.linalg.cholesky(b))
+b = np.array([[25, 15, -5], [15, 18,  0], [-5,  0, 11]])
+reference = np.array([[5.0, 0.0, 0.0], [3.0, 3.0, 0.0], [-1.0, 1.0, 3.0]])
+result = np.linalg.cholesky(b)
+for i in range(3):
+    for j in range(3): 
+        print(f'({i}, {j}): {math.isclose(result[i][j], reference[i][j], rel_tol=1E-6, abs_tol=1E-6)}')
 
 c = np.array([[18, 22,  54,  42], [22, 70,  86,  62], [54, 86, 174, 134], [42, 62, 134, 106]])
-print(np.linalg.cholesky(c))
-
-
-
-
+reference = np.array([[4.242640687119285, 0.0, 0.0, 0.0],
+       [5.185449728701349, 6.565905201197403, 0.0, 0.0],
+       [12.727922061357857, 3.0460384954008553, 1.6497422479090682, 0.0],
+       [9.899494936611665, 1.6245538642137891, 1.8497110052313865, 1.3926212476455826]])
+result = np.linalg.cholesky(c)
+for i in range(4):
+    for j in range(4): 
+        print(f'({i}, {j}): {math.isclose(result[i][j], reference[i][j], rel_tol=1E-6, abs_tol=1E-6)}')
diff --git a/tests/2d/numpy/cholesky.py.exp b/tests/2d/numpy/cholesky.py.exp
index a8e88ef6..aa2dc3e5 100644
--- a/tests/2d/numpy/cholesky.py.exp
+++ b/tests/2d/numpy/cholesky.py.exp
@@ -1,9 +1,29 @@
-array([[1.0, 0.0],
-       [2.0, 1.0]], dtype=float64)
-array([[5.0, 0.0, 0.0],
-       [3.0, 3.0, 0.0],
-       [-1.0, 1.0, 3.0]], dtype=float64)
-array([[4.242640687119285, 0.0, 0.0, 0.0],
-       [5.185449728701349, 6.565905201197403, 0.0, 0.0],
-       [12.72792206135786, 3.046038495400855, 1.649742247909068, 0.0],
-       [9.899494936611665, 1.624553864213789, 1.849711005231386, 1.392621247645583]], dtype=float64)
+(0, 0): True
+(0, 1): True
+(1, 0): True
+(1, 1): True
+(0, 0): True
+(0, 1): True
+(0, 2): True
+(1, 0): True
+(1, 1): True
+(1, 2): True
+(2, 0): True
+(2, 1): True
+(2, 2): True
+(0, 0): True
+(0, 1): True
+(0, 2): True
+(0, 3): True
+(1, 0): True
+(1, 1): True
+(1, 2): True
+(1, 3): True
+(2, 0): True
+(2, 1): True
+(2, 2): True
+(2, 3): True
+(3, 0): True
+(3, 1): True
+(3, 2): True
+(3, 3): True
diff --git a/tests/2d/numpy/logspace.py b/tests/2d/numpy/logspace.py
index e6f2047b..7fb1ef26 100644
--- a/tests/2d/numpy/logspace.py
+++ b/tests/2d/numpy/logspace.py
@@ -3,8 +3,20 @@
 except:
     import numpy as np
 
-dtypes = (np.uint8, np.int8, np.uint16, np.int16, np.float)
+import math
+
+dtypes = (np.uint8, np.int8, np.uint16, np.int16)
 
