tessFOV will plot the footprint of NASA's TESS Spacecraft pointings on your existing matplotlib.pyplot.Axes objects. tessFOV uses the tess-point package to find the edges of the CCDs for any given pointing, and provides user friendly functions for plotting these footprints.

tessFOV requires Python 3.8 or higher. The full list of module requirements can be found in the pyproject.toml file of this module.

tessFOV has the following functions available:

add_tessfov_outline: Adds outlines for a given sector, camera, CCD
add_tessfov_shade: Adds shaded regions for a given sector, camera, CCD
add_tessfov_text: Adds labels for a given sector, camera, CCD

You can specify any number of sectors [1 ... 69], cameras [1 .. 4], or CCDs [1 .. 4].

Below are a few examples of how to use tessFOV.

Below is an example of how to add the footprint to your existing plot. Here we plot a subset of the sectors from Cycle 1, and plot only the outlines of the CCDs. You can pass matplotlib.pyplot.plot keyword arguments to add_tessfov_outline (e.g. ls, lw, color).

from tessfov import add_tessfov_outline
fig = plt.figure(dpi=150)
ax = plt.subplot(111)
ax.set(xlabel="RA", ylabel="Dec", xlim=(0, 360), ylim=(-90, 90))
add_tessfov_outline(ax, sector=np.arange(1, 14, 3))

Below are a few examples of how to use tessFOV.

You can add the footprint to matplotlib projections (such as the 'hammer' projection). In these cases you must use the wrap_at keyword to ensure that the points "wrap" at 180 degrees. You should also use the unit 'rad' (radians), as this is what is standard for this plotting projection. Below we plot 4 sectors from Cycle 5.

from tessfov import add_tessfov_shade
fig = plt.figure(dpi=150)
ax = plt.subplot(111, projection="hammer")
add_tessfov_shade(
    ax, sector=np.arange(56, 60), unit="rad", wrap_at=180, rasterized=True
)
ax.set(xlabel="RA", ylabel="Dec")
ax.grid(True, ls="--")

Below are a few examples of how to use tessFOV.

You are able to use tessFOV to plot a subset of sectors, cameras and CCDs. Below we plot a single CCD from sector 2, and add a label.

fig = plt.figure(dpi=150)
ax = plt.subplot(111)
ax.set(xlabel="RA", ylabel="Dec", xlim=(330, 360), ylim=(-40, 0))
add_tessfov_outline(ax, sector=2, camera=1, ccd=4, color="grey", ls="--")
add_tessfov_text(ax, sector=2, camera=1, ccd=4, color="grey", fontsize=12)

When adding shaded regions using add_tessfov_shade, you may find that the xlim and ylim of your plot do not update to capture those patches. You should adjust the xlim and ylim parameters of your matplotlib.pyplot.Axes object.

You can install tessFOV using pip:

pip install tessfov --upgrade

You can use this tool to understand maps of completeness across the sky observed by TESS. To make a dataset of the completeness you can use the get_completeness function:

sectors = np.arange(1, 58)
ra, dec, completeness_by_sector = get_completeness(sectors)

completeness_by_sector is then a boolean array with shape Number of Sectors x Number of samples. The array is True where a point in the sky would fall on the detector in a given sector. Using this dataset you can create maps of the sky that look like this: