diff --git a/examples/inverse-calculations.py b/examples/inverse-calculations.py
index a2f9337..4fe5ad9 100644
--- a/examples/inverse-calculations.py
+++ b/examples/inverse-calculations.py
@@ -1,12 +1,23 @@
 # %%
 import csv
 from copy import deepcopy
-import numpy as np
+from typing import Dict, List
+from pathlib import Path
+
+from numpy import linspace
 from scipy import optimize
+from jinja2 import Environment, FileSystemLoader
 
 from koozie import fr_u
 
-from dimes import MarkersOnly, LinesOnly, DimensionalPlot, DisplayData, DimensionalData
+from dimes import (
+    LineProperties,
+    MarkersOnly,
+    LinesOnly,
+    DimensionalPlot,
+    DisplayData,
+    DimensionalData,
+)
 
 
 from resdx.util import (
@@ -19,6 +30,7 @@
     # quartic,
     # quartic_string,
     calculate_r_squared,
+    geometric_space,
 )
 
 import resdx
@@ -36,11 +48,14 @@ def __init__(self, function, regression_string, initial_coefficient_guesses):
 
 
 class RatingRegression:
+
+    input_data: List[List[float]]
+
     def __init__(
         self,
         staging_type: resdx.StagingType,
         calculation,
-        target_title: str,
+        input_title: str,
         initial_guess,
         rating_range: DisplayData,
         secondary_range: DisplayData,
@@ -48,14 +63,20 @@ def __init__(
     ):
         self.staging_type = staging_type
         self.calculation = calculation
-        self.target_title = target_title
+        self.input_title = input_title
         self.initial_guess = initial_guess
         self.rating_range = rating_range
         self.secondary_range = secondary_range
         self.curve_fit = curve_fit
 
-    def evaluate(self, output_name):
+    def evaluate(self, output_name, do_curve_fit=False):
         display_data = []
+        csv_output_data = {
+            self.rating_range.name: [],
+            self.secondary_range.name: [],
+            self.input_title: [],
+        }
+        self.input_data = []
         for secondary_value in self.secondary_range.data_values:
             series_name = f"{self.secondary_range.name}={secondary_value:.2}"
 
@@ -69,6 +90,7 @@ def evaluate(self, output_name):
                     self.initial_guess,
                     curve_fit_function=self.curve_fit.function,
                     curve_fit_guesses=self.curve_fit.initial_coefficient_guesses,
+                    do_curve_fit=do_curve_fit,
                 )
             except RuntimeError as e:
                 raise RuntimeError(
@@ -80,34 +102,69 @@ def evaluate(self, output_name):
                     inputs,
                     name=series_name,
                     native_units="W/W",
-                    line_properties=MarkersOnly(),
+                    line_properties=MarkersOnly() if do_curve_fit else LineProperties(),
                 )
             )
-            curve_fit_string = self.curve_fit.regression_string(
-                self.rating_range.name, *coefficients
-            )
-            curve_fit_data = [
-                self.curve_fit.function(rating, *coefficients)
-                for rating in self.rating_range.data_values
-            ]
-            r2 = calculate_r_squared(inputs, curve_fit_data)
-            display_data.append(
-                DisplayData(
-                    curve_fit_data,
-                    name=f"{series_name}: {curve_fit_string}, R2={r2:.4g}",
-                    native_units="W/W",
-                    line_properties=LinesOnly(),
+            if do_curve_fit:
+                curve_fit_string = self.curve_fit.regression_string(
+                    self.rating_range.name, *coefficients
+                )
+                curve_fit_data = [
+                    self.curve_fit.function(rating, *coefficients)
+                    for rating in self.rating_range.data_values
+                ]
+                r2 = calculate_r_squared(inputs, curve_fit_data)
+                display_data.append(
+                    DisplayData(
+                        curve_fit_data,
+                        name=f"{series_name}: {curve_fit_string}, R2={r2:.4g}",
+                        native_units="W/W",
+                        line_properties=LinesOnly(),
+                    )
                 )
-            )
-
-        plot(self.rating_range, display_data, self.target_title, output_name)
-
 
