Merge branch 'release/0.7.0'

.github/workflows/ci.yml

@@ -12,7 +12,9 @@ jobs:
     strategy:
       matrix:
         python-version:
-          - "3.7"
+          - "3.9"
+          - "3.10"
+          - "3.11"
     steps:
       - uses: actions/checkout@v3
       - name: Set up Python ${{ matrix.python-version }}
@@ -30,5 +32,5 @@ jobs:
       - name: Run tests with tox
         run: tox -e py3
       - name: Upload coverage report
-        if: ${{ matrix.python-version == 3.7 }} # Only upload coverage once
+        if: ${{ matrix.python-version == 3.11 }} # Only upload coverage once
         uses: codecov/codecov-action@v1

README.md

@@ -37,7 +37,7 @@ More details about the installation process can be found at [DeepHyper Installat
 
 [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/deephyper/tutorials/blob/main/tutorials/colab/DeepHyper_101.ipynb)
 
-The black-box function named `run` is defined by taking an input dictionary named `config`` which contains the different variables to optimize. Then the run-function is bound to an `Evaluator` in charge of distributing the computation of multiple evaluations. Finally, a Bayesian search named `CBO` is created and executed to find the values of config which **MAXIMIZE** the return value of `run(config)`.
+The black-box function named `run` is defined by taking an input job named `job` which contains the different variables to optimize `job.parameters`. Then the run-function is bound to an `Evaluator` in charge of distributing the computation of multiple evaluations. Finally, a Bayesian search named `CBO` is created and executed to find the values of config which **MAXIMIZE** the return value of `run(job)`.
 
 ```python
 def run(job):
@@ -129,11 +129,11 @@ If you wish to cite the Software, please use the following:
 
 ```
 @misc{deephyper_software,
-title = {"DeepHyper: A Python Package for Scalable Neural Architecture and Hyperparameter Search"},
-author = {{DeepHyper Development Team}},
-organization = {DeepHyper Team},
-year = 2018,
-url = {https://github.com/deephyper/deephyper}
+    title = {"DeepHyper: A Python Package for Scalable Neural Architecture and Hyperparameter Search"},
+    author = {Balaprakash, Prasanna and Egele, Romain and Salim, Misha and Maulik, Romit and Vishwanath, Venkat and Wild, Stefan and others},
+    organization = {DeepHyper Team},
+    year = 2018,
+    url = {https://github.com/deephyper/deephyper}
 } 
 ```
 

deephyper/__version__.py

@@ -1,4 +1,4 @@
-VERSION = (0, 6, 0)
+VERSION = (0, 7, 0)
 
 __version__ = ".".join(map(str, VERSION))
 

deephyper/analysis/_matplotlib.py

@@ -0,0 +1,55 @@
+import matplotlib as mpl
+
+
+def figure_size(width, fraction=1):
+    """Set figure dimensions to avoid scaling in LaTeX.
+
+    Args:
+        width (float): Document textwidth or columnwidth in pts.
+        fraction (float, optional) Fraction of the width which you wish the figure to occupy.
+
+    Returns:
+        tuple: Dimensions of figure in inches.
+    """
+    # Width of figure (in pts)
+    fig_width_pt = width * fraction
+
+    # Convert from pt to inches
+    inches_per_pt = 1 / 72.27
+
+    # Golden ratio to set aesthetic figure height
+    # https://disq.us/p/2940ij3
+    golden_ratio = (5**0.5 - 1) / 2
+
+    # Figure width in inches
+    fig_width_in = fig_width_pt * inches_per_pt
+    # Figure height in inches
+    fig_height_in = fig_width_in * golden_ratio
+
+    fig_dim = (fig_width_in, fig_height_in)
+
+    return fig_dim
+
+
+def update_matplotlib_rc(width=252 * 1.8, fraction=1.0, fontsize=10):
+    mpl.rcParams.update(
+        {
+            "figure.figsize": figure_size(width=width, fraction=fraction),
+            "figure.facecolor": "white",
+            "figure.edgecolor": "white",
+            "savefig.dpi": 360,
+            "figure.subplot.bottom": 0.5,
+            # Use LaTeX to write all text
+            "text.usetex": True,
+            # "font.family": "serif",
+            # Use 10pt font in plots, to match 10pt font in document
+            "axes.labelsize": fontsize,
+            "font.size": fontsize,
+            # Make the legend/label fonts a little smaller
+            "legend.fontsize": fontsize - 3,
+            "xtick.labelsize": fontsize - 1,
+            "ytick.labelsize": fontsize - 1,
+            # tight layout,
+            "figure.autolayout": True,
+        }
+    )