Tests

.github/workflows/CI.yml

@@ -8,27 +8,29 @@ on:
     branches: [ master ]
   pull_request:
     branches: [ master ]
+  schedule:
+    - cron: "0 0 * * 1" # every monday at 00:00
 
 jobs:
   build:
 
     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
     - name: Set up Python ${{ matrix.python-version }}
       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

.gitignore

@@ -1,2 +1,6 @@
 build/
 globalemu.egg-info/
+env*
+__pycache__/
+venv*
+.coverage

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/
 

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)

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()

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
+        )

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')

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*"]