class_docstr: A truncated positive exponential continuous random variable.
  
  The probability distribution is::
  
     p(x) ~ c * x + d   between a and b
          = 0             otherwise
  
  The arguments are (a, b, c).  d is set by the normalization
  
  %(before_notes)s
  
  %(example)s
class_docstr_tok: ["A","truncated","positive","exponential","continuous","random","variable",".","The","probability","distribution","is",":",":","p","(","x",")","~","c","*","x","+","d","between","a","and","b","=","0","otherwise","The","arguments","are","(","a",",","b",",","c",")",".","d","is","set","by","the","normalization","%","(","before_notes",")","s","%","(","example",")","s"]
code: def _argcheck(self, a, b, c):
      return (a != b) and not np.isinf(c)
  
file_path: astroML/astroML/stats/random.py
imports: import numpy
  from scipy.stats.distributions import rv_continuous
label_desc: Use image node_id 1 for calling the linear_gen obj's underlying member method code with example usage: obj._argcheck(a, b, c) and returns: unknown