How to do Dose/Response curve fitting in Python for Drug Discovery

doseResponsePython.ipynb

Copied as-is into a new jupyter session, I get the following after assigning fitCompound:

[/var/folders/2s/9l3t4cfj0c5g1s4_7shzc5900000gp/T/ipykernel_19131/1118045928.py:7](http://localhost:8888/var/folders/2s/9l3t4cfj0c5g1s4_7shzc5900000gp/T/ipykernel_19131/1118045928.py#line=6): RuntimeWarning: invalid value encountered in log
  return(c+(d-c)[/](http://localhost:8888/)(1+np.exp(b*(np.log(x)-np.log(e)))))

Then a type error making the lmplot:

TypeError                                 Traceback (most recent call last)
Cell In[81], line 3
      1 refDose = np.linspace(min(drData.logDose)*0.9,max(drData.logDose)*1.1,256)
      2 refDose = (10**-refDose)*1e6
----> 3 sns.lmplot('logDose','response',data=drData,hue='compound',fit_reg=False)
      4 for fit in fitData:
      5     plt.plot([pDose(i) for i in refDose],[ll4(i,*[fit[i] for i in ['b','c','d','e']]) for i in refDose])

TypeError: lmplot() got multiple values for argument 'data'

I have the same problem, anyone found a solution?

@resminer @meeuosh thanks for your patience, the last commit should solve the issue (mixing positional and named arguments is never a good idea!)