diff --git a/.github/workflows/CI.yml b/.github/workflows/CI.yml
index a9f3fa4..bd5d097 100644
--- a/.github/workflows/CI.yml
+++ b/.github/workflows/CI.yml
@@ -8,6 +8,8 @@ on:
     branches: [ master ]
   pull_request:
     branches: [ master ]
+  schedule:
+    - cron: "0 0 * * 1" # every monday at 00:00
 
 jobs:
   build:
@@ -15,8 +17,8 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ['3.8', '3.9', '3.10']
+        os: [ubuntu-latest, macos-latest]
+        python-version: ['3.10', '3.11', '3.12', '3.13']
 
     steps:
     - uses: actions/checkout@v2
@@ -24,11 +26,11 @@ jobs:
       uses: actions/setup-python@v2
       with:
         python-version: ${{ matrix.python-version }}
-    - name: Install dependencies
+    - name: Install
       run: |
         python -m pip install --upgrade pip
         python -m pip install flake8 pytest coverage
-        pip install -r requirements.txt
+        python -m pip install .
     - name: Lint with flake8
       run: |
         # stop the build if there are Python syntax errors or undefined names
diff --git a/.gitignore b/.gitignore
index 48ce8c8..3290b96 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,2 +1,6 @@
 build/
 globalemu.egg-info/
+env*
+__pycache__/
+venv*
+.coverage
diff --git a/MANIFEST.in b/MANIFEST.in
deleted file mode 100644
index f9bd145..0000000
--- a/MANIFEST.in
+++ /dev/null
@@ -1 +0,0 @@
-include requirements.txt
diff --git a/README.rst b/README.rst
index 04d4a2c..cccdad8 100644
--- a/README.rst
+++ b/README.rst
@@ -7,7 +7,7 @@ Introduction
 
 :globalemu: Robust Global 21-cm Signal Emulation
 :Author: Harry Thomas Jones Bevins
-:Version: 1.8.2
+:Version: 1.9.1
 :Homepage: https://github.com/htjb/globalemu
 :Documentation: https://globalemu.readthedocs.io/
 
diff --git a/docs/images/gui.png b/docs/images/gui.png
index 37e499b..e779233 100644
Binary files a/docs/images/gui.png and b/docs/images/gui.png differ
diff --git a/globalemu/eval.py b/globalemu/eval.py
index e9a557e..7b696da 100644
--- a/globalemu/eval.py
+++ b/globalemu/eval.py
@@ -15,6 +15,7 @@
 from tensorflow.keras import backend as K
 import gc
 import pickle
+import warnings
 
 
 class evaluate():
@@ -48,7 +49,7 @@ class evaluate():
                         base_dir + 'model.h5',
                         compile=False)
 
-        logs: **list / default: [0, 1, 2]**
+        logs: **list / default: []**
             | The indices corresponding to the astrophysical
                 parameters that
                 were logged during training. The default assumes
@@ -140,7 +141,14 @@ def __init__(self, **kwargs):
                 self.base_dir + 'model.h5',
                 compile=False)
 
