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+ ... origin="lower", ... ) >>> _ = ax[0].set_title(f"Airy beam {freqs[0]*1e-6} MHz") - >>> _ = ax[0].set_xlabel("direction cosine l") - >>> _ = ax[0].set_ylabel("direction cosine m") - >>> _ = fig.colorbar(bp_low, ax=ax[0], fraction=0.046, pad=0.04) + >>> _ = fig.colorbar(bp_low, ax=ax[0], fraction=0.046, pad=0.04, location="left") >>> bp_high = ax[1].imshow( ... beam_vals[0,0,-1], ... norm=LogNorm(vmin = 1e-8, vmax =1), ... extent=[np.min(l_arr), np.max(l_arr), np.min(m_arr), np.max(m_arr)], + ... origin="lower", ... ) >>> _ = ax[1].set_title(f"Airy beam {freqs[-1]*1e-6} MHz") - >>> _ = ax[1].set_xlabel("direction cosine l") - >>> _ = ax[1].set_ylabel("direction cosine m") - >>> _ = fig.colorbar(bp_high, ax=ax[1], fraction=0.046, pad=0.04) + >>> _ = fig.colorbar(bp_high, ax=ax[1], fraction=0.046, pad=0.04, location="left") + + >>> for ind in range(2): + ... _ = ax[ind].set_xticks([0], labels=["North"]) + ... _ = ax[ind].set_yticks([0], labels=["East"]) + ... _ = ax[ind].yaxis.set_label_position("right") + ... _ = ax[ind].yaxis.tick_right() + ... _ = ax[ind].xaxis.set_label_position("top") + ... _ = ax[ind].xaxis.tick_top() + >>> fig.tight_layout() >>> plt.show() # doctest: +SKIP >>> plt.savefig("Images/airy_beam.png", bbox_inches='tight') @@ -144,29 +151,46 @@ part, but in general E-Field beams can be complex, so a complex array is returne >>> fig, ax = plt.subplots(2, 2) - >>> be00 = ax[0,0].imshow(beam_vals[0,0,0].real, extent=[np.min(l_arr), np.max(l_arr), np.min(m_arr), np.max(m_arr)]) + >>> be00 = ax[0,0].imshow( + ... beam_vals[0,0,0].real, + ... extent=[np.min(l_arr), np.max(l_arr), np.min(m_arr), np.max(m_arr)], + ... origin="lower", + ... ) >>> _ = ax[0,0].set_title("E/W dipole azimuth response") - >>> _ = ax[0,0].set_xlabel("direction cosine l") - >>> _ = ax[0,0].set_ylabel("direction cosine m") - >>> _ = fig.colorbar(be00, ax=ax[0,0]) + >>> _ = fig.colorbar(be00, ax=ax[0,0], location="left") - >>> be10 = ax[1,0].imshow(beam_vals[1,0,0].real, extent=[np.min(l_arr), np.max(l_arr), np.min(m_arr), np.max(m_arr)]) + >>> be10 = ax[1,0].imshow( + ... beam_vals[1,0,0].real, + ... extent=[np.min(l_arr), np.max(l_arr), np.min(m_arr), np.max(m_arr)], + ... origin="lower", + ... ) >>> _ = ax[1,0].set_title("E/W dipole zenith angle response") - >>> _ = ax[1,0].set_xlabel("direction cosine l") - >>> _ = ax[1,0].set_ylabel("direction cosine m") - >>> _ = fig.colorbar(be00, ax=ax[1,0]) + >>> _ = fig.colorbar(be10, ax=ax[1,0], location="left") - >>> be01 = ax[0,1].imshow(beam_vals[0,1,0].real, extent=[np.min(l_arr), np.max(l_arr), np.min(m_arr), np.max(m_arr)]) + >>> be01 = ax[0,1].imshow( + ... beam_vals[0,1,0].real, + ... extent=[np.min(l_arr), np.max(l_arr), np.min(m_arr), np.max(m_arr)], + ... origin="lower", + ... ) >>> _ = ax[0,1].set_title("N/S dipole azimuth response") - >>> _ = ax[0,1].set_xlabel("direction cosine l") - >>> _ = ax[0,1].set_ylabel("direction cosine m") - >>> _ = fig.colorbar(be00, ax=ax[0,1]) + >>> _ = fig.colorbar(be01, ax=ax[0,1], location="left") - >>> be11 = ax[1,1].imshow(beam_vals[1,1,0].real, extent=[np.min(l_arr), np.max(l_arr), np.min(m_arr), np.max(m_arr)]) + >>> be11 = ax[1,1].imshow( + ... beam_vals[1,1,0].real, + ... extent=[np.min(l_arr), np.max(l_arr), np.min(m_arr), np.max(m_arr)], + ... origin="lower", + ... ) >>> _ = ax[1,1].set_title("N/S dipole zenith angle response") - >>> _ = ax[1,1].set_xlabel("direction cosine l") - >>> _ = ax[1,1].set_ylabel("direction cosine m") - >>> _ = fig.colorbar(be00, ax=ax[1,1]) + >>> _ = fig.colorbar(be11, ax=ax[1,1], location="left") + + >>> for row_ind in range(2): + ... for col_ind in range(2): + ... _ = ax[row_ind,col_ind].set_xticks([0], labels=["North"]) + ... _ = ax[row_ind,col_ind].set_yticks([0], labels=["East"]) + ... _ = ax[row_ind,col_ind].yaxis.set_label_position("right") + ... _ = ax[row_ind,col_ind].yaxis.tick_right() + ... _ = ax[row_ind,col_ind].xaxis.set_label_position("top") + ... _ = ax[row_ind,col_ind].xaxis.tick_top() >>> fig.tight_layout() >>> plt.show() # doctest: +SKIP diff --git a/docs/beam_interface_tutorial.rst b/docs/beam_interface_tutorial.rst index 7788a5943d..86cc2bc391 100644 --- a/docs/beam_interface_tutorial.rst +++ b/docs/beam_interface_tutorial.rst @@ -79,21 +79,28 @@ that is attached to it is an analytic beam or a UVBeam. ... dipole_beam_vals[0].real, ... norm=LogNorm(vmin = 1e-4, vmax =1), ... extent=[np.min(l_arr), np.max(l_arr), np.min(m_arr), np.max(m_arr)], + ... origin="lower", ... ) >>> _ = ax[0].set_title(f"E/W Dipole power beam") - >>> _ = ax[0].set_xlabel("direction cosine l") - >>> _ = ax[0].set_ylabel("direction cosine m") - >>> _ = fig.colorbar(bp_dip, ax=ax[0], fraction=0.046, pad=0.04) + >>> _ = fig.colorbar(bp_dip, ax=ax[0], fraction=0.046, pad=0.04, location="left") >>> bp_mwa = ax[1].imshow( ... mwa_beam_vals[0].real, ... norm=LogNorm(vmin = 1e-4, vmax =1), ... extent=[np.min(l_arr), np.max(l_arr), np.min(m_arr), np.max(m_arr)], + ... origin="lower", ... ) >>> _ = ax[1].set_title(f"MWA E/W power beam") - >>> _ = ax[1].set_xlabel("direction cosine l") - >>> _ = ax[1].set_ylabel("direction cosine m") - >>> _ = fig.colorbar(bp_mwa, ax=ax[1], fraction=0.046, pad=0.04) + >>> _ = fig.colorbar(bp_mwa, ax=ax[1], fraction=0.046, pad=0.04, location="left") + + >>> for ind in range(2): + ... _ = ax[ind].set_xticks([0], labels=["North"]) + ... _ = ax[ind].set_yticks([0], labels=["East"]) + ... _ = ax[ind].yaxis.set_label_position("right") + ... _ = ax[ind].yaxis.tick_right() + ... _ = ax[ind].xaxis.set_label_position("top") + ... _ = ax[ind].xaxis.tick_top() + >>> fig.tight_layout() >>> plt.show() # doctest: +SKIP >>> plt.savefig("Images/dipole_mwa_power.png", bbox_inches='tight') diff --git a/docs/uvdata_tutorial.rst b/docs/uvdata_tutorial.rst index c7a1ca740a..bac35351db 100644 --- a/docs/uvdata_tutorial.rst +++ b/docs/uvdata_tutorial.rst @@ -919,7 +919,7 @@ Note: there is now support for reading in only part of a uvfits, uvh5 or miriad >>> # Amplitude waterfall for all spectral channels and 0th polarization >>> fig, ax = plt.subplots(1, 1) - >>> _ = ax.imshow(np.abs(waterfall_data), interpolation='none') + >>> _ = ax.imshow(np.abs(waterfall_data), interpolation='none', origin="lower") >>> _ = ax.set_yticks([0, waterfall_times.size - 1]) >>> _ = ax.set_yticklabels([waterfall_times[0], waterfall_times[1]]) >>> freq_tick_inds = np.concatenate((np.arange(0, uvd.Nfreqs, 16), [uvd.Nfreqs-1]))