Refactored things to be faster using Numpy arrays

ThermoPyle/ThermoPyle/ThermoPyle.py

@@ -9,6 +9,7 @@
 import json
 from copy import deepcopy
 from itertools import permutations
+# from numba import jit, jitclass, int64, float64, void
 
 import arrow
 import CoolProp.CoolProp as CP
@@ -43,9 +44,9 @@ class ThermoFluid():
 
     Parameters:
         fluid (str): CoolProp Fluid type to use
-        var1 (str): x variable
-        var2 (str): y variable
-        outvar (str): z var (generated by code), normally S, U
+        xvar (str): x variable
+        yvar (str): y variable
+        zvar (str): z var (generated by code), normally S, U
         numPoints (Union[List[int],int]): number of Points for linspaces
         colorMap (str): What color map to use
 
@@ -65,9 +66,9 @@ class ThermoFluid():
 
     def __init__(self,
                  fluid: str="Water",
-                 var1: str="T",
-                 var2: str="P",
-                 outvar: str="S",
+                 xvar: str="T",
+                 yvar: str="P",
+                 zvar: str="S",
                  numPoints: Union[List[int], int]=[217, 217],
                  colorMap: str="viridis"):
 
@@ -77,9 +78,9 @@ def __init__(self,
         else:
             self.numPoints = [numPoints[0], numPoints[1]]
         self.colorMap = colorMap
-        self.xvar = var1
-        self.yvar = var2
-        self.zvar = outvar
+        self.xvar = xvar
+        self.yvar = yvar
+        self.zvar = zvar
         self.vars = [self.xvar, self.yvar, self.zvar]
         self.M = CP.PropsSI("M", self.fluid)
         if "S" in self.vars[:-1]:
@@ -120,39 +121,39 @@ def __init__(self,
 
         # Create a empty list for storing data
         # Then make our data.
-        data = []
+        data = np.empty((0, 3), dtype=float)
 
         if "V" not in self.vars:
             for x in xspace:
                 for y in yspace:
-                    data.append([
+                    data = np.append(data, [[
                         x, y, CP.PropsSI(self.zvar, self.xvar, x, self.yvar, y,
                                          self.fluid)
-                    ])
+                    ]], axis=0)
         elif self.xvar == "V":
             for x in xspace:
                 for y in yspace:
-                    data.append([
+                    data = np.append(data, [[
                         x, y, CP.PropsSI(self.zvar, "D", self.M / x, self.yvar,
                                          y, self.fluid)
-                    ])
+                    ]], axis=0)
         elif self.yvar == "V":
             for x in xspace:
                 for y in yspace:
-                    data.append([
+                    data = np.append(data, [[
                         x, y, CP.PropsSI(self.zvar, self.xvar, x, "D",
                                          self.M / y, self.fluid)
-                    ])
+                    ]], axis=0)
         elif self.zvar == "V":
             for x in xspace:
                 for y in yspace:
-                    data.append([
+                    data = np.append(data, [[
                         x, y, self.M /
                         CP.PropsSI("D", self.xvar, x, self.yvar, y, self.fluid)
-                    ])
+                    ]], axis=0)
 
         # Create Pandas Frame of Data
-        self.data = pd.DataFrame(np.asarray(data), columns=self.vars)
+        self.data = pd.DataFrame(data, columns=self.vars)
         self.make_units()
         self.clean()
         self.make_meta()

ThermoPyle/setup.py

@@ -9,7 +9,7 @@ def readme():
 
 setup(
     name='ThermoPyle',
-    version='0.5.4',
+    version='0.5.5',
     description='Creation of Thermodynamic Surfaces using CoolProp',
     long_description=readme(),
     url='https://github.com/nick5435/thermo-bridge',

docs/source/CSVFluid.rst

@@ -3,5 +3,4 @@ ThermoPyle.CSVFluid
 ###################
 
 .. autoclass:: ThermoPyle.CSVFluid
-        :special-members:
         :members:

docs/source/ThermoFluid.rst

@@ -3,5 +3,4 @@ ThermoPyle.ThermoFluid
 ######################
 
 .. autoclass:: ThermoPyle.ThermoFluid
-        :special-members:
         :members:

docs/source/conf.py

@@ -78,7 +78,7 @@
 # The short X.Y version.
 version = "0.5"
 # The full version, including alpha/beta/rc tags.
-release = "0.5.4"
+release = "0.5.5"
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

notebooks/thermo_generic_library_runner.ipynb

@@ -5,8 +5,8 @@
    "execution_count": 1,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2017-03-06T23:50:49.538057Z",
-     "start_time": "2017-03-06T17:50:43.719121-06:00"
+     "end_time": "2017-03-20T15:46:35.676357Z",
+     "start_time": "2017-03-20T10:46:33.515313-05:00"
     },
     "collapsed": false,
     "deletable": true,
@@ -33,8 +33,8 @@
    "execution_count": 2,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2017-03-06T23:50:58.360063Z",
-     "start_time": "2017-03-06T17:50:50.260062-06:00"
+     "end_time": "2017-03-20T15:46:38.079756Z",
+     "start_time": "2017-03-20T10:46:36.504737-05:00"
     },
     "collapsed": false,
     "deletable": true,
@@ -50,12 +50,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "(46656, 3)\n"
+      "(10000, 3)\n"
      ]
     }
    ],
    "source": [
-    "myfluid = TP.ThermoFluid(\"Water\", \"T\", \"P\", \"U\", [216, 216], \"viridis\")\n",
+    "myfluid = TP.ThermoFluid(fluid=\"Water\", xvar=\"T\", yvar=\"P\", zvar=\"U\")\n",
     "print(myfluid.data.shape)"
    ]
   },

scripts/der_CSV_gen.py

@@ -11,7 +11,8 @@ def make_Time(time):
 
 
 start = timeit.default_timer()
-myfluid = TP.ThermoFluid("Water", "T", "P", "U", [217, 217])
+myfluid = TP.ThermoFluid(fluid="Water", xvar="T",
+                         yvar="P", zvar="U", numPoints=[217, 217])
 
 d_vars = ["U", "T", "P", "S", "D", "G"]
 newCols = {f"d({z})/d({y})|{x}" for x, y, z in permutations(d_vars, 3)