-        self.logs = kwargs.pop('logs', [0, 1, 2])
+        self.logs = kwargs.pop('logs', [])
+        if self.logs == []:
+            warnings.warn("logs has defaulted to [] i.e. " + 
+                          "log no input parameters. Older versions " +
+                          "assumed logs=[0, 1, 2]. If logs is not in " +
+                          "{base_dir}/kwargs.txt and the network " +
+                          "was trained with globalemu < 1.9 there is a " +
+                          "good chance logs should be [0, 1, 2]!")
         if type(self.logs) is not list:
             raise TypeError("'logs' must be a list.")
         self.garbage_collection = kwargs.pop('gc', False)
diff --git a/globalemu/gui.py b/globalemu/gui.py
new file mode 100644
index 0000000..76228da
--- /dev/null
+++ b/globalemu/gui.py
@@ -0,0 +1,104 @@
+import matplotlib.pyplot as plt
+from matplotlib.widgets import Slider, Button
+import numpy as np
+import sys
+import os
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
+from globalemu.eval import evaluate
+
+def main():
+    base_dir = sys.argv[1]
+    if base_dir[-1] != '/':
+        base_dir += '/'
+    
+    config = np.genfromtxt(
+        base_dir + 'gui_configuration.csv',
+        delimiter=',',
+        names=True,
+        dtype='U100,f8,f8,f8,f8,U100,U100',  # Explicitly specify types
+        encoding='utf-8'
+    )
+    
+    logs = config['logs'].tolist()
+    logs = [int(x) for x in logs if x != '--']
+    label_min = config['label_min'][0]
+    label_max = config['label_max'][0]
+    ylabel = config['ylabel'][0]
+    
+    predictor = evaluate(base_dir=base_dir, logs=logs)
+    
+    # Calculate initial values (center of range)
+    center = []
+    for i in range(len(config['names'])):
+        center.append(config['mins'][i] + (config['maxs'][i] - config['mins'][i])/2)
+    center = np.array(center)
+    
+    # Create figure with plot on left, sliders on right
+    n_sliders = len(config['names'])
+    fig = plt.figure(figsize=(14, 8))
+    
+    # Main plot on left side - takes full height
+    ax_plot = plt.subplot2grid((n_sliders, 2), (0, 0), rowspan=n_sliders)
+    
+    # Initial signal
+    def get_params(slider_vals):
+        params = []
+        for i in range(len(slider_vals)):
+            if i in set(logs):
+                params.append(10**slider_vals[i])
+            else:
+                params.append(slider_vals[i])
+        return params
+    
+    signal, z = predictor(get_params(center))
+    line, = ax_plot.plot(z, signal, c='k', lw=2)
+    ax_plot.set_xlabel('z')
+    ax_plot.set_ylabel(ylabel)
+    ax_plot.set_ylim([label_min, label_max])
+    ax_plot.grid(True, alpha=0.3)
+    
+    # Create sliders on right side
+    sliders = []
+    
+    for i in range(n_sliders):
+        # Create axis for this slider on right column
+        ax_slider = plt.subplot2grid((n_sliders, 2), (i, 1))
+        
+        # Create slider
+        slider = Slider(
+            ax_slider,
+            config['names'][i],
+            config['mins'][i],
+            config['maxs'][i],
+            valinit=center[i],
+            valstep=(config['maxs'][i] - config['mins'][i])/100
+        )
+        sliders.append(slider)
+    
+    # Update function
+    def update(val):
+        slider_vals = [s.val for s in sliders]
+        params = get_params(slider_vals)
+        signal, z = predictor(params)
+        line.set_ydata(signal)
+        fig.canvas.draw_idle()
+    
+    # Connect all sliders to update function
+    for slider in sliders:
+        slider.on_changed(update)
+    
+    # Reset button
+    ax_reset = plt.axes([0.8, 0.025, 0.1, 0.04])
+    btn_reset = Button(ax_reset, 'Reset')
+    
+    def reset(event):
+        for i, slider in enumerate(sliders):
+            slider.set_val(center[i])
+    
+    btn_reset.on_clicked(reset)
+    
+    plt.tight_layout()
+    plt.show()
+
+if __name__ == '__main__':
+    main()
\ No newline at end of file
diff --git a/globalemu/gui_config.py b/globalemu/gui_config.py
index 1368242..706f32f 100644
--- a/globalemu/gui_config.py
+++ b/globalemu/gui_config.py
@@ -15,7 +15,6 @@
 """
 
 import numpy as np
-import pandas as pd
 import pickle
 
 
@@ -115,14 +114,33 @@ def __init__(self, base_dir, paramnames, data_dir, **kwargs):
             else:
                 full_logs.append('--')
 
-        df = pd.DataFrame({'names': self.paramnames,
-                           'mins': data_mins,
-                           'maxs': data_maxs,
-                           'label_min':
-                           [test_labels.min()] + ['']*(len(data_maxs)-1),
-                           'label_max':
-                           [test_labels.max()] + ['']*(len(data_maxs)-1),
-                           'logs': full_logs,
-                           'ylabel': self.ylabel})
-
-        df.to_csv(base_dir + 'gui_configuration.csv', index=False)
+        # Create the data arrays
+        n = len(data_maxs)
+        names = np.array(self.paramnames, dtype='U100')  # Unicode strings
+        mins = np.array(data_mins, dtype=float)
+        maxs = np.array(data_maxs, dtype=float)
+
+        # label_min: first value is test_labels.min(), rest are empty strings
+        label_min = np.array([test_labels.min()] + ['']*(n-1), dtype='U100')
+
+        # label_max: first value is test_labels.max(), rest are empty strings
+        label_max = np.array([test_labels.max()] + ['']*(n-1), dtype='U100')
+
+        logs = np.array(full_logs, dtype='U100')
+        ylabel = np.array([self.ylabel]*n, dtype='U100')
+
+        # Stack into 2D array (transpose to get columns)
+        data = np.column_stack([names, mins, maxs, label_min, label_max, logs, ylabel])
+
+        # Write header
+        header = 'names,mins,maxs,label_min,label_max,logs,ylabel'
+
+        # Save to CSV
+        np.savetxt(
+            base_dir + 'gui_configuration.csv',
+            data,
+            delimiter=',',
+            header=header,
+            comments='',  # Prevents '#' being added to header
+            fmt='%s'      # String format for all columns
+        )
diff --git a/globalemu/preprocess.py b/globalemu/preprocess.py
index eb5b046..c6b677c 100644
--- a/globalemu/preprocess.py
+++ b/globalemu/preprocess.py
@@ -13,7 +13,6 @@
 