-def plot(x, ys, y_axis_name, figure_name):
-    plot = DimensionalPlot(x)
-    for y in ys:
-        plot.add_display_data(y, axis_name=y_axis_name)
-    plot.write_html_plot(f"output/{figure_name}.html")
+            csv_output_data[self.rating_range.name] += list(
+                self.rating_range.data_values
+            )
+            csv_output_data[self.secondary_range.name] += [secondary_value] * len(
+                self.rating_range.data_values
+            )
+            csv_output_data[self.input_title] += inputs
+            self.input_data.append(inputs)
+
+        self.plot(display_data, output_name)
+
+        self.write_csv(csv_output_data, output_name)
+
+    def plot(self, display_data_list, figure_name):
+        plot = DimensionalPlot(self.rating_range)
+        for y in display_data_list:
+            plot.add_display_data(y, axis_name=self.input_title)
+        plot.write_html_plot(f"output/{figure_name}.html")
+
+    def write_csv(self, column_dictionary: Dict[str, List[float]], table_name: str):
+        with open(f"output/{table_name}-points.csv", "w", encoding="utf-8") as csv_file:
+            writer = csv.writer(csv_file)
+            key_list = list(column_dictionary.keys())
+            writer.writerow(key_list)
+            for index in range(len(column_dictionary[key_list[0]])):
+                writer.writerow([column_dictionary[key][index] for key in key_list])
+
+    def write_csv2(self, table_name: str, write_mode: str = "w"):
+        with open(
+            f"output/{table_name}-table.csv", write_mode, encoding="utf-8"
+        ) as csv_file:
+            writer = csv.writer(csv_file)
+            writer.writerow(
+                [f"{self.staging_type.name} {self.input_title}", self.rating_range.name]
+            )
+            writer.writerow(
+                [self.secondary_range.name] + list(self.rating_range.data_values)
+            )
+            for index, rating_value in enumerate(self.secondary_range.data_values):
+                writer.writerow([rating_value] + self.input_data[index])
+            if write_mode == "a":
+                writer.writerow(["", ""])
 
 
 def make_objective_function(comparison, target):
@@ -120,6 +177,7 @@ def get_inverse_values(
     initial_guess=lambda x: x / 3.0,
     curve_fit_function=quadratic,
     curve_fit_guesses=(1, 1, 1),
+    do_curve_fit=False,
 ):
     inverse_values = []
     for target in target_range.data_values:
@@ -135,10 +193,16 @@ def get_inverse_values(
             raise RuntimeError(
                 f"Unable to find solution for target: {target_range.name}={target}."
             )
-    print(f"    curve fitting...")
-    curve_fit_coefficients = optimize.curve_fit(
-        curve_fit_function, target_range.data_values, inverse_values, curve_fit_guesses
-    )[0]
+    if do_curve_fit:
+        print(f"    curve fitting...")
+        curve_fit_coefficients = optimize.curve_fit(
+            curve_fit_function,
+            target_range.data_values,
+            inverse_values,
+            curve_fit_guesses,
+        )[0]
+    else:
+        curve_fit_coefficients = None
     return inverse_values, curve_fit_coefficients
 
 
@@ -149,32 +213,32 @@ def seer_function(cop_82_min, seer, staging_type, seer_eer_ratio):
         input_seer=seer,
         input_eer=seer / seer_eer_ratio,
         rated_net_total_cooling_cop_82_min=cop_82_min,
-        input_hspf=10.0,
+        input_hspf=7.5,  # TODO: Change to 7.5
     ).seer()
 
 
 two_speed_cooling_regression = RatingRegression(
     staging_type=resdx.StagingType.TWO_STAGE,
     calculation=seer_function,
-    target_title="Net COP (at B low conditions)",
+    input_title="Net COP (at B low conditions)",
     initial_guess=lambda target: target / 3.0,
     rating_range=DimensionalData(
-        np.linspace(6, 26.5, 2), name="SEER2", native_units="Btu/Wh"
+        list(linspace(6, 26.5, 2)), name="SEER2", native_units="Btu/Wh"
     ),  # All straight lines don't need more than two points
     secondary_range=DimensionalData(
-        np.linspace(1.2, 2.0, 10), name="SEER2/EER2", native_units="W/W"
-    ),
+        list(linspace(1.2, 2.0, 2)), name="SEER2/EER2", native_units="W/W"
+    ),  # Also straight line
     curve_fit=linear_curve_fit,
 )
 
 variable_speed_cooling_regression = deepcopy(two_speed_cooling_regression)
 variable_speed_cooling_regression.staging_type = resdx.StagingType.VARIABLE_SPEED
 variable_speed_cooling_regression.rating_range = DimensionalData(
-    np.linspace(14, 35, 3), name="SEER2", native_units="Btu/Wh"
-)
-
-# two_speed_cooling_regression.evaluate("cooling-two-speed-cop82-v-seer")
-# variable_speed_cooling_regression.evaluate("cooling-variable-speed-cop82-v-seer")
+    list(linspace(14, 35, 3)), name="SEER2", native_units="Btu/Wh"
+)  # Slight inflection, three points should suffice
+variable_speed_cooling_regression.secondary_range = DimensionalData(
+    list(geometric_space(1.2, 2.0, 5, 0.5)), name="SEER2/EER2", native_units="W/W"
+)  # Exponential variation 5 values
 
