  Much of the information gleaned from observations of star-forming regions
comes from the analysis of their molecular emission spectra, particularly in
the radio regime. The time-consuming nature of fitting synthetic spectra to
observations interactively for such line-rich sources, however, often results
in such analysis being limited to data extracted from a single-dish observation
or a handful of pixels from an interferometric observation. Yet, star-forming
regions display a wide variety of physical conditions that are difficult, if
not impossible, to accurately characterize with such a limited number of
spectra. We have developed an automated fitting routine that visits every pixel
in the field of view of an ALMA data cube and determines the best-fit physical
parameters, including excitation temperature and column densities, for a given
list of molecules. In this proof-of-concept work, we provide an overview of the
fitting routine and apply it to 0".26, 1.1 km s$^{-1}$ resolution ALMA
observations of two sites of massive star-formation in NGC 6334I. Parameters
were found for 21 distinct molecules by generating synthetic spectra across
7.48 GHz of spectral bandwidth between 280 and 351 GHz. Spatial images of the
derived parameters for each of the > 8000 pixels are presented with special
attention paid to the C$_2$H$_4$O$_2$ isomers and their relative variations. We
highlight the greater scientific utility of the column density and velocity
images of individual molecules compared to traditional moment maps of single
transitions.