 import numpy as np
 import os
-import pandas as pd
 import pickle
 from globalemu.cmSim import calc_signal
 from globalemu.resample import sampling
@@ -146,10 +145,12 @@ def __init__(self, num, z, **kwargs):
 
         np.savetxt(self.base_dir + 'z.txt', self.z)
 
-        def load_data(file):
-            return pd.read_csv(
+        def load_data(file: str) -> np.ndarray:
+            """Helper function to load the data from the provided directory."""
+            return np.loadtxt(
                 self.data_location + file,
-                delim_whitespace=True, header=None).values
+                dtype=float
+            )
 
         full_train_data = load_data('train_data.txt')
         full_train_labels = load_data('train_labels.txt')
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..326149b
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,50 @@
+[build-system]
+requires = ["setuptools>=77.0", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "globalemu"
+version = "1.9.1"
+description = "globalemu: Robust and Fast Global 21-cm Signal Emulation."
+readme = "README.rst"
+authors = [
+    {name = "Harry T. J. Bevins", email = "htjb2@cam.ac.uk"}]
+license = {text = "MIT"}
+requires-python = ">=3.10"
+dependencies = [
+    'numpy',
+    'tensorflow',
+    'matplotlib',
+    'Pillow'
+]
+
+classifiers=[
+    'Intended Audience :: Science/Research',
+    'Natural Language :: English',
+    'Programming Language :: Python :: 3.10',
+    'Programming Language :: Python :: 3.11',
+    'Programming Language :: Python :: 3.12',
+    'Programming Language :: Python :: 3.13',
+    'Topic :: Scientific/Engineering',
+    'Topic :: Scientific/Engineering :: Astronomy',
+    'Topic :: Scientific/Engineering :: Physics',
+]
+
+[project.scripts]
+globalemu = "globalemu.gui:main"
+
+
+[project.optional-dependencies]
+dev = [
+    "pytest",
+]
+docs = [
+    "sphinx",
+    "sphinx_rtd_theme",
+    "numpydoc",
+    "packaging"
+]
+
+[tool.setuptools.packages.find]
+where = ["."]
+include = ["globalemu*"]
diff --git a/requirements.txt b/requirements.txt
deleted file mode 100644
index 0ab477e..0000000
--- a/requirements.txt
+++ /dev/null
@@ -1,6 +0,0 @@
-numpy
-tensorflow-macos; sys_platform == 'darwin'
-tensorflow; sys_platform != 'darwin'
-pandas
-matplotlib
-Pillow
diff --git a/scripts/globalemu b/scripts/globalemu
deleted file mode 100644
index fffa3d3..0000000
--- a/scripts/globalemu
+++ /dev/null
@@ -1,152 +0,0 @@
-#!/usr/bin/env python3
-from tkinter import *
-import matplotlib.pyplot as plt
-from matplotlib.mathtext import math_to_image
-from io import BytesIO
-from PIL import ImageTk, Image
-import numpy as np
-import shutil
-import pandas as pd
-import os
-import sys
-import locale
-os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
-from globalemu.eval import evaluate
-
-l = '.'.join(locale.getlocale())
-if l[:2] != 'en':
-    try:
-        locale.setlocale(locale.LC_ALL, 'en_GB.UTF-8')
-    except OSError:
-        print("OSError: system locale is not set to 'en_' and " +
-              "'en_GB.UTF-8' is not available. This will cause " +
-              "issues with tkinter. To install 'en_GB.UTF-8' and run the " +
-              "GUI run 'sudo apt-get install language-pack-en' in " +
-              "the terminal.")
-
-def slider_var(name, lower, upper, position_y,
-             initial, img_x_resize, img_y_resize, tickinterval,
-             resolution=0.1):
-    """Creates the GUI sliders and associated labels"""
-    position_x = 410
-    buffer = BytesIO()
-    math_to_image(name, buffer, dpi=200, format='png')
-    buffer.seek(0)
-
-    img_var = ImageTk.PhotoImage(Image.open(buffer).resize(
-        (img_x_resize, img_y_resize)))
-    entry = Scale(
-                window, from_=lower, to=upper,
-                orient=HORIZONTAL, length=325,
-                resolution=resolution,
-                tickinterval=tickinterval,
-                background='white', command=signal)
-    entry.place(x=position_x, y=position_y)
-    entry.set(initial)
-    return entry, img_var
-
-def signal(_, parameters=None):
-    """Creates the new signals when the user moves the sliders."""
-    if parameters is not None:
-        params = []
-        for i in range(len(center)):
-            if i in set(logs):
-                params.append(10**parameters[i])
-            else:
-                params.append(parameters[i])
-    else:
-        params = []
-        for i in range(len(entries)):
-            if i in set(logs):
-                params.append(10**float(entries[i].get()))
-            else:
-                params.append(float(entries[i].get()))
-    signal, z = predictor(params)
-    plt.figure(figsize=(4, 3))
-    plt.plot(z, signal, c='k')
-    plt.xlabel('z')
-    plt.ylabel(ylabel)
-    plt.ylim([label_min, label_max])
-    plt.tight_layout()
-    plt.savefig('img/img.png', dpi=100)
-    plt.close()
-    if parameters is None:
-        new_img = ImageTk.PhotoImage(Image.open("img/img.png"))
-        panel.configure(image=new_img)
-        panel.image = new_img
-
-
-def reset(parameters=None):
-    """Resets the GUI when the reset button is pressed."""
-    if parameters is not None:
-        signal('', parameters)
-    else:
-        for i in range(len(center)):
-            if i in set(logs):
-                entries[i].set(center[i])
-            else:
-                entries[i].set(center[i])
-        signal('')
-
-base_dir = sys.argv[1]
-
-config = pd.read_csv(base_dir + 'gui_configuration.csv')
-
-logs = config['logs'].tolist()
-logs = [int(x) for x in logs if x != '--']
-label_min = config['label_min'][0]
-label_max = config['label_max'][0]
-ylabel = config['ylabel'][0]
-
-predictor = evaluate(base_dir=base_dir, logs=logs)
-
-window = Tk()
-window.geometry("800x450")
-window.configure(background='white')
-
-window.title('globalemu GUI')
-
-if os.path.exists('img/'):
-    shutil.rmtree('img/')
-os.mkdir('img/')
-
-center = []
-for i in range(len(config['names'])):
-    center.append(config['mins'][i] + (config['maxs'][i] - config['mins'][i])/2)
-center = np.array(center)
-
-reset(parameters=center)
-
-img = ImageTk.PhotoImage(Image.open("img/img.png"))
-panel = Label(window, image=img)
-panel.place(x=10, y=10)
-
-bad_characters = ['$', '\mathrm', '{', '}', '_', '^', '\\']
-common_greek = ['tau', 'alpha', 'nu', 'beta']
-entries, labels = [], []
-for i in range(len(config['names'])):
-    for j in range(len(bad_characters)):
-        if j == 0:
-            reduced_name = config['names'][i].replace(bad_characters[j], '')
-        else:
-            reduced_name = reduced_name.replace(bad_characters[j], '')
-    if reduced_name in set(common_greek):
-        reduced_name = 'o'
-    e, l = slider_var(config['names'][i], config['mins'][i],
-                      config['maxs'][i], 10+60*i,
-                      center[i],
-                      8*len(reduced_name), 15,
-                      (config['maxs'][i] - config['mins'][i])/5,
-                      resolution=(config['maxs'][i] - config['mins'][i])/100)
-    labels.append(l)
-    entries.append(e)
-
-for i in range(len(labels)):
-    Label(window, image=labels[i]).place(x=740, y=10+i*60)
-
-btn = Button(window, text='Reset', command=reset)
-btn.place(x=180, y=360)
-
-window.mainloop()
-
-shutil.rmtree('img/')
diff --git a/setup.py b/setup.py
deleted file mode 100644
index 23e4b04..0000000
--- a/setup.py
+++ /dev/null
@@ -1,46 +0,0 @@
-from setuptools import setup, find_packages
-
-def readme(short=False):
-    with open('README.rst', encoding='utf-8') as f:
-        if short:
-            return f.readlines()[1].strip()
-        else:
-            return f.read()
-
-def get_version_from_readme() -> str:
-    """Get current version of package from README.rst"""
-    readme_text = readme()
-    for line in readme_text.splitlines():
-        if ":Version:" in line:
-            current_version = line.split(":")[-1].strip()
-            return current_version
-    raise ValueError("Could not find version in README.rst")
-
-setup(
-    name='globalemu',
-    version=get_version_from_readme(),
-    description='globalemu: Robust and Fast Global 21-cm Signal Emulation',
-    long_description=readme(),
-    author='Harry T. J. Bevins',
-    author_email='htjb2@cam.ac.uk',
-    url='https://github.com/htjb/globalemu',
-    packages=find_packages(),
-    install_requires=open('requirements.txt').read().splitlines(),
-    license='MIT',
-    scripts=['scripts/globalemu'],
-    extras_require={
-          'docs': ['sphinx', 'sphinx_rtd_theme', 'numpydoc', 'packaging'],
-          },
-    tests_require=['pytest'],
-    classifiers=[
-               'Intended Audience :: Science/Research',
-               'Natural Language :: English',
-               'License :: OSI Approved :: MIT License',
-               'Programming Language :: Python :: 3.6',
-               'Programming Language :: Python :: 3.7',
-               'Programming Language :: Python :: 3.8',
-               'Topic :: Scientific/Engineering',
-               'Topic :: Scientific/Engineering :: Astronomy',
-               'Topic :: Scientific/Engineering :: Physics',
-    ],
-)
diff --git a/tests/test_download.py b/tests/test_download.py
index 440ed82..b76ee22 100644
--- a/tests/test_download.py
+++ b/tests/test_download.py
@@ -2,7 +2,6 @@
 import os
 import pytest
 import requests
-import pandas as pd
 import numpy as np
 
 
@@ -25,12 +24,8 @@ def download_21cmGEM_data():
         with open(data_dir + saves[i], 'wb') as f:
             f.write(requests.get(url).content)
 
-    td = pd.read_csv(
-        data_dir + 'train_data.txt',
-        delim_whitespace=True, header=None).values
-    tl = pd.read_csv(
-        data_dir + 'train_labels.txt',
-        delim_whitespace=True, header=None).values
+    td = np.loadtxt(data_dir + 'train_data.txt', dtype=float) 
+    tl = np.loadtxt(data_dir + 'train_labels.txt', dtype=float)
 
     np.savetxt(data_dir + 'train_data.txt', td[:500, :])
     np.savetxt(data_dir + 'train_labels.txt', tl[:500, :])
diff --git a/tests/test_gui_config.py b/tests/test_gui_config.py
index 0bc1f28..a2cb755 100644
--- a/tests/test_gui_config.py
+++ b/tests/test_gui_config.py
@@ -1,4 +1,4 @@
-import pandas as pd
+import numpy as np
 from globalemu.gui_config import config
 from globalemu.downloads import download
 import shutil
@@ -26,7 +26,14 @@ def test_config():
 
     assert(os.path.exists('xHI_release/gui_configuration.csv') is True)
 
-    res = pd.read_csv('xHI_release/gui_configuration.csv')
+    res = np.genfromtxt(
+            'xHI_release/gui_configuration.csv',
+            delimiter=',',
+            names=True,
+            dtype='U100,f8,f8,f8,f8,U100,U100',  # Explicitly specify types
+            encoding='utf-8'
+        )
+
     logs = res['logs'].tolist()
     logs = [int(x) for x in logs if x != '--']
     assert(logs == [0, 1, 2])
diff --git a/tests/test_network.py b/tests/test_network.py
index 60410b9..f297de0 100644
--- a/tests/test_network.py
+++ b/tests/test_network.py
@@ -14,61 +14,66 @@ def custom_loss(y, y_, x):
 
     z = np.arange(5, 50.1, 0.1)
 
-    process(10, z, data_location='21cmGEM_data/')
+    process(10, z, data_location="21cmGEM_data/")
     nn(batch_size=451, layer_sizes=[8], epochs=10, loss_function=custom_loss)
 
     # results of below will not make sense as it is being run on the
     # global signal data but it will test the code (xHI data not public)
-    process(10, z, data_location='21cmGEM_data/', xHI=True)
+    process(10, z, data_location="21cmGEM_data/", xHI=True)
     nn(batch_size=451, layer_sizes=[8], epochs=5, xHI=True)
 
-    nn(batch_size=451, layer_sizes=[8], epochs=5, output_activation='linear')
+    nn(batch_size=451, layer_sizes=[8], epochs=5, output_activation="linear")
 
     # test early_stop code
     nn(batch_size=451, layer_sizes=[], epochs=20, early_stop=True)
 
+    process(10, z, data_location="21cmGEM_data/", base_dir="base_dir/")
+    nn(
+        batch_size=451,
+        layer_sizes=[],
+        random_seed=10,
+        epochs=30,
+        base_dir="base_dir/",
+        early_stop=True,
+    )
+
+    dir = ["model_dir/", "base_dir/"]
+    for i in range(len(dir)):
+        if os.path.exists(dir[i]):
+            shutil.rmtree(dir[i])
+
+
+def test_process_nn_keyword_errors():
+    z = np.arange(5, 50.1, 0.1)
     with pytest.raises(KeyError):
-        process(10, z, datalocation='21cmGEM_data/')
+        process(10, z, datalocation="21cmGEM_data/")
 
     with pytest.raises(KeyError):
         nn(batch_size=451, layersizes=[8], epochs=10)
 
-    with pytest.raises(TypeError):
-        nn(batch_size='foo')
-    with pytest.raises(TypeError):
-        nn(activation=10)
-    with pytest.raises(TypeError):
-        nn(epochs=False)
-    with pytest.raises(TypeError):
-        nn(lr='bar')
-    with pytest.raises(TypeError):
-        nn(dropout=True)
-    with pytest.raises(TypeError):
-        nn(input_shape='foo')
-    with pytest.raises(TypeError):
-        nn(output_shape='foobar')
-    with pytest.raises(TypeError):
-        nn(layer_sizes=10)
-    with pytest.raises(TypeError):
-        nn(base_dir=50)
-    with pytest.raises(KeyError):
-        nn(base_dir='dir')
-    with pytest.raises(TypeError):
-        nn(early_stop='foo')
-    with pytest.raises(TypeError):
-        nn(xHI='false')
-    with pytest.raises(TypeError):
-        nn(resume=10)
-    with pytest.raises(TypeError):
-        nn(output_activation=2)
-    with pytest.raises(TypeError):
-        nn(loss_function='foobar')
-
-    process(10, z, data_location='21cmGEM_data/', base_dir='base_dir/')
-    nn(batch_size=451, layer_sizes=[], random_seed=10, epochs=30,
-       base_dir='base_dir/', early_stop=True)
-
-    dir = ['model_dir/', 'base_dir/']
-    for i in range(len(dir)):
-        if os.path.exists(dir[i]):
-            shutil.rmtree(dir[i])
+
+@pytest.mark.parametrize(
+    "keyword, value",
+    [
+        ("batch_size", "foo"),
+        ("activation", 10),
+        ("epochs", False),
+        ("lr", "bar"),
+        ("dropout", True),
+        ("input_shape", "foo"),
+        ("output_shape", "foobar"),
+        ("layer_sizes", 10),
+        ("base_dir", 50),
+        ("early_stop", "foo"),
+        ("xHI", "false"),
+        ("resume", 10),
+        ("output_activation", 2),
+        ("loss_function", "foobar"),
+    ],
+)
+def test_process_nn_type_errors(keyword, value):
+    z = np.arange(5, 50.1, 0.1)
+
+    process(10, z, data_location="21cmGEM_data/")
+    with pytest.raises((TypeError, ValueError)):
+        nn(**{keyword: value})
diff --git a/tests/test_preprocess.py b/tests/test_preprocess.py
index 5e63bf6..ed294da 100644
--- a/tests/test_preprocess.py
+++ b/tests/test_preprocess.py
@@ -2,7 +2,6 @@
 from globalemu.preprocess import process
 import os
 import pytest
-import pandas as pd
 import shutil
 
 
@@ -29,8 +28,9 @@ def test_preprocess():
     for i in range(len(files)):
         assert(os.path.exists('model_dir/' + files[i]) is True)
 
-    full_train_data = pd.read_csv(
-        'model_dir/train_dataset.csv', header=None).values
+    full_train_data = np.loadtxt(
+        'model_dir/train_dataset.csv', dtype=float,
+        delimiter=',')
 
     for i in range(full_train_data.shape[1]):
         if i < full_train_data.shape[1] - 1: