matplotlibify

environment.yml

@@ -20,6 +20,8 @@ dependencies:
   - matplotlib
   - ipympl  # interactive matplotlib plots
   - seaborn
+  - plotly
+  - kaleido
   # - altair
   # - yellowbrick
   # ML, STATS & DEEP LEARNING

requirements.txt

@@ -1,4 +1,6 @@
 importlib_metadata==4.11.4
+kaleido
 numpy==1.22.4
 pillow==9.1.1
+plotly
 pymatgen==2022.5.19

setup.cfg

@@ -52,6 +52,8 @@ install_requires =
     numpy
     pillow
     pymatgen
+    plotly
+    kaleido
 
 
 [options.packages.find]

src/xtal2png/utils/plotting.py

@@ -0,0 +1,128 @@
+from typing import Union
+
+import plotly.graph_objs as go
+from plotly import offline
+
+
+def matplotlibify(
+    fig: go.Figure,
+    size: int = 24,
+    width_inches: Union[float, int] = 3.5,
+    height_inches: Union[float, int] = 3.5,
+    dpi: int = 142,
+    return_scale: bool = False,
+) -> go.Figure:
+    """Make plotly figures look more like matplotlib for academic publishing.
+
+    modified from: https://medium.com/swlh/fa56ddd97539
+
+    Parameters
+    ----------
+    fig : go.Figure
+        Plotly figure to be matplotlibified
+    size : int, optional
+        Font size for layout and axes, by default 24
+    width_inches : Union[float, int], optional
+        Width of matplotlib figure in inches, by default 3.5
+    height_inches : Union[float, int], optional
+        Height of matplotlib figure in Inches, by default 3.5
+    dpi : int, optional
+        Dots per inch (resolution) of matplotlib figure, by default 142. Leave as
+        default unless you're willing to verify nothing strange happens with the output.
+    return_scale : bool, optional
+        If true, then return `scale` which is a quantity that helps with creating a
+        high-resolution image at the specified absolute width and height in inches.
+        More specifically:
+        >>> width_default_px = fig.layout.width
+        >>> targ_dpi = 300
+        >>> scale = width_inches / (width_default_px / dpi) * (targ_dpi / dpi)
+        Feel free to ignore this parameter.
+
+    Returns
+    -------
+    fig : go.Figure
+        The matplotlibified plotly figure.
+
+    Examples
+    --------
+    >>> import plotly.express as px
+    >>> df = px.data.tips()
+    >>> fig = px.histogram(df, x="day")
+    >>> fig.show()
+    >>> fig = matplotlibify(fig, size=24, width_inches=3.5, height_inches=3.5, dpi=142)
+    >>> fig.show()
+
+    Note the difference between
+    https://user-images.githubusercontent.com/45469701/171044741-35591a2c-dede-4df1-ae47-597bbfdb89cf.png # noqa: E501
+    and
+    https://user-images.githubusercontent.com/45469701/171044746-84a0deb0-1e15-40bf-a459-a5a7d3425b20.png, # noqa: E501
+    which are both static exports of interactive plotly figures.
+    """
+    font_dict = dict(family="Arial", size=size, color="black")
+
+    # app = QApplication(sys.argv)
+    # screen = app.screens()[0]
+    # dpi = screen.physicalDotsPerInch()
+    # app.quit()
+
+    fig.update_layout(
+        font=font_dict,
+        plot_bgcolor="white",
+        width=width_inches * dpi,
+        height=height_inches * dpi,
+        margin=dict(r=40, t=20, b=10),
+    )
+
+    fig.update_yaxes(
+        showline=True,  # add line at x=0
+        linecolor="black",  # line color
+        linewidth=2.4,  # line size
+        ticks="inside",  # ticks outside axis
+        tickfont=font_dict,  # tick label font
+        mirror="allticks",  # add ticks to top/right axes
+        tickwidth=2.4,  # tick width
+        tickcolor="black",  # tick color
+    )
+
+    fig.update_xaxes(
+        showline=True,
+        showticklabels=True,
+        linecolor="black",
+        linewidth=2.4,
+        ticks="inside",
+        tickfont=font_dict,
+        mirror="allticks",
+        tickwidth=2.4,
+        tickcolor="black",
+    )
+    fig.update(layout_coloraxis_showscale=False)
+
+    width_default_px = fig.layout.width
+    targ_dpi = 300
+    scale = width_inches / (width_default_px / dpi) * (targ_dpi / dpi)
+
+    if return_scale:
+        return fig, scale
+    else:
+        return fig
+
+
+def plot_and_save(fig_path, fig, mpl_kwargs={}, show=False, update_legend=False):
+    if show:
+        offline.plot(fig)
+    fig.write_html(fig_path + ".html")
+    fig.to_json(fig_path + ".json")
+    if update_legend:
+        fig.update_layout(
+            legend=dict(
+                font=dict(size=16),
+                yanchor="bottom",
+                y=0.99,
+                xanchor="right",
+                x=0.99,
+                bgcolor="rgba(0,0,0,0)",
+                # orientation="h",
+            )
+        )
+    fig = matplotlibify(fig, **mpl_kwargs)
+    fig.write_image(fig_path + ".png")

tests/xtal2png_test.py

@@ -2,6 +2,7 @@
 # (test), and back to crystal Structure (test)
 
 
+import plotly.express as px
 from numpy.testing import assert_allclose
 
 from xtal2png.core import XtalConverter
@@ -12,6 +13,7 @@
     rgb_scaler,
     rgb_unscaler,
 )
+from xtal2png.utils.plotting import plot_and_save
 
 rgb_tol = 1 / 255  # should this be 256?
 rgb_loose_tol = 1.5 / 255
@@ -138,6 +140,15 @@ def test_rgb_scaler_unscaler():
     assert_allclose(check_output, scaled)
 
 
+def test_plot_and_save():
+    df = px.data.tips()
+    fig = px.histogram(df, x="day")
+    plot_and_save("reports/figures/tmp", fig, mpl_kwargs={})
+
+
+# TODO: test_matplotlibify with assertion
+
+
 if __name__ == "__main__":
     test_element_wise_scaler_unscaler()
     test_rgb_scaler_unscaler()