Fix: epimargin/plots.py:62:0: E0102: function already defined line 14

************* Module epimargin.plots
(function-redefined)
epimargin/plots.py:194:0: E0102: function already defined line 14
(function-redefined)

Fixes: Use `import matplotlib.pyplot as plt` rather than `from matplotlib.pyplot import *`.
Related: COVID-IWG#123

epimargin/plots.py

@@ -11,12 +11,16 @@
 import seaborn as sns
 import tikzplotlib
 from matplotlib.patheffects import Normal, Stroke
-from matplotlib.pyplot import *
+
+# pylint will complain about grid overwriting matplotlib.pyplot.grid
+# from matplotlib.pyplot import *
+
+import matplotlib.pyplot as plt
 
 from .models import SIR
 
 def normalize_dates(dates):
- try: 
+ try:
  return [_.to_pydatetime().date() for _ in dates]
  except AttributeError:
  return dates
@@ -36,7 +40,7 @@ def normalize_dates(dates):
 BLK = "#292f36"
 BLK_CI = "#aeb7c2"
 
-### stoplight 
+### stoplight
 RED = "#D63231"
 YLW = "#FD8B5A"
 GRN = "#38AE66"
@@ -48,16 +52,18 @@ def normalize_dates(dates):
 ANOMALY_RED = "#D63231"
 PRED_PURPLE = "#554B68"
 
-## policy simulations 
+## policy simulations
 SIM_PALETTE = ["#437034", "#7D4343", "#43587D", "#7D4370"]
 
-# typography
-def rebuild_font_cache():
- import matplotlib.font_manager
- matplotlib.font_manager._rebuild()
+# FIXME: Maptlotlib 3>.1.x as rebuild_if_missing set to True.
+# Also this is not used anywhere.
+## typography
+#def rebuild_font_cache():
+# import matplotlib.font_manager
+# matplotlib.font_manager._rebuild()
 
 def despine(**kwargs):
- pass 
+ pass
 
 def grid(flag):
  if flag:
@@ -67,7 +73,7 @@ def grid(flag):
 
 # container class for different theme
 Aesthetics = namedtuple(
- "Aesthetics", 
+ "Aesthetics",
  ["title", "label", "note", "ticks", "style", "palette", "accent", "despine", "framealpha", "handlelength"]
 )
 
@@ -135,7 +141,7 @@ def set_theme(name):
  theme = substack_settings
  elif name == "minimal":
  theme = minimal_settings
- else: # default 
+ else: # default
  theme = default_settings
  sns.set(style = theme.style, palette = theme.palette, font = theme.ticks["family"])
  mpl.rcParams.update({"font.size": 22})
@@ -166,20 +172,20 @@ def rgb_to_dec(value):
 def get_continuous_cmap(hex_list, float_list=None):
  ''' creates and returns a color map that can be used in heat map figures.
  If float_list is not provided, colour map graduates linearly between each color in hex_list.
- If float_list is provided, each color in hex_list is mapped to the respective location in float_list. 
- 
+ If float_list is provided, each color in hex_list is mapped to the respective location in float_list.
+
  Parameters
  ----------
  hex_list: list of hex code strings
  float_list: list of floats between 0 and 1, same length as hex_list. Must start with 0 and end with 1.
- 
+
  Returns
  ----------
  colour map'''
  rgb_list = [rgb_to_dec(hex_to_rgb(i)) for i in hex_list]
  if not float_list:
  float_list = list(np.linspace(0,1,len(rgb_list)))
- 
+
  cdict = dict()
  for num, col in enumerate(['red', 'green', 'blue']):
  col_list = [[float_list[i], rgb_list[i][num], rgb_list[i][num]] for i in range(len(float_list))]
@@ -193,7 +199,7 @@ def get_continuous_cmap(hex_list, float_list=None):
 default_cmap = get_continuous_cmap([GRN, YLW, RED, RED], [0, 0.8, 0.9, 1])
 def get_cmap(vmin = 0, vmax = 3, cmap = default_cmap):
  return mpl.cm.ScalarMappable(
- norm = mpl.colors.Normalize(vmin, vmax), 
+ norm = mpl.colors.Normalize(vmin, vmax),
  cmap = cmap
  )
 
@@ -213,7 +219,7 @@ def __init__(self, fig: Optional[mpl.figure.Figure] = None):
  def axis_labels(self, x, y, enforce_spacing = True, **kwargs):
  kwargs["fontdict"] = kwargs.get("fontdict", theme.label)
  if enforce_spacing and not x.startswith("\n"):
- x = "\n" + x 
+ x = "\n" + x
  if enforce_spacing and not y.endswith("\n"):
  y = y + "\n"
  return self.xlabel(x, **kwargs).ylabel(y, **kwargs)
@@ -222,13 +228,13 @@ def xlabel(self, xl: str, **kwargs):
  kwargs["fontdict"] = kwargs.get("fontdict", theme.label)
  plt.xlabel(xl, **kwargs)
  plt.gca().xaxis.label.set_color("dimgray")
- return self 
+ return self
 
  def ylabel(self, yl: str, **kwargs):
  kwargs["fontdict"] = kwargs.get("fontdict", theme.label)
  plt.ylabel(yl, **kwargs)
  plt.gca().yaxis.label.set_color("dimgray")
- return self 
+ return self
 
  # stack title/subtitle vertically
  def title(self, text: str, **kwargs):
@@ -242,15 +248,15 @@ def title(self, text: str, **kwargs):
  kwargs["fontdict"] = kwargs.get("fontdict", theme.title)
  kwargs["fontweight"] = kwargs.get("fontweight", theme.title["weight"])
  plt.suptitle(text, **kwargs)
- return self 
- 
+ return self
+
  def annotate(self, text: str, **kwargs):
  kwargs["fontdict"] = kwargs.get("fontdict", theme.note)
  kwargs["loc"] = kwargs.get("loc", "left")
  plt.title(text, **kwargs)
  return self
 
- # stack title/subtitle horizontally 
+ # stack title/subtitle horizontally
  def l_title(self, text: str, **kwargs):
  kwargs["loc"] = "left"
  kwargs["ha"] = kwargs.get("ha", "left")
@@ -259,47 +265,47 @@ def l_title(self, text: str, **kwargs):
  kwargs["fontdict"] = kwargs.get("fontdict", theme.title)
  kwargs["fontweight"] = kwargs.get("fontweight", theme.title["weight"])
  plt.title(text, **kwargs)
- return self 
- 
+ return self
+
  def r_title(self, text: str, **kwargs):
  kwargs["loc"] = "right"
  kwargs["ha"] = kwargs.get("ha", "right")
  kwargs["va"] = kwargs.get("va", "bottom")
  kwargs["fontdict"] = kwargs.get("fontdict", theme.note)
  kwargs["color"] = theme.accent
  plt.title(text, **kwargs)
- return self 
- 
+ return self
+
  def size(self, w, h):
  self.figure.set_size_inches(w, h)
  return self
- 
+
  def legend(self, *args, **kwargs):
  kwargs["framealpha"] = kwargs.get("framealpha", theme.framealpha)
  kwargs["handlelength"] = kwargs.get("handlelength", theme.handlelength)
  plt.legend(*args, **kwargs)
  return self
- 
+
  def format_xaxis(self, fmt = DATE_FMT):
  plt.gca().xaxis.set_major_formatter(DATE_FMT)
  plt.gca().xaxis.set_minor_formatter(DATE_FMT)
- return self 
+ return self
 
  def save(self, filename: Path, **kwargs):
  if str(filename).endswith("tex"):
  tikzplotlib.save(filename, **kwargs)
- return self 
+ return self
  kwargs["transparent"] = kwargs.get("transparent", str(filename).endswith("svg"))
  plt.savefig(filename, **kwargs)
- return self 
+ return self
 
  def adjust(self, **kwargs):
  plt.subplots_adjust(**kwargs)
- return self 
+ return self
 
  def show(self, **kwargs):
  plt.show(**kwargs)
- return self 
+ return self
 
 def plot_SIRD(model: SIR, layout = (1, 4)) -> PlotDevice:
  """ plot all 4 available curves (S, I, R, D) for a given SIR model """
@@ -311,7 +317,7 @@ def plot_SIRD(model: SIR, layout = (1, 4)) -> PlotDevice:
  d = ax.semilogy(t, model.D, alpha=0.75, label="Deaths", )
  r = ax.semilogy(t, model.R, alpha=0.75, label="Recovered", )
  ax.label_outer()
- 
+
  fig.legend([s, i, r, d], labels = ["S", "I", "R", "D"], loc = "center right", borderaxespad = 0.1)
  return PlotDevice(fig)
 
@@ -320,7 +326,7 @@ def plot_curve(models: Sequence[SIR], labels: Sequence[str], curve: str = "I"):
  fig = plt.figure()
  for (model, label) in zip(models, labels):
  plt.semilogy(model.aggregate(curve), label = label, figure = fig)
- plt.legend() 
+ plt.legend()
  plt.tight_layout()
  return PlotDevice(fig)
 
