black without mortimer
This commit is contained in:
Noe Brucy
+61
-51
@@ -104,16 +104,15 @@ def quiver(ax, map_h, map_v, extent, key_v=None, lognorm=False, label="", **kwar
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min_v = np.min(norm_v)
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if key_v is None:
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key_v = (max_v + min_v) / 2.0
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key_v = (max_v + min_v) / 2.0
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key = f"${key_v:g}$ {label}"
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if lognorm:
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lognorm_v = np.log10(norm_v)
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map_h *= lognorm_v/norm_v
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map_v *= lognorm_v/norm_v
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key_v = np.log10(key_v)
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lognorm_v = np.log10(norm_v)
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map_h *= lognorm_v / norm_v
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map_v *= lognorm_v / norm_v
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key_v = np.log10(key_v)
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# plot vector field
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vec_field = ax.quiver(hh, vv, map_h, map_v, units="width", **kwargs)
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@@ -203,7 +202,7 @@ class Plotter(Aggregator, BaseProcessor):
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# Conversion table from namelist values (from ramses config file) into suitanle units
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value_convert = {
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"sfr_avg_window": lambda x: 80 * x, # Myr
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"sfr_avg_window": lambda x: 80 * x, # Myr
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"Bx": lambda x: x * 7.6189439,
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}
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@@ -241,7 +240,6 @@ class Plotter(Aggregator, BaseProcessor):
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# log info
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self.log_id = "plotter({})".format(tag)
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super(Plotter, self).__init__(path, path_out, params, tag)
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# Select runs
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@@ -421,7 +419,7 @@ class Plotter(Aggregator, BaseProcessor):
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if ax is not None:
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onefigure = True
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if not movie:
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plot_filename = self._find_filename(name_full)
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plot_filename = self._find_filename(name_full)
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for i, (run, num) in enumerate(run_num):
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@@ -465,7 +463,7 @@ class Plotter(Aggregator, BaseProcessor):
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if self.params.astrophysix.generate:
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df = rule.datafile(name, arg)
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df[filetype] = plot_filename
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if plot_info is not None:
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df.plot_info = plot_info
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if num is not None:
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@@ -499,7 +497,7 @@ class Plotter(Aggregator, BaseProcessor):
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if self.params.plot.tight_layout and close:
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plt.tight_layout(pad=1)
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if self.params.out.save:
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if self.params.out.save:
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os.makedirs(os.path.dirname(plot_filename), exist_ok=True)
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plt.savefig(plot_filename)
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self.logger.info(f"{plot_filename} plotted")
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@@ -565,10 +563,10 @@ class Plotter(Aggregator, BaseProcessor):
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prop_label = self.label_convert[prop_name]
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else:
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prop_label = prop_name
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try:
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prop_value = self.study.get_nml(nml_key, run)
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try:
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prop_value = self.study.get_nml(nml_key, run)
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except KeyError:
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return ""
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return ""
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if prop_name in self.value_str:
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prop_value_str = self.value_str[prop_name](prop_value)
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elif prop_name in self.value_convert:
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@@ -594,8 +592,8 @@ class Plotter(Aggregator, BaseProcessor):
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elif nml_key is not None:
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if not type(nml_key) == list:
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nml_key = [nml_key]
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lbl_list = map(get_label_nml, nml_key) # get namelist value
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lbl_list = filter(lambda x: len(x) > 0, lbl_list) # Remove void labels
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lbl_list = map(get_label_nml, nml_key) # get namelist value
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lbl_list = filter(lambda x: len(x) > 0, lbl_list) # Remove void labels
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label_run = ", ".join(lbl_list)
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if label is not None and len(label) > 0:
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@@ -831,7 +829,7 @@ class Plotter(Aggregator, BaseProcessor):
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s=title,
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color=overtext_color,
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transform=ax.transAxes,
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**text_kwargs
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**text_kwargs,
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)
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else:
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plt.title(title)
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@@ -971,9 +969,7 @@ class Plotter(Aggregator, BaseProcessor):
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if sinks:
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try:
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self.current_processor.sinks()
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data = pd.DataFrame(
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self.current_processor.get_value("/datasets/sinks")
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)
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data = pd.DataFrame(self.current_processor.get_value("/datasets/sinks"))
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part_pos = data[["x", "y", "z"]].values
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unit_length /= self.current_processor.lbox
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except KeyError:
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@@ -1038,6 +1034,8 @@ class Plotter(Aggregator, BaseProcessor):
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# Scatter plot
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scatter = plt.scatter(part_h, part_v, s=s, c=c, **kwargs)
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return scatter
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def _overlay_vector(
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self,
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name,
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@@ -1160,7 +1158,9 @@ class Plotter(Aggregator, BaseProcessor):
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else:
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nml_value = self.study.get_nml(nml_color, run)
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if os.path.basename(nml_color) in self.value_convert:
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nml_value = self.value_convert[ os.path.basename(nml_color)](nml_value)
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nml_value = self.value_convert[os.path.basename(nml_color)](
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nml_value
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)
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try:
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color = colors[nml_value]
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except TypeError:
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@@ -1219,32 +1219,31 @@ class Plotter(Aggregator, BaseProcessor):
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def plot(
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self,
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x:np.array,
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y:np.array,
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xlabel:str="",
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ylabel:str="",
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label:str="",
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xscale:str="linear",
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yscale:str="linear",
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fit:str=None,
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fitlabel:str=None,
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smooth:float=0,
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x: np.array,
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y: np.array,
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xlabel: str = "",
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ylabel: str = "",
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label: str = "",
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xscale: str = "linear",
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yscale: str = "linear",
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fit: str = None,
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fitlabel: str = None,
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smooth: float = 0,
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nml_key=None,
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run:str=None,
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yerr:np.array=None,
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grid:bool=False,
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put_time:bool=False,
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run: str = None,
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yerr: np.array = None,
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grid: bool = False,
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put_time: bool = False,
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unit_time=U.Myr,
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colors=None,
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nml_color=None,
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legend:bool=False,
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legend: bool = False,
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**kwargs,
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):
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"""
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Generic plot routine, with x, y two numpy arrauys
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"""
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# Option to smooth data for readability (beware)
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if smooth > 0:
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y = gaussian_filter1d(y, sigma=smooth)
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@@ -1283,7 +1282,9 @@ class Plotter(Aggregator, BaseProcessor):
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else:
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nml_value = self.study.get_nml(nml_color, run)
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if os.path.basename(nml_color) in self.value_convert:
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nml_value = self.value_convert[os.path.basename(nml_color)](nml_value)
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nml_value = self.value_convert[os.path.basename(nml_color)](
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nml_value
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)
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try:
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color = colors[nml_value]
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except TypeError:
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@@ -1321,8 +1322,8 @@ class Plotter(Aggregator, BaseProcessor):
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def _plot(
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self,
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name_x:str,
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name_y:str,
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name_x: str,
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name_y: str,
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node_arg=None,
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xlabel=None,
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ylabel=None,
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@@ -1363,10 +1364,18 @@ class Plotter(Aggregator, BaseProcessor):
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# Find proper labels
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xlabel, xunit_old, xunit = self._ax_label_unit(
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name_x, xlabel, xunit, xunit_coeff, put_units=put_units,
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name_x,
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xlabel,
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xunit,
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xunit_coeff,
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put_units=put_units,
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)
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ylabel, yunit_old, yunit = self._ax_label_unit(
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name_y, ylabel, yunit, yunit_coeff, put_units=put_units,
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name_y,
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ylabel,
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yunit,
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yunit_coeff,
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put_units=put_units,
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)
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# Manage the different forms in which the data may be stored :
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@@ -1426,8 +1435,7 @@ class Plotter(Aggregator, BaseProcessor):
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"Errorbar may be meaningless when ytransform is used"
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)
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self.plot(x, y, yerr=yerr, xlabel=xlabel,
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ylabel=ylabel, run=run, **kwargs)
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self.plot(x, y, yerr=yerr, xlabel=xlabel, ylabel=ylabel, run=run, **kwargs)
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if subname_x:
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hdf5_x.close()
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@@ -1518,13 +1526,15 @@ class Plotter(Aggregator, BaseProcessor):
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This is where rules are defined
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"""
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self.rules = {
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"plot_comp": PlotRule(lambda arg, **kwargs: self._plot(*arg, **kwargs), kind="comp"
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"plot_comp": PlotRule(
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lambda arg, **kwargs: self._plot(*arg, **kwargs), kind="comp"
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),
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"plot_run": PlotRule(lambda arg, **kwargs: self._plot(*arg, **kwargs), kind="run"
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"plot_run": PlotRule(
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lambda arg, **kwargs: self._plot(*arg, **kwargs), kind="run"
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),
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"plot_snapshot": PlotRule(lