Dev

tessreduce/R_load.py

@@ -1,59 +1,110 @@
 import numpy as np
 
-R_ps1 = {'g': {'coeff': [ 3.61562687, -0.0891928 ],
-		  	   'std': 0.004146827352467696},
-		 'r': {'coeff': [ 2.58602003, -0.03325315],
-		 	   'std': 0.0010620316190595924},
-		 'i': {'coeff': [ 1.90959054, -0.01284678],
-		  	   'std': 0.0004962971568272631},
-		 'z': {'coeff': [ 1.50168735, -0.0045642 ],
-		  	   'std': 0.0014331914679903046},
-		 'y': {'coeff': [ 1.25340149, -0.00247802],
-		  	   'std': 0.0005840472105137083},
-		 'kep': {'coeff': [ 2.68629375, -0.26884456],
-		  	     'std': 0.0020136674269240393},
-		 'tess': {'coeff': [ 1.902, -0.179],
-		  	   	  'std': 0.0028265468011445124}
-	  	}
+# Dictionary of Pan Stars 1 R values
+R_ps1 = {'g': {'coeff': [3.61562687, -0.0891928],
+               'std': 0.004146827352467696},
+         'r': {'coeff': [2.58602003, -0.03325315],
+               'std': 0.0010620316190595924},
+         'i': {'coeff': [1.90959054, -0.01284678],
+               'std': 0.0004962971568272631},
+         'z': {'coeff': [1.50168735, -0.0045642],
+               'std': 0.0014331914679903046},
+         'y': {'coeff': [1.25340149, -0.00247802],
+               'std': 0.0005840472105137083},
+         'kep': {'coeff': [2.68629375, -0.26884456],
+                 'std': 0.0020136674269240393},
+         'tess': {'coeff': [1.902, -0.179],
+                  'std': 0.0028265468011445124}
+         }
 
+
+# Dictionary of Skymapper R values
 R_sm = {'u': {'coeff': [4.902198196976004, -0.04396865635703249],
-	    	  'std': 0.005212225623300655},
-	    'v': {'coeff': [4.553419148586131, -0.03096904487746069],
-	    	  'std': 0.015102362684553196},
-	    'g': {'coeff': [3.434788880230338, -0.17247389098523408],
-	    	  'std': 0.0019526614969365428},
-	    'r': {'coeff': [2.6377280770536853, -0.07696556583546744],
-	    	  'std': 0.0016588895668870856},
-	    'i': {'coeff': [1.8190330572341713, -0.01977796422745485],
-	    	  'std': 0.0008544792739952313},
-	    'z': {'coeff': [1.3827366254049507, -0.017314195591388342],
-	     	  'std': 0.003027218953684425},
-	    'tess': {'coeff': [ 1.902, -0.179],
-	     	     'std': 0.0028265468011445124}
- 	    }
-
-
-def line(x, c1, c2): 
-    return c1 + c2*x
-
-def R_val(band,g=None,r=None,gr=None,ext=0,system='ps1'):
-	if system.lower() == 'ps1':
-		R = R_ps1
-	elif system.lower() == 'skymapper':
-		R = R_sm
-	if (g is not None) & (r is not None):
-		gr = g-r
-
-	if (gr is None) | np.isnan(gr).all():
-		Rb   = R[band]['coeff'][1]
-	else:
-		Rr0 = R[band]['coeff'][1]
-		Rg0 = R[band]['coeff'][1]
-
-		gr_int = gr - ext*(Rg0 - Rr0)
-
-		vals = R[band]['coeff']
-		Rb  = line(gr_int,vals[0],vals[1])
-	Rb_e = R[band]['std']
-
-	return Rb, Rb_e
+              'std': 0.005212225623300655},
+        'v': {'coeff': [4.553419148586131, -0.03096904487746069],
+              'std': 0.015102362684553196},
+        'g': {'coeff': [3.434788880230338, -0.17247389098523408],
+              'std': 0.0019526614969365428},
+        'r': {'coeff': [2.6377280770536853, -0.07696556583546744],
+              'std': 0.0016588895668870856},
+        'i': {'coeff': [1.8190330572341713, -0.01977796422745485],
+              'std': 0.0008544792739952313},
+        'z': {'coeff': [1.3827366254049507, -0.017314195591388342],
+              'std': 0.003027218953684425},
+        'tess': {'coeff': [1.902, -0.179],
+                 'std': 0.0028265468011445124}
+        }
+
+
+def line(x, c1, c2):
+    """
+    Makes a line based on a y-intercept and a slope:
+
+    y = c1 + c2*x
+    -------------
+
+    Paramters:
+    ---------
+    x: array_like  
+            An array of x values to be turned into points on the line.
+    c1: float
+            The y-intercept of the line.  
+    c2: float
+            The slope of the line.
+
+    Returns:
+    -------
+    this_line: array_like
+            The line from the specified parameters, the same shape as x. 
+    """
+    this_line = c1+c2*x
+    return this_line
+
+
+def R_val(band, g=None, r=None, gr=None, ext=0, system='ps1'):
+    """
+    Calcuates the R values based on the system that is used. 
+
+    Parameters:
+    ----------
+    band: str
+            The band that the extinction should be calculated for.
+    g: float, optional
+            The g mag of the object. Default is None.
+    r:
+            The r mag of the object. Default is None.
+    gr: float, optional
+            The g-r colour of the object, is superseeded by g-r if g and r are given. Default is None.
+    ext: int
+            Default is 0.
+    system: str
+            Values checked for are 'ps1' and 'skymapper'. Other strings should not be used. Default is 'ps1'.
+
+    Returns:
+    -------
+    Rb:
+            The R value through the band, from known dictionaries.
+    Rb_e:
+            The standard deviation of Rb, from known dictionaries.. 
+
+    """
+    if system.lower() == 'ps1':
+        R = R_ps1
+    elif system.lower() == 'skymapper':
+        R = R_sm
+    if (g is not None) & (r is not None):
+        gr = g-r
+
+    if (gr is None) | np.isnan(gr).all():
+        Rb = R[band]['coeff'][1]
+    else:
+        Rr0 = R[band]['coeff'][1]
+        Rg0 = R[band]['coeff'][1]
+
+        gr_int = gr - ext*(Rg0 - Rr0)
+
+        vals = R[band]['coeff']
+        Rb = line(gr_int, vals[0], vals[1])
+    Rb_e = R[band]['std']
+
+    return Rb, Rb_e