Set the grid for the rectangle boundaries, and the data values. Parameters ---------- x, y : 1D array-like, optional Monotonic arrays of length N+1 and M+1, respectively, specifying rectangle boundaries. If not given, will default to
(self, x, y, A)
| 1290 | return False |
| 1291 | |
| 1292 | def set_data(self, x, y, A): |
| 1293 | """ |
| 1294 | Set the grid for the rectangle boundaries, and the data values. |
| 1295 | |
| 1296 | Parameters |
| 1297 | ---------- |
| 1298 | x, y : 1D array-like, optional |
| 1299 | Monotonic arrays of length N+1 and M+1, respectively, specifying |
| 1300 | rectangle boundaries. If not given, will default to |
| 1301 | ``range(N + 1)`` and ``range(M + 1)``, respectively. |
| 1302 | A : array-like |
| 1303 | The data to be color-coded. The interpretation depends on the |
| 1304 | shape: |
| 1305 | |
| 1306 | - (M, N) `~numpy.ndarray` or masked array: values to be colormapped |
| 1307 | - (M, N, 3): RGB array |
| 1308 | - (M, N, 4): RGBA array |
| 1309 | """ |
| 1310 | A = self._normalize_image_array(A) |
| 1311 | x = np.arange(0., A.shape[1] + 1) if x is None else np.array(x, float).ravel() |
| 1312 | y = np.arange(0., A.shape[0] + 1) if y is None else np.array(y, float).ravel() |
| 1313 | if A.shape[:2] != (y.size - 1, x.size - 1): |
| 1314 | raise ValueError( |
| 1315 | "Axes don't match array shape. Got %s, expected %s." % |
| 1316 | (A.shape[:2], (y.size - 1, x.size - 1))) |
| 1317 | # For efficient cursor readout, ensure x and y are increasing. |
| 1318 | if x[-1] < x[0]: |
| 1319 | x = x[::-1] |
| 1320 | A = A[:, ::-1] |
| 1321 | if y[-1] < y[0]: |
| 1322 | y = y[::-1] |
| 1323 | A = A[::-1] |
| 1324 | self._A = A |
| 1325 | self._Ax = x |
| 1326 | self._Ay = y |
| 1327 | self._imcache = None |
| 1328 | self.stale = True |
| 1329 | |
| 1330 | def set_array(self, *args): |
| 1331 | raise NotImplementedError('Method not supported') |
no test coverage detected