 for dtype in dtypes:
     print(np.logspace(0, 10, num=5, endpoint=False, dtype=dtype))
-    print(np.logspace(0, 10, num=5, endpoint=True, dtype=dtype))
\ No newline at end of file
+    print(np.logspace(0, 10, num=5, endpoint=True, dtype=dtype))
+
+
+reference = [1.0, 100.0, 10000.0, 1000000.0, 100000000.0]
+result = np.logspace(0, 10, num=5, endpoint=False, dtype=np.float)
+print([math.isclose(result[i], reference[i], rel_tol=1E-6, abs_tol=1E-6) for i in range(len(reference))])
+
+
+reference = [1.0, 316.22776601683796, 100000.00000000001, 31622776.6016838, 10000000000.000002]
+result = np.logspace(0, 10, num=5, endpoint=True, dtype=np.float)
+print([math.isclose(result[i], reference[i], rel_tol=1E-6, abs_tol=1E-6) for i in range(len(reference))])
diff --git a/tests/2d/numpy/logspace.py.exp b/tests/2d/numpy/logspace.py.exp
index 1a09cef4..5e91bbe8 100644
--- a/tests/2d/numpy/logspace.py.exp
+++ b/tests/2d/numpy/logspace.py.exp
@@ -6,5 +6,5 @@ array([1, 100, 10000, 16960, 57600], dtype=uint16)
 array([1, 316, 34464, 34424, 0], dtype=uint16)
 array([1, 100, 10000, 16960, -7936], dtype=int16)
 array([1, 316, -31072, -31112, 0], dtype=int16)
-array([1.0, 100.0, 10000.0, 1000000.0, 100000000.0], dtype=float64)
-array([1.0, 316.227766016838, 100000.0, 31622776.6016838, 10000000000.0], dtype=float64)
+[True, True, True, True, True]
+[True, True, True, True, True]
diff --git a/tests/2d/numpy/transpose.py b/tests/2d/numpy/transpose.py
new file mode 100644
index 00000000..9ffbfb31
--- /dev/null
+++ b/tests/2d/numpy/transpose.py
@@ -0,0 +1,58 @@
+try:
+    from ulab import numpy as np
+except ImportError:
+    import numpy as np
+
+dtypes = (np.uint8, np.int8, np.uint16, np.int16, np.float)
+
+print("Basic 2D transpose")
+a = np.array(range(6)).reshape((2, 3))
+print("Original array:")
+print(a)
+print("Transposed (no axes):")
+print(a.transpose())
+print()
+
+print("2D transpose with axes=(1, 0)")
+a = np.array(range(6)).reshape((2, 3))
+print("Original array:")
+print(a)
+print("Transposed with axes=(1, 0):")
+print(a.transpose(axes=(1, 0)))
+print()
+
+print("2D transpose with axes=(0, 1)")
+a = np.array(range(6)).reshape((2, 3))
+print("Original array:")
+print(a)
+print("Transposed with axes=(0, 1):")
+print(a.transpose(axes=(0, 1)))
+print()
+
+print("1D array transpose")
+a = np.array(range(5))
+print("Original array:")
+print(a)
+print("Transposed array:")
+print(a.transpose())
+print()
+
+print("Transpose of different dtypes")
+for dtype in dtypes:
+    a = np.array(range(4), dtype=dtype).reshape((2, 2))
+    print('Original array:')
+    print(a)
+    print('Transposed array:')
+    print(a.transpose())
+print()
+
+print(".T property vs transpose() method")
+a = np.array(range(6)).reshape((2, 3))
+print("Original array:")
+print(a)
+print("Using .T property:")
+print(a.T)
+print("Using .transpose():")
+print(a.transpose())
+print("Both should be equal:", np.all(a.T == a.transpose()))
+print()
\ No newline at end of file
diff --git a/tests/2d/numpy/transpose.py.exp b/tests/2d/numpy/transpose.py.exp
new file mode 100644
index 00000000..87627cb2
--- /dev/null
+++ b/tests/2d/numpy/transpose.py.exp
@@ -0,0 +1,78 @@
+Basic 2D transpose
+Original array:
+array([[0.0, 1.0, 2.0],
+       [3.0, 4.0, 5.0]], dtype=float64)
+Transposed (no axes):
+array([[0.0, 3.0],
+       [1.0, 4.0],
+       [2.0, 5.0]], dtype=float64)
+
+2D transpose with axes=(1, 0)
+Original array:
+array([[0.0, 1.0, 2.0],
+       [3.0, 4.0, 5.0]], dtype=float64)
+Transposed with axes=(1, 0):
+array([[0.0, 3.0],
+       [1.0, 4.0],
+       [2.0, 5.0]], dtype=float64)
+
+2D transpose with axes=(0, 1)
+Original array:
+array([[0.0, 1.0, 2.0],
+       [3.0, 4.0, 5.0]], dtype=float64)
+Transposed with axes=(0, 1):
+array([[0.0, 1.0, 2.0],
+       [3.0, 4.0, 5.0]], dtype=float64)
+
+1D array transpose
+Original array:
+array([0.0, 1.0, 2.0, 3.0, 4.0], dtype=float64)
+Transposed array:
+array([0.0, 1.0, 2.0, 3.0, 4.0], dtype=float64)
+
+Transpose of different dtypes
+Original array:
+array([[0, 1],
+       [2, 3]], dtype=uint8)
+Transposed array:
+array([[0, 2],
+       [1, 3]], dtype=uint8)
+Original array:
+array([[0, 1],
+       [2, 3]], dtype=int8)
+Transposed array:
+array([[0, 2],
+       [1, 3]], dtype=int8)
+Original array:
+array([[0, 1],
+       [2, 3]], dtype=uint16)
+Transposed array:
+array([[0, 2],
+       [1, 3]], dtype=uint16)
+Original array:
+array([[0, 1],
+       [2, 3]], dtype=int16)
+Transposed array:
+array([[0, 2],
+       [1, 3]], dtype=int16)
+Original array:
+array([[0.0, 1.0],
+       [2.0, 3.0]], dtype=float64)
+Transposed array:
+array([[0.0, 2.0],
+       [1.0, 3.0]], dtype=float64)
+
+.T property vs transpose() method
+Original array:
+array([[0.0, 1.0, 2.0],
+       [3.0, 4.0, 5.0]], dtype=float64)
+Using .T property:
+array([[0.0, 3.0],
+       [1.0, 4.0],
+       [2.0, 5.0]], dtype=float64)
+Using .transpose():
+array([[0.0, 3.0],
+       [1.0, 4.0],
+       [2.0, 5.0]], dtype=float64)
+Both should be equal: True
+
diff --git a/tests/2d/scipy/integrate.py b/tests/2d/scipy/integrate.py
index 1d0edb7b..2c176c46 100644
--- a/tests/2d/scipy/integrate.py
+++ b/tests/2d/scipy/integrate.py
@@ -1,28 +1,30 @@
-import sys
-from math import *
-
 try:
-    from ulab import scipy
+    from ulab import scipy as spy
+    from ulab import numpy as np
 except ImportError:
     import scipy
 