 
 # Heating
@@ -185,21 +249,21 @@ def hspf_function(cop_47, hspf, staging_type, cap17m):
         rated_net_heating_capacity_17=fr_u(3.0, "ton_ref") * cap17m,
         rated_net_heating_cop=cop_47,
         input_hspf=hspf,
-        input_seer=19.0,
-        input_eer=10.0,
+        input_seer=14.3,
+        input_eer=11.0,
     ).hspf()
 
 
 single_speed_heating_regression = RatingRegression(
     staging_type=resdx.StagingType.SINGLE_STAGE,
     calculation=hspf_function,
-    target_title="Net COP (at H1 full conditions)",
+    input_title="Net COP (at H1 full conditions)",
     initial_guess=lambda target: target / 2.0,
     rating_range=DimensionalData(
-        np.linspace(5, 11, 5), name="HSPF2", native_units="Btu/Wh"
+        list(linspace(5, 11, 5)), name="HSPF2", native_units="Btu/Wh"
     ),
     secondary_range=DimensionalData(
-        [0.5, 0.55, 0.6, 0.7, 0.8, 1.1], name="Q17/Q47", native_units="Btu/Btu"
+        list(geometric_space(0.5, 1.1, 5, 2.0)), name="Q17/Q47", native_units="Btu/Btu"
     ),
     curve_fit=quadratic_curve_fit,
 )
@@ -209,10 +273,35 @@ def hspf_function(cop_47, hspf, staging_type, cap17m):
 
 variable_speed_heating_regression = deepcopy(single_speed_heating_regression)
 variable_speed_heating_regression.staging_type = resdx.StagingType.VARIABLE_SPEED
-variable_speed_cooling_regression.rating_range = DimensionalData(
-    np.linspace(5, 16, 5), name="HSPF2", native_units="Btu/Wh"
+variable_speed_heating_regression.rating_range = DimensionalData(
+    list(linspace(7, 16, 5)), name="HSPF2", native_units="Btu/Wh"
 )
 
+two_speed_cooling_regression.evaluate("cooling-two-speed-cop82-v-seer")
+variable_speed_cooling_regression.evaluate("cooling-variable-speed-cop82-v-seer")
 single_speed_heating_regression.evaluate("heating-single-speed-cop47-v-hspf")
 two_speed_heating_regression.evaluate("heating-two-speed-cop47-v-hspf")
 variable_speed_heating_regression.evaluate("heating-variable-speed-cop47-v-hspf")
+
+two_speed_cooling_regression.write_csv2("regressions")
+variable_speed_cooling_regression.write_csv2("regressions", "a")
+single_speed_heating_regression.write_csv2("regressions", "a")
+two_speed_heating_regression.write_csv2("regressions", "a")
+variable_speed_heating_regression.write_csv2("regressions", "a")
+
+# Write python file
+SOURCE_PATH = Path("resdx", "models")
+FILE_NAME = "rating_correlations.py"
+template_environment = Environment(loader=FileSystemLoader(SOURCE_PATH))
+template = template_environment.get_template(f"{FILE_NAME}.jinja")
+
+content = template.render(
+    heating_1s=single_speed_heating_regression,
+    heating_2s=two_speed_heating_regression,
+    heating_vs=variable_speed_heating_regression,
+    cooling_2s=two_speed_cooling_regression,
+    cooling_vs=variable_speed_cooling_regression,
+)
+
+with open(Path(SOURCE_PATH, FILE_NAME), mode="w", encoding="utf-8") as python_file:
+    python_file.write(content)
diff --git a/poetry.lock b/poetry.lock
index 5ffd633..8c67bee 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -148,33 +148,33 @@ test = ["pytest"]
 
 [[package]]
 name = "debugpy"
-version = "1.8.1"
+version = "1.8.2"
 description = "An implementation of the Debug Adapter Protocol for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "debugpy-1.8.2.zip", hash = "sha256:95378ed08ed2089221896b9b3a8d021e642c24edc8fef20e5d4342ca8be65c00"},
 ]
 
 [[package]]
@@ -227,13 +227,13 @@ toml = ["tomli"]
 
 [[package]]
 name = "exceptiongroup"
-version = "1.2.1"
+version = "1.2.2"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "exceptiongroup-1.2.1-py3-none-any.whl", hash = "sha256:5258b9ed329c5bbdd31a309f53cbfb0b155341807f6ff7606a1e801a891b29ad"},
-    {file = "exceptiongroup-1.2.1.tar.gz", hash = "sha256:a4785e48b045528f5bfe627b6ad554ff32def154f42372786903b7abcfe1aa16"},
+    {file = "exceptiongroup-1.2.2-py3-none-any.whl", hash = "sha256:3111b9d131c238bec2f8f516e123e14ba243563fb135d3fe885990585aa7795b"},
+    {file = "exceptiongroup-1.2.2.tar.gz", hash = "sha256:47c2edf7c6738fafb49fd34290706d1a1a2f4d1c6df275526b62cbb4aa5393cc"},
 ]
 
 [package.extras]
@@ -255,22 +255,22 @@ tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipyth
 
