Use SciencePlots

Signed-off-by: Devansh Agarwal <devansh.kv@gmail.com>

bin/your_h5plotter.py

@@ -12,7 +12,7 @@
 from rich.logging import RichHandler
 from rich.progress import Progress
 
-from your.utils.plotter import get_params, plot_h5
+from your.utils.plotter import plot_h5
 
 os.environ["HDF5_USE_FILE_LOCKING"] = "FALSE"
 matplotlib.use("Agg")
@@ -113,10 +113,6 @@ def mapper(save, detrend_ft, publication, mad_filter, out_dir, h5_file):
     else:
         raise ValueError(f"Need either --files or --results_csv argument.")
 
-    params = get_params()
-
-    plt.rcParams.update(params)
-
     with Pool(processes=values.nproc) as p:
         max_ = len(h5_files)
         func = partial(

your/utils/plotter.py

@@ -14,71 +14,6 @@
 from your.utils.math import smad_plotter
 
 
-def figsize(scale, width_by_height_ratio):
-    """
-    Create figure size either a full page or a half page figure
-
-    Args:
-        scale (float): 0.5 for half page figure, 1 for full page
-        width_by_height_ratio (float): ratio of width to height for the figure
-
-    Returns:
-        list: list of width and height
-    """
-    fig_width_pt = (
-        513.17  # 469.755                  # Get this from LaTeX using \the\textwidth
-    )
-    inches_per_pt = 1.0 / 72.27  # Convert pt to inch
-    golden_mean = (np.sqrt(5.0) - 1.0) / 2.0  # Aesthetic ratio (you could change this)
-    fig_width = fig_width_pt * inches_per_pt * scale  # width in inches
-    fig_height = fig_width * golden_mean  # height in inches
-    fig_size = [fig_width, width_by_height_ratio * fig_height]
-    return fig_size
-
-
-def get_params(scale=0.5, width_by_height_ratio=1):
-    """
-    Create a dictionary for pretty plotting
-
-    Args:
-        scale (float): 0.5 for half page figure, 1 for full page
-        width_by_height_ratio (float): ratio of width to height for the figure
-
-    Returns:
-        dict: dictionary of parameters
-    """
-    params = {
-        "backend": "pdf",
-        "axes.labelsize": 10,
-        "lines.markersize": 4,
-        "font.size": 10,
-        "xtick.major.size": 6,
-        "xtick.minor.size": 3,
-        "ytick.major.size": 6,
-        "ytick.minor.size": 3,
-        "xtick.major.width": 0.5,
-        "ytick.major.width": 0.5,
-        "xtick.minor.width": 0.5,
-        "ytick.minor.width": 0.5,
-        "lines.markeredgewidth": 1,
-        "axes.linewidth": 1.2,
-        "legend.fontsize": 7,
-        "xtick.labelsize": 10,
-        "ytick.labelsize": 10,
-        "savefig.dpi": 200,
-        "path.simplify": True,
-        "font.family": "serif",
-        "font.serif": "Times",
-        "text.latex.preamble": [
-            r"\usepackage{amsmath}",
-            r"\usepackage{amsbsy}",
-            r"\DeclareMathAlphabet{\mathcal}{OMS}{cmsy}{m}{n}",
-        ],
-        "figure.figsize": figsize(scale, width_by_height_ratio),
-    }
-    return params
-
-
 def plot_h5(
     h5_file,
     save=True,
@@ -102,7 +37,9 @@ def plot_h5(
         None
 
     """
-    with h5py.File(h5_file, "r") as f:
+    with h5py.File(h5_file, "r") as f, plt.style.context(
+        ["science", "no-latex", "ieee"]
+    ):
         dm_time = np.array(f["data_dm_time"])
         if detrend_ft:
             freq_time = detrend(np.array(f["data_freq_time"])[:, ::-1].T)
@@ -187,11 +124,11 @@ def plot_h5(
                 filename = outdir + os.path.basename(h5_file)[:-3] + ".png"
             else:
                 filename = h5_file[:-3] + ".png"
-            plt.savefig(filename, bbox_inches="tight")
+            plt.savefig(filename, bbox_inches="tight", dpi=300)
         else:
             plt.close()
 
-        return None
+    return None
 
 
 def save_bandpass(
@@ -212,10 +149,6 @@ def save_bandpass(
     freqs = your_object.chan_freqs
     foff = your_object.your_header.foff
 
-    params = get_params()
-
-    plt.rcParams.update(params)
-
     if not outdir:
         outdir = "./"
 
@@ -227,22 +160,23 @@ def save_bandpass(
     else:
         bp_plot = outname
 
-    fig = plt.figure()
-    ax11 = fig.add_subplot(111)
-    if foff < 0:
-        ax11.invert_xaxis()
-
-    ax11.plot(freqs, bandpass, "k-", label="Bandpass")
-    if mask is not None:
-        if mask.sum():
-            logging.info("Flagged %d channels", mask.sum())
-            ax11.plot(freqs[mask], bandpass[mask], "ro", label="Flagged Channels")
-    ax11.set_xlabel("Frequency (MHz)")
-    ax11.set_ylabel("Arb. Units")
-    ax11.legend()
-
-    ax21 = ax11.twiny()
-    ax21.plot(chan_nos, bandpass, alpha=0)
-    ax21.set_xlabel("Channel Numbers")
-
-    return plt.savefig(bp_plot, bbox_inches="tight")
+    with plt.style.context(["science", "no-latex"]):
+        fig = plt.figure()
+        ax11 = fig.add_subplot(111)
+        if foff < 0:
+            ax11.invert_xaxis()
+
+        ax11.plot(freqs, bandpass, "k-", label="Bandpass")
+        if mask is not None:
+            if mask.sum():
+                logging.info("Flagged %d channels", mask.sum())
+                ax11.plot(freqs[mask], bandpass[mask], "r.", label="Flagged Channels")
+        ax11.set_xlabel("Frequency (MHz)")
+        ax11.set_ylabel("Arb. Units")
+        ax11.legend()
+
+        ax21 = ax11.twiny()
+        ax21.plot(chan_nos, bandpass, alpha=0)
+        ax21.set_xlabel("Channel Numbers")
+
+    return plt.savefig(bp_plot, bbox_inches="tight", dpi=300)