-f = lambda x: x * sin(x) * exp(x)
-a=1
-b=2
+import math
+
+f = lambda x: x * np.sin(x) * np.exp(x)
+a = 1
+b = 2
 
-(res, err) = scipy.integrate.tanhsinh(f, a, b)
-if isclose (res, 7.11263821415851) and isclose (err, 5.438231077315757e-14):
-	print (res, err)
-		
-res = scipy.integrate.romberg(f, a, b)
-if isclose (res, 7.112638214158507):
-	print (res)
+(res, err) = spy.integrate.tanhsinh(f, a, b)
+print('testing tanhsinh')
+print(math.isclose(res, 7.11263821415851, rel_tol=1E-6, abs_tol=1E-6))
+print()
 
-res = scipy.integrate.simpson(f, a, b)
-if isclose (res, 7.112638214158494):
-	print (res)
+print('testing romberg')
+res = spy.integrate.romberg(f, a, b)
+print(math.isclose(res, 7.112638214158507, rel_tol=1E-6, abs_tol=1E-6))
+print()
 
-(res, err) = scipy.integrate.quad(f, a, b)
-if isclose (res, 7.112638214158507) and isclose (err, 7.686723611780195e-14):
-		print (res, err)
+print('testing simpson')
+res = spy.integrate.simpson(f, a, b)
+print(math.isclose(res, 7.112638214158507, rel_tol=1E-6, abs_tol=1E-6))
+print()
 
+print('testing quad')
+(res, err) = spy.integrate.quad(f, a, b)
+print(math.isclose(res, 7.112638214158507, rel_tol=1E-6, abs_tol=1E-6))
diff --git a/tests/2d/scipy/integrate.py.exp b/tests/2d/scipy/integrate.py.exp
index 10426e6c..d8c790c7 100644
--- a/tests/2d/scipy/integrate.py.exp
+++ b/tests/2d/scipy/integrate.py.exp
@@ -1,4 +1,11 @@
-7.11263821415851 5.438231077315757e-14
-7.112638214158507
-7.112638214158494
-7.112638214158507 7.686723611780195e-14
+testing tanhsinh
+True
+
+testing romberg
+True
+
+testing simpson
+True
+
+testing quad
+True