 [[package]]
 name = "importlib-metadata"
-version = "7.1.0"
+version = "8.0.0"
 description = "Read metadata from Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "importlib_metadata-7.1.0-py3-none-any.whl", hash = "sha256:30962b96c0c223483ed6cc7280e7f0199feb01a0e40cfae4d4450fc6fab1f570"},
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 ]
 
 [package.dependencies]
 zipp = ">=0.5"
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
 perf = ["ipython"]
-testing = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-perf (>=0.9.2)", "pytest-ruff (>=0.2.1)"]
+test = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-perf (>=0.9.2)", "pytest-ruff (>=0.2.1)"]
 
 [[package]]
 name = "iniconfig"
@@ -285,13 +285,13 @@ files = [
 
 [[package]]
 name = "ipykernel"
-version = "6.29.4"
+version = "6.29.5"
 description = "IPython Kernel for Jupyter"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -372,15 +372,32 @@ docs = ["Jinja2 (==2.11.3)", "MarkupSafe (==1.1.1)", "Pygments (==2.8.1)", "alab
 qa = ["flake8 (==5.0.4)", "mypy (==0.971)", "types-setuptools (==67.2.0.1)"]
 testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
 
+[[package]]
+name = "jinja2"
+version = "3.1.4"
+description = "A very fast and expressive template engine."
+optional = false
+python-versions = ">=3.7"
+files = [
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+    {file = "jinja2-3.1.4.tar.gz", hash = "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369"},
+]
+
+[package.dependencies]
+MarkupSafe = ">=2.0"
+
+[package.extras]
+i18n = ["Babel (>=2.7)"]
+
 [[package]]
 name = "jupyter-client"
-version = "8.6.1"
+version = "8.6.2"
 description = "Jupyter protocol implementation and client libraries"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -393,7 +410,7 @@ traitlets = ">=5.3"
 
 [package.extras]
 docs = ["ipykernel", "myst-parser", "pydata-sphinx-theme", "sphinx (>=4)", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
-test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pytest", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"]
+test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pytest (<8.2.0)", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"]
 
 [[package]]
 name = "jupyter-core"
@@ -430,6 +447,75 @@ files = [
 click = ">=8.1.3,<9.0.0"
 pint = ">=0.21,<0.22"
 
+[[package]]
+name = "markupsafe"
+version = "2.1.5"
+description = "Safely add untrusted strings to HTML/XML markup."
+optional = false
+python-versions = ">=3.7"
+files = [
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 [[package]]
 name = "matplotlib-inline"
 version = "0.1.7"
@@ -502,13 +588,13 @@ files = [
 
 [[package]]
 name = "packaging"
-version = "24.0"
+version = "24.1"
 description = "Core utilities for Python packages"
 optional = false
-python-versions = ">=3.7"
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 [[package]]
@@ -563,13 +649,13 @@ xarray = ["xarray"]
 
 [[package]]
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-version = "4.2.1"
+version = "4.2.2"
 description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`."
 optional = false
 python-versions = ">=3.8"
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@@ -609,13 +695,13 @@ testing = ["pytest", "pytest-benchmark"]
 
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+version = "3.0.47"
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 [package.extras]
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 [package.extras]
@@ -870,36 +957,36 @@ cffi = {version = "*", markers = "implementation_name == \"pypy\""}
 
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+    {file = "scipy-1.13.1-cp312-cp312-win_amd64.whl", hash = "sha256:cdd7dacfb95fea358916410ec61bbc20440f7860333aee6d882bb8046264e949"},
+    {file = "scipy-1.13.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:436bbb42a94a8aeef855d755ce5a465479c721e9d684de76bf61a62e7c2b81d5"},
+    {file = "scipy-1.13.1-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:8335549ebbca860c52bf3d02f80784e91a004b71b059e3eea9678ba994796a24"},
+    {file = "scipy-1.13.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d533654b7d221a6a97304ab63c41c96473ff04459e404b83275b60aa8f4b7004"},
+    {file = "scipy-1.13.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:637e98dcf185ba7f8e663e122ebf908c4702420477ae52a04f9908707456ba4d"},
+    {file = "scipy-1.13.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:a014c2b3697bde71724244f63de2476925596c24285c7a637364761f8710891c"},
+    {file = "scipy-1.13.1-cp39-cp39-win_amd64.whl", hash = "sha256:392e4ec766654852c25ebad4f64e4e584cf19820b980bc04960bca0b0cd6eaa2"},
+    {file = "scipy-1.13.1.tar.gz", hash = "sha256:095a87a0312b08dfd6a6155cbbd310a8c51800fc931b8c0b84003014b874ed3c"},
 ]
 
 [package.dependencies]
@@ -942,13 +1029,13 @@ tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
 
 [[package]]
 name = "tenacity"
-version = "8.3.0"
+version = "8.5.0"
 description = "Retry code until it succeeds"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "tenacity-8.3.0-py3-none-any.whl", hash = "sha256:3649f6443dbc0d9b01b9d8020a9c4ec7a1ff5f6f3c6c8a036ef371f573fe9185"},
-    {file = "tenacity-8.3.0.tar.gz", hash = "sha256:953d4e6ad24357bceffbc9707bc74349aca9d245f68eb65419cf0c249a1949a2"},
+    {file = "tenacity-8.5.0-py3-none-any.whl", hash = "sha256:b594c2a5945830c267ce6b79a166228323ed52718f30302c1359836112346687"},
+    {file = "tenacity-8.5.0.tar.gz", hash = "sha256:8bc6c0c8a09b31e6cad13c47afbed1a567518250a9a171418582ed8d9c20ca78"},
 ]
 
 [package.extras]
@@ -968,22 +1055,22 @@ files = [
 
 [[package]]
 name = "tornado"
-version = "6.4"
+version = "6.4.1"
 description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
 optional = false
-python-versions = ">= 3.8"
+python-versions = ">=3.8"
 files = [
-    {file = "tornado-6.4-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:02ccefc7d8211e5a7f9e8bc3f9e5b0ad6262ba2fbb683a6443ecc804e5224ce0"},
-    {file = "tornado-6.4-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:27787de946a9cffd63ce5814c33f734c627a87072ec7eed71f7fc4417bb16263"},
-    {file = "tornado-6.4-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f7894c581ecdcf91666a0912f18ce5e757213999e183ebfc2c3fdbf4d5bd764e"},
-    {file = "tornado-6.4-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e43bc2e5370a6a8e413e1e1cd0c91bedc5bd62a74a532371042a18ef19e10579"},
-    {file = "tornado-6.4-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f0251554cdd50b4b44362f73ad5ba7126fc5b2c2895cc62b14a1c2d7ea32f212"},
-    {file = "tornado-6.4-cp38-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:fd03192e287fbd0899dd8f81c6fb9cbbc69194d2074b38f384cb6fa72b80e9c2"},
-    {file = "tornado-6.4-cp38-abi3-musllinux_1_1_i686.whl", hash = "sha256:88b84956273fbd73420e6d4b8d5ccbe913c65d31351b4c004ae362eba06e1f78"},
-    {file = "tornado-6.4-cp38-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:71ddfc23a0e03ef2df1c1397d859868d158c8276a0603b96cf86892bff58149f"},
-    {file = "tornado-6.4-cp38-abi3-win32.whl", hash = "sha256:6f8a6c77900f5ae93d8b4ae1196472d0ccc2775cc1dfdc9e7727889145c45052"},
-    {file = "tornado-6.4-cp38-abi3-win_amd64.whl", hash = "sha256:10aeaa8006333433da48dec9fe417877f8bcc21f48dda8d661ae79da357b2a63"},
-    {file = "tornado-6.4.tar.gz", hash = "sha256:72291fa6e6bc84e626589f1c29d90a5a6d593ef5ae68052ee2ef000dfd273dee"},
+    {file = "tornado-6.4.1-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:163b0aafc8e23d8cdc3c9dfb24c5368af84a81e3364745ccb4427669bf84aec8"},
+    {file = "tornado-6.4.1-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:6d5ce3437e18a2b66fbadb183c1d3364fb03f2be71299e7d10dbeeb69f4b2a14"},
+    {file = "tornado-6.4.1-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e2e20b9113cd7293f164dc46fffb13535266e713cdb87bd2d15ddb336e96cfc4"},
+    {file = "tornado-6.4.1-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8ae50a504a740365267b2a8d1a90c9fbc86b780a39170feca9bcc1787ff80842"},
+    {file = "tornado-6.4.1-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:613bf4ddf5c7a95509218b149b555621497a6cc0d46ac341b30bd9ec19eac7f3"},
+    {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:25486eb223babe3eed4b8aecbac33b37e3dd6d776bc730ca14e1bf93888b979f"},
+    {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_i686.whl", hash = "sha256:454db8a7ecfcf2ff6042dde58404164d969b6f5d58b926da15e6b23817950fc4"},
+    {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:a02a08cc7a9314b006f653ce40483b9b3c12cda222d6a46d4ac63bb6c9057698"},
+    {file = "tornado-6.4.1-cp38-abi3-win32.whl", hash = "sha256:d9a566c40b89757c9aa8e6f032bcdb8ca8795d7c1a9762910c722b1635c9de4d"},
+    {file = "tornado-6.4.1-cp38-abi3-win_amd64.whl", hash = "sha256:b24b8982ed444378d7f21d563f4180a2de31ced9d8d84443907a0a64da2072e7"},
+    {file = "tornado-6.4.1.tar.gz", hash = "sha256:92d3ab53183d8c50f8204a51e6f91d18a15d5ef261e84d452800d4ff6fc504e9"},
 ]
 
 [[package]]
@@ -1003,13 +1090,13 @@ test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,
 