@@ -336,21 +342,21 @@ def gantt_chart(gantt_data, start_date: Optional[str] = None, show_cbar = True):
  else:
  xticklabels = sorted(gantt_df.day.unique())
  xlabel = "Days Since Beginning of Adaptive Control"
- ax = sns.heatmap(gantt_pv["beta"], linewidths = 2, alpha = 0.8, 
+ ax = sns.heatmap(gantt_pv["beta"], linewidths = 2, alpha = 0.8,
  annot = gantt_pv["R"], annot_kws={"size": 8},
  cmap = ["#38AE66", "#FFF3B4", "#FD8B5A", "#D63231"],
  cbar = show_cbar,
  yticklabels = gantt_df["district"].unique(),
  xticklabels = xticklabels,
  cbar_kws = {
- "ticks":[0.5, 1, 2, 2.5], 
- "label": "Mobility", 
- "format": mpl.ticker.FuncFormatter(lambda x, pos: {0.5:"voluntary", 1:"cautionary", 2:"partial", 2.5:"restricted"}[x]), 
- "orientation": "horizontal", 
- "aspect": 50, 
+ "ticks":[0.5, 1, 2, 2.5],
+ "label": "Mobility",
+ "format": mpl.ticker.FuncFormatter(lambda x, pos: {0.5:"voluntary", 1:"cautionary", 2:"partial", 2.5:"restricted"}[x]),
+ "orientation": "horizontal",
+ "aspect": 50,
  "drawedges": True,
  "fraction": 0.05,
- "pad": 0.10, 
+ "pad": 0.10,
  "shrink": 0.5
  }
  )
@@ -368,12 +374,12 @@ def predictions(date_range, model, color, bounds = [2.5, 97.5], curve = "dT"):
  return [(range_marker, median_marker), model.name]
 
 def simulations(
- simulation_results: Sequence[Tuple[SIR]], 
- labels: Sequence[str], 
- historical: Optional[pd.Series] = None, 
- historical_label: str = "Empirical Case Data", 
- curve: str = "dT", 
- smoothing: Optional[np.ndarray] = None, 
+ simulation_results: Sequence[Tuple[SIR]],
+ labels: Sequence[str],
+ historical: Optional[pd.Series] = None,
+ historical_label: str = "Empirical Case Data",
+ curve: str = "dT",
+ smoothing: Optional[np.ndarray] = None,
  semilog: bool = True) -> PlotDevice:
  """ plot simulation results for new daily cases and optionally show historical trends """
 
@@ -408,13 +414,13 @@ def simulations(
  p = plt.plot([pd.Timestamp(t) for t in smoothing[:, 0]], smoothing[:, 1], 'k-', linewidth = 1)
  legends.append(p)
  legend_labels.append("smoothed_data")
- 
+
  for (rng, label, color) in zip(ranges, labels, SIM_PALETTE):
  p, = plt.plot(t, rng["avg"], color = color, linewidth = 2)
  f = plt.fill_between(t, rng["min"], rng["max"], color = color, alpha = 0.2)
  legends.append((p, f))
  legend_labels.append(label)
- 
+
  plt.gca().xaxis.set_major_formatter(DATE_FMT)
  plt.gca().xaxis.set_minor_formatter(DATE_FMT)
  plt.legend(legends, legend_labels, prop = dict(size = 20), handlelength = theme.handlelength, framealpha = theme.framealpha, loc = "best")
@@ -429,7 +435,7 @@ def Rt(dates, Rt_pred, Rt_CI_upper, Rt_CI_lower, CI, ymin = 0.5, ymax = 3, yaxis
  """ plot Rt and associated confidence intervals over time """
  CI_marker = plt.fill_between(dates, Rt_CI_lower, Rt_CI_upper, color = BLK, alpha = 0.3)
  Rt_marker, = plt.plot(dates, Rt_pred, color = BLK, linewidth = 2, zorder = 5, solid_capstyle = "butt")
- if yaxis_colors: 
+ if yaxis_colors:
  plt.plot([dates[0], dates[0]], [2.5, ymax], color = RED, linewidth = 6, alpha = 0.9, solid_capstyle="butt", zorder = 10)
  plt.plot([dates[0], dates[0]], [1, 2.5], color = YLW, linewidth = 6, alpha = 0.9, solid_capstyle="butt", zorder = 10)
  plt.plot([dates[0], dates[0]], [ymin, 1], color = GRN, linewidth = 6, alpha = 0.9, solid_capstyle="butt", zorder = 10)
@@ -447,13 +453,13 @@ def Rt(dates, Rt_pred, Rt_CI_upper, Rt_CI_lower, CI, ymin = 0.5, ymax = 3, yaxis
  plt.gca().xaxis.set_minor_formatter(DATE_FMT)
  set_tick_size(theme.ticks["size"])
  pd.markers = {"Rt" : (CI_marker, Rt_marker)}
- return pd 
+ return pd
 
-def daily_cases(dates, T_pred, T_CI_upper, T_CI_lower, new_cases_ts, anomaly_dates, anomalies, CI, prediction_ts = None): 
+def daily_cases(dates, T_pred, T_CI_upper, T_CI_lower, new_cases_ts, anomaly_dates, anomalies, CI, prediction_ts = None):
  """ plots expected, smoothed cases from simulated annealing training """
  new_cases_dates = dates[-len(new_cases_ts):]
  exp_cases_dates = dates[-len(T_pred):]
- valid_idx = [i for i in range(len(dates)) if dates[i] not in anomaly_dates] 
+ valid_idx = [i for i in range(len(dates)) if dates[i] not in anomaly_dates]
  T_CI_lower_rect = [min(l, u) for (l, u) in zip(T_CI_lower, T_CI_upper)]
  T_CI_upper_rect = [max(l, u) for (l, u) in zip(T_CI_lower, T_CI_upper)]
  observed_marker, = plt.plot([d for d in new_cases_dates if d not in anomaly_dates], [new_cases_ts[i] for i in range(len(new_cases_ts)) if new_cases_dates[i] not in anomaly_dates], color = OBS_BLK, linewidth = 2, zorder = 8)
@@ -473,12 +479,12 @@ def daily_cases(dates, T_pred, T_CI_upper, T_CI_lower, new_cases_ts, anomaly_dat
  plt.vlines(dates[-1], ymin = 0, ymax = top, color = "black", linestyles = "dotted")
  legends += [(predicted_CI_marker, predicted_marker)]
  labels += [label]
- else: 
+ else:
  end = dates[-1]
  plt.ylim(bottom = 0, top = top)
  legends += [anomalies_marker]
  labels += ["anomalies"]
- xlim(left = dates[0], right = end)
+ plt.xlim(left = dates[0], right = end)
  plt.legend(legends, labels, prop = {'size': 14}, framealpha = theme.framealpha, handlelength = theme.handlelength, loc = "best")
  plt.gca().xaxis.set_major_formatter(DATE_FMT)
  plt.gca().xaxis.set_minor_formatter(DATE_FMT)
@@ -494,25 +500,25 @@ def choropleth(gdf, label_fn = lambda _: "", col = "Rt", title = "$R_t$", label_
  ax.set_xticks([])
  ax.set_yticks([])
  if title:
- ax.set_title(title, loc="left", fontdict = theme.label) 
+ ax.set_title(title, loc="left", fontdict = theme.label)
  gdf.plot(color=[mappable.to_rgba(_) for _ in gdf[col]], ax = ax, edgecolors="black", linewidth=0.5, missing_kwds = {"color": theme.accent, "edgecolor": "white"})
  if label_fn is not None:
  for (_, row) in gdf.iterrows():
  label = label_fn(row)
  value = round(row[col], 2)
  ax.annotate(
- s = f"{label}{value}", 
- xy = list(row["pt"].coords)[0], 
- ha = "center", 
- fontfamily = theme.note["family"], 
- color = "black", **label_kwargs, 
+ s = f"{label}{value}",
+ xy = list(row["pt"].coords)[0],
+ ha = "center",
+ fontfamily = theme.note["family"],
+ color = "black", **label_kwargs,
  fontweight = "semibold",
  size = 12)\
  .set_path_effects([Stroke(linewidth = 2, foreground = "white"), Normal()])
  cbar_ax = fig.add_axes([0.90, 0.25, 0.01, 0.5])
  cb = fig.colorbar(mappable = mappable, orientation = "vertical", cax = cbar_ax)
  cbar_ax.set_title("$R_t$", fontdict = theme.note)
- 
+
  return PlotDevice(fig)
 
 def double_choropleth(gdf, label_fn = lambda _: "", Rt_col = "Rt", Rt_proj_col = "Rt_proj", titles = ["Current $R_t$", "Projected $R_t$ (1 Week)"], arrangement = (1, 2), label_kwargs = {}, mappable = sm):
@@ -523,7 +529,7 @@ def double_choropleth(gdf, label_fn = lambda _: "", Rt_col = "Rt", Rt_proj_col =
  ax.grid(False)
  ax.set_xticks([])
  ax.set_yticks([])
- ax.set_title(title, loc="left", fontdict = theme.label) 
+ ax.set_title(title, loc="left", fontdict = theme.label)
  gdf.plot(color=[mappable.to_rgba(_) for _ in gdf[col]], ax = ax, edgecolors="black", linewidth=0.5, missing_kwds = {"color": theme.accent, "edgecolor": "white"})
  if label_fn is not None:
  for (_, row) in gdf.iterrows():
@@ -536,7 +542,7 @@ def double_choropleth(gdf, label_fn = lambda _: "", Rt_col = "Rt", Rt_proj_col =
  cbar_ax = fig.add_axes([0.95, 0.25, 0.01, 0.5])
  cb = fig.colorbar(mappable = mappable, orientation = "vertical", cax = cbar_ax)
  cbar_ax.set_title("$R_t$", fontdict = theme.note)
- 
+
  return PlotDevice(fig)
 
 def double_choropleth_v(*args, **kwargs):