diff options
Diffstat (limited to 'lib/dfatool.py')
| -rwxr-xr-x | lib/dfatool.py | 14 |
1 files changed, 7 insertions, 7 deletions
diff --git a/lib/dfatool.py b/lib/dfatool.py index dd8e288..76bf51a 100755 --- a/lib/dfatool.py +++ b/lib/dfatool.py @@ -547,7 +547,7 @@ class analytic: _num0_16 = np.vectorize(lambda x: 16 - bin(int(x)).count("1")) _num1 = np.vectorize(lambda x: bin(int(x)).count("1")) _safe_log = np.vectorize(lambda x: np.log(np.abs(x)) if np.abs(x) > 0.001 else 1.) - _safe_frac = np.vectorize(lambda x: 1 / x if np.abs(x) > 0.001 else 1.) + _safe_inv = np.vectorize(lambda x: 1 / x if np.abs(x) > 0.001 else 1.) _safe_sqrt = np.vectorize(lambda x: np.sqrt(np.abs(x))) _function_map = { @@ -556,13 +556,13 @@ class analytic: 'logarithmic1' : lambda x: np.log(x + 1), 'exponential' : np.exp, 'square' : lambda x : x ** 2, - 'fractional' : lambda x : 1 / x, + 'inverse' : lambda x : 1 / x, 'sqrt' : np.sqrt, 'num0_8' : _num0_8, 'num0_16' : _num0_16, 'num1' : _num1, 'safe_log' : lambda x: np.log(np.abs(x)) if np.abs(x) > 0.001 else 1., - 'safe_frac' : lambda x: 1 / x if np.abs(x) > 0.001 else 1., + 'safe_inv' : lambda x: 1 / x if np.abs(x) > 0.001 else 1., 'safe_sqrt': lambda x: np.sqrt(np.abs(x)), } @@ -594,7 +594,7 @@ class analytic: lambda model_param: True, 2 ), - 'fractional' : ParamFunction( + 'inverse' : ParamFunction( lambda reg_param, model_param: reg_param[0] + reg_param[1] / model_param, lambda model_param: model_param != 0, 2 @@ -627,8 +627,8 @@ class analytic: lambda model_param: True, 2 ) - functions['safe_frac'] = ParamFunction( - lambda reg_param, model_param: reg_param[0] + reg_param[1] * analytic._safe_frac(model_param), + functions['safe_inv'] = ParamFunction( + lambda reg_param, model_param: reg_param[0] + reg_param[1] * analytic._safe_inv(model_param), lambda model_param: True, 2 ) @@ -654,7 +654,7 @@ class analytic: return 'np.exp({})'.format(ref_str) if function_type == 'square': return '({})**2'.format(ref_str) - if function_type == 'fractional': + if function_type == 'inverse': return '1/({})'.format(ref_str) if function_type == 'sqrt': return 'np.sqrt({})'.format(ref_str) |