 [[package]]
 name = "typing-extensions"
-version = "4.11.0"
+version = "4.12.2"
 description = "Backported and Experimental Type Hints for Python 3.8+"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "typing_extensions-4.11.0-py3-none-any.whl", hash = "sha256:c1f94d72897edaf4ce775bb7558d5b79d8126906a14ea5ed1635921406c0387a"},
-    {file = "typing_extensions-4.11.0.tar.gz", hash = "sha256:83f085bd5ca59c80295fc2a82ab5dac679cbe02b9f33f7d83af68e241bea51b0"},
+    {file = "typing_extensions-4.12.2-py3-none-any.whl", hash = "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d"},
+    {file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
 ]
 
 [[package]]
@@ -1025,20 +1112,20 @@ files = [
 
 [[package]]
 name = "zipp"
-version = "3.18.1"
+version = "3.19.2"
 description = "Backport of pathlib-compatible object wrapper for zip files"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "zipp-3.18.1-py3-none-any.whl", hash = "sha256:206f5a15f2af3dbaee80769fb7dc6f249695e940acca08dfb2a4769fe61e538b"},
-    {file = "zipp-3.18.1.tar.gz", hash = "sha256:2884ed22e7d8961de1c9a05142eb69a247f120291bc0206a00a7642f09b5b715"},
+    {file = "zipp-3.19.2-py3-none-any.whl", hash = "sha256:f091755f667055f2d02b32c53771a7a6c8b47e1fdbc4b72a8b9072b3eef8015c"},
+    {file = "zipp-3.19.2.tar.gz", hash = "sha256:bf1dcf6450f873a13e952a29504887c89e6de7506209e5b1bcc3460135d4de19"},
 ]
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
 
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9"
-content-hash = "8e24d00084a0700fd09f2612096ef0fbef5c863c8ace13e9b41e8fa6af9cd0d6"
+content-hash = "059720d9fcd44072adf2185a2030feed33006e26dedea74351c2e2882df27685"
diff --git a/pyproject.toml b/pyproject.toml
index 920e7e1..d43e881 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -10,11 +10,13 @@ koozie = "^1.2.2"
 PsychroLib = "^2.5.0"
 scipy = "^1.6.3"
 dimes = { git = "https://github.com/bigladder/dimes.git", branch = "main"} # { git = "https://github.com/bigladder/dimes.git", branch = ""} { path = "../dimes/", develop = true }
+numpy = "^1"
 
 [tool.poetry.group.dev.dependencies]
 pytest = "^7.1.3"
 doit = "*"
 tomli = "2.0.1"
+jinja2 = "*"
 
 [tool.poetry.group.extras.dependencies]
 ipykernel = "^6.29.4"
diff --git a/resdx/models/rating_correlations.py b/resdx/models/rating_correlations.py
new file mode 100644
index 0000000..288184b
--- /dev/null
+++ b/resdx/models/rating_correlations.py
@@ -0,0 +1,48 @@
+'''
+This file is generated from a template. To modify, edit the *.py.jinja file.
+'''
+from scipy.interpolate import RegularGridInterpolator
+
+from ..enums import StagingType
+
+
+def cop_47_h1_full(
+    staging_type: StagingType, hspf: float, capacity_maintenance_17: float
+) -> float:
+    if staging_type == StagingType.SINGLE_STAGE:
+        rating_range = [5.0, 6.5, 8.0, 9.5, 11.0]
+        ratio_range = [0.5, 0.54, 0.6200000000000001, 0.7800000000000001, 1.1]
+        input_data = [[2.009891731516297, 2.900448585535248, 4.010093456900876, 5.431988020200642, 7.3195111256671614], [2.000775998527909, 2.8485818540848657, 3.8747600210672744, 5.14222083812663, 6.747399891091504], [1.981863842010724, 2.75526906175661, 3.644057842525539, 4.676132481713103, 5.889180566884448], [1.9554023667471951, 2.624560580784747, 3.3386311532345387, 4.102292714662521, 4.92089711863152], [1.9693303958590127, 2.5755072458673234, 3.1890102522030994, 3.8099730364590108, 4.43853248959917]]
+    elif staging_type == StagingType.TWO_STAGE:
+        rating_range = [5.0, 6.5, 8.0, 9.5, 11.0]
+        ratio_range = [0.5, 0.54, 0.6200000000000001, 0.7800000000000001, 1.1]
+        input_data = [[1.8101801914391407, 2.614381419505263, 3.6139566602663744, 4.894301728231222, 6.593043340163464], [1.7913598796010213, 2.5520880128115797, 3.4709094527846704, 4.605371229376505, 6.041479535921948], [1.766569892370598, 2.455733700059477, 3.247480945864716, 4.166613801000631, 5.246564710654553], [1.7232924438587915, 2.3127754783969836, 2.9416856265089177, 3.6141153256068947, 4.334743691615336], [1.6588882151089572, 2.1693312160911917, 2.6858585160743886, 3.2085795512988318, 3.737606398358994]]
+    elif staging_type == StagingType.VARIABLE_SPEED:
+        # Historic NEEP correlation: heating_cop_47 = 2.837 + 0.066 * hspf2
+        rating_range = [7.0, 9.25, 11.5, 13.75, 16.0]
+        ratio_range = [0.5, 0.54, 0.6200000000000001, 0.7800000000000001, 1.1]
+        input_data = [[2.740066866351769, 4.156022076239291, 6.041842869168669, 8.739888768474037, 12.866672323186215], [2.667812510609135, 3.9451382307326983, 5.574737310534095, 7.719342445603765, 10.667803107740331], [2.535750780817139, 3.6052072307479794, 4.850218534269239, 6.317683766086791, 8.072737844797668], [2.3888256205829537, 3.2196379035518303, 4.084194981286329, 4.984539043255583, 5.922874051307971], [2.206503280082531, 2.9066655845439233, 3.6024341639533906, 4.293820514817972, 4.980836304375722]]
+
+    return RegularGridInterpolator((ratio_range, rating_range), input_data, "linear")(
+        (capacity_maintenance_17, hspf)
+    )
+
+
+def cop_82_b_low(
+    staging_type: StagingType, seer: float, seer_eer_ratio: float
+) -> float:
+    if staging_type == StagingType.SINGLE_STAGE:
+        raise RuntimeError("COP 82 B low is not available for single speed equipment.")
+    elif staging_type == StagingType.TWO_STAGE:
+        rating_range = [6.0, 26.5]
+        ratio_range = [1.2, 2.0]
+        input_data = [[1.8692967646990817, 8.256060710754276], [2.0562340305644637, 9.081700301659712]]
+    elif staging_type == StagingType.VARIABLE_SPEED:
+        # Historic NEEP correlation: EIRr82min = bracket(1.305 - 0.324 * seer2 / eer2, 0.2, 1.0)
+        rating_range = [14.0, 24.5, 35.0]
+        ratio_range = [1.2, 1.6266666666666667, 1.84, 1.9466666666666668, 2.0]
+        input_data = [[4.039748885942864, 7.02150622902228, 9.965018134965845], [5.1912880405225375, 8.771554284371133, 12.138772788050298], [7.232648166115862, 11.778281508307055, 15.84198925923578], [9.372588314901472, 14.940024343784389, 19.56328381350001], [10.830706081861422, 17.124829221643882, 22.209844832722816]]
+
+    return RegularGridInterpolator((ratio_range, rating_range), input_data, "linear")(
+        (seer_eer_ratio, seer)
+    )
\ No newline at end of file
diff --git a/resdx/models/rating_correlations.py.jinja b/resdx/models/rating_correlations.py.jinja
new file mode 100644
index 0000000..3478537
--- /dev/null
+++ b/resdx/models/rating_correlations.py.jinja
@@ -0,0 +1,48 @@
+'''
+This file is generated from a template. To modify, edit the *.py.jinja file.
+'''
+from scipy.interpolate import RegularGridInterpolator
+
+from ..enums import StagingType
+
+
+def cop_47_h1_full(
+    staging_type: StagingType, hspf: float, capacity_maintenance_17: float
+) -> float:
+    if staging_type == StagingType.SINGLE_STAGE:
+        rating_range = {{ heating_1s.rating_range.data_values }}
+        ratio_range = {{ heating_1s.secondary_range.data_values }}
+        input_data = {{ heating_1s.input_data }}
+    elif staging_type == StagingType.TWO_STAGE:
+        rating_range = {{ heating_2s.rating_range.data_values }}
+        ratio_range = {{ heating_2s.secondary_range.data_values }}
+        input_data = {{ heating_2s.input_data }}
+    elif staging_type == StagingType.VARIABLE_SPEED:
+        # Historic NEEP correlation: heating_cop_47 = 2.837 + 0.066 * hspf2
+        rating_range = {{ heating_vs.rating_range.data_values }}
+        ratio_range = {{ heating_vs.secondary_range.data_values }}
+        input_data = {{ heating_vs.input_data }}
+
+    return RegularGridInterpolator((ratio_range, rating_range), input_data, "linear")(
+        (capacity_maintenance_17, hspf)
+    )
+
+
+def cop_82_b_low(
+    staging_type: StagingType, seer: float, seer_eer_ratio: float
+) -> float:
+    if staging_type == StagingType.SINGLE_STAGE:
+        raise RuntimeError("COP 82 B low is not available for single speed equipment.")
+    elif staging_type == StagingType.TWO_STAGE:
+        rating_range = {{ cooling_2s.rating_range.data_values }}
+        ratio_range = {{ cooling_2s.secondary_range.data_values }}
+        input_data = {{ cooling_2s.input_data }}
+    elif staging_type == StagingType.VARIABLE_SPEED:
+        # Historic NEEP correlation: EIRr82min = bracket(1.305 - 0.324 * seer2 / eer2, 0.2, 1.0)
+        rating_range = {{ cooling_vs.rating_range.data_values }}
+        ratio_range = {{ cooling_vs.secondary_range.data_values }}
+        input_data = {{ cooling_vs.input_data }}
+
+    return RegularGridInterpolator((ratio_range, rating_range), input_data, "linear")(
+        (seer_eer_ratio, seer)
+    )
diff --git a/resdx/models/tabular_data.py b/resdx/models/tabular_data.py
index 767a28a..cd867b1 100644
--- a/resdx/models/tabular_data.py
+++ b/resdx/models/tabular_data.py
@@ -7,9 +7,12 @@
 from koozie import fr_u
 
