def pdf(self, X):
        X = np.asarray(X)
        return np.exp(-X)/(1+np.exp(-X))**2
Takes a preprocessor define and returns a -D parameter that's ninja- and
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/discrete/discrete_model.py/Logit.pdf--crossover with--dataset/ETHPy150Open adblockplus/gyp/pylib/gyp/generator/ninja.py/Define