Fix representation of bools

Changed "True" from 1 to -1 to match Eclipse binary file format.

src/ecl_data_io/_unformatted/read.py

@@ -121,7 +121,7 @@ def _read(self):
         self._read_record_marker(16)
         if self._type == b"X231":
             self._read_record_marker(16)
-            self._length *= -(2 ** 31)
+            self._length *= -(2**31)
             previous_keyword = self._keyword
             self._read_keyword()
             if previous_keyword != self._keyword:

src/ecl_data_io/_unformatted/write.py

@@ -15,9 +15,9 @@ def write_array_header(stream, kw_str, type_str, size):
     if not ecl_types.is_valid_type(type_str):
         raise EclWriteError(f"Not a valid ecl type: {type_str}")
 
-    if size > 2 ** 31:
-        write_array_header(stream, kw_str, b"X231", -(size // (2 ** 31)))
-        size %= 2 ** 31
+    if size > 2**31:
+        write_array_header(stream, kw_str, b"X231", -(size // (2**31)))
+        size %= 2**31
 
     stream.write((16).to_bytes(4, byteorder="big", signed=True))
     stream.write(kw_str.encode("ascii"))
@@ -30,7 +30,7 @@ def cast_array_to_ecl(arr):
     if arr.dtype in [np.int32, np.float32, np.float64]:
         return arr.astype(arr.dtype.newbyteorder(">"))
     if np.issubdtype(arr.dtype, np.bool_):
-        return arr.astype(">i4")
+        return -arr.astype(">i4")
     elif np.issubdtype(arr.dtype, np.integer):
         result_dtype = ">i4"
     elif np.issubdtype(arr.dtype, np.floating):

tests/test_unformatted_write.py

@@ -55,7 +55,7 @@ def test_write_array_header_not_a_type():
         (np.array([1], dtype=np.int32), np.array([1], dtype=np.int32)),
         (np.array([1.0], dtype=np.float32), np.array([1.0], dtype=np.float32)),
         (np.array([1.0], dtype=np.float64), np.array([1.0], dtype=np.float64)),
-        (np.array([True, False], dtype=np.bool_), np.array([1, 0], dtype=np.int32)),
+        (np.array([True, False], dtype=np.bool_), np.array([-1, 0], dtype=np.int32)),
         (np.array([10, 20], dtype=np.int8), np.array([10, 20], dtype=np.int32)),
         (np.array([1.0], dtype=np.float128), np.array([1.0], dtype=np.float64)),
     ],