 from ..util import bracket, calc_biquad
+from ..enums import StagingType
 
 from .nrel import NRELDXModel
 
+from .rating_correlations import cop_47_h1_full, cop_82_b_low
+
 
 class TemperatureSpeedPerformanceTable:
     def __init__(
@@ -342,13 +345,14 @@ def make_neep_statistical_model_data(
     P_c.set_by_ratio(Qmax, t_95, Pr95rated)
     P_c.set_by_maintenance(Qmax, t_82, t_95, Pm95max)
     if cooling_cop_82_min is None:
-        EIRr82min = bracket(
-            1.305 - 0.324 * seer2 / eer2, 0.2, 1.0
-        )  # TODO: Replace with new regression
-        cooling_cop_82_min = (Q_c.get(Qmax, t_82) / P_c.get(Qmax, t_82)) / EIRr82min
+        cooling_cop_82_min = cop_82_b_low(
+            StagingType.VARIABLE_SPEED, seer2, seer2 / eer2
+        )
     else:
         EIRr82min = (Q_c.get(Qmax, t_82) / P_c.get(Qmax, t_82)) / cooling_cop_82_min
 
+    EIRr82min = (Q_c.get(Qmax, t_82) / P_c.get(Qmax, t_82)) / cooling_cop_82_min
+
     if cooling_capacity_ratio is not None:
         Qr95min = cooling_capacity_ratio
     else:
@@ -446,7 +450,7 @@ def make_neep_statistical_model_data(
 
     # Net Power
     if heating_cop_47 is None:
-        heating_cop_47 = 2.837 + 0.066 * hspf2
+        heating_cop_47 = cop_47_h1_full(StagingType.VARIABLE_SPEED, hspf2, Qm17rated)
 
     Pr47rated = Qr47rated * EIRr47rated
     Pr47min = Qr47min * EIRr47min
@@ -688,7 +692,7 @@ def make_single_speed_model_data(
 
     # Net Power
     if heating_cop_47 is None:
-        heating_cop_47 = 2.837 + 0.066 * hspf2  # TODO: Replace with inverse correlation
+        heating_cop_47 = cop_47_h1_full(StagingType.SINGLE_STAGE, hspf2, Qm17rated)
 
     Pm17rated = Qm17rated * EIRm17rated
 
@@ -765,7 +769,9 @@ def make_two_speed_model_data(
     Pm95rated = Qm95rated * EIRm95rated
 
     if cooling_cop_82_min is None:
-        cooling_cop_82_min = seer2 / 2.0  # TODO: Replace with regression
+        cooling_cop_82_min = cop_82_b_low(
+            StagingType.VARIABLE_SPEED, seer2, seer2 / eer2
+        )
 
     # 82 / 95 F
     P_c.set(Qrated, t_95, Q_c.get(Qrated, t_95) / fr_u(eer2, "Btu/Wh"))
@@ -826,7 +832,7 @@ def make_two_speed_model_data(
 
     # Net Power
     if heating_cop_47 is None:
-        heating_cop_47 = 2.837 + 0.066 * hspf2  # TODO: Replace with inverse correlation
+        heating_cop_47 = cop_47_h1_full(StagingType.SINGLE_STAGE, hspf2, Qm17rated)
 
     Pm17rated = Qm17rated * EIRm17rated
     PrHmin = QrHmin * EIRrHmin
diff --git a/resdx/util.py b/resdx/util.py
index 39802c1..4c944d4 100644
--- a/resdx/util.py
+++ b/resdx/util.py
@@ -105,3 +105,17 @@ def calculate_r_squared(source_data, regression_data):
     ss_res = np.sum(residuals**2)
     ss_tot = np.sum((source_data_array - np.mean(source_data_array)) ** 2)
     return 1 - ss_res / ss_tot
+
+
+def geometric_space(start: float, end: float, number: int, coefficient: float = 1.0):
+    distance = end - start
+    if coefficient == 1.0:
+        d0 = distance / (number - 1)
+    else:
+        d0 = distance * (coefficient - 1) / (coefficient ** (number - 1) - 1)
+    values = np.zeros(number)
+    values[0] = start
+    for index in range(len(values) - 1):
+        delta = d0 * (coefficient**index)
+        values[index + 1] = values[index] + delta
+    return values