Merge pull request #8 from barentsen/fix-off-by-one

Fix Off-By-One error in column and row coordinates

pyproject.toml

@@ -47,6 +47,7 @@ dephell = "^0.8.3"
 tess-locator = {path = "../tess-locator", develop = true}
 tess-ephem = {path = "../tess-ephem", develop = true}
 lightkurve = {path = "../lightkurve", develop = true}
+pytest-remotedata = "^0.3.2"
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]

src/tess_cloud/image.py

@@ -272,7 +272,9 @@ async def _find_data_offset(
     async def _find_pixel_offset(self, column: int, row: int) -> int:
         """Returns the byte offset of a specific pixel position."""
         data_offset = await self._find_data_offset(ext=self.data_ext)
-        pixel_offset = column + row * FFI_COLUMNS
+        # Subtract 1 from column and row because the byte location assumes zero-indexing,
+        # whereas the TESS convention is to address column and row number with one-indexing.
+        pixel_offset = (column - 1) + (row - 1) * FFI_COLUMNS
         return data_offset + BYTES_PER_PIX * pixel_offset
 
     async def _find_pixel_blocks(

src/tess_cloud/targetpixelfile.py

@@ -282,7 +282,14 @@ def _create_table_extension(self):
 
         coldefs = fits.ColDefs(cols)
         hdu = fits.BinTableHDU.from_columns(coldefs)
+
+        # Set useful header keywords
         hdu.header["BJDREFI"] = 2457000
+        # Lightkurve relies on 1CRV5P and 2CRV5P to display column/row coordinates in plots
+        if "CORNER_COLUMN" in self._optional_column_data:
+            hdu.header["1CRV5P"] = self._optional_column_data["CORNER_COLUMN"][0]
+        if "CORNER_ROW" in self._optional_column_data:
+            hdu.header["2CRV5P"] = self._optional_column_data["CORNER_ROW"][0]
 
         return hdu
 

tests/test_cutout.py

@@ -1,9 +1,11 @@
 import asyncio
 
 from astropy.io import fits
+import lightkurve as lk
 import numpy as np
+import pytest
 
-from tess_cloud import TessImage
+from tess_cloud import TessImage, list_images
 
 
 def test_cutout():
@@ -33,3 +35,27 @@ def test_cutout():
         img.cutout(column=1, row=1, shape=(1, 3)).flux.round(7)
         == np.array([[-0.0605419], [0.0327947], [-0.0278026]])
     ).all()
+
+
+@pytest.mark.remote_data
+def test_against_tesscut():
+    """Does a cutout from TessCut match TessCloud?"""
+    target = "Pi Men"
+    sector = 31
+    shape = (3, 3)
+    # Download TPF with TessCut
+    tpf_tesscut = lk.search_tesscut(target, sector=sector).download(
+        cutout_size=shape, quality_bitmask=None
+    )
+    # Download TPF with TessCloud
+    imglist = list_images(sector=sector, camera=tpf_tesscut.camera, ccd=tpf_tesscut.ccd)
+    center_column, center_row = (
+        tpf_tesscut.column + 1,
+        tpf_tesscut.row + 1,
+    )  # add +1 to request center of a (3, 3)
+    tpf_tesscloud = imglist[0:2].cutout(
+        column=center_column, row=center_row, shape=shape
+    )
+    # Compare both
+    assert np.all(tpf_tesscut[0].flux == tpf_tesscloud[0].flux)
+    assert np.all(tpf_tesscut[1].flux == tpf_tesscloud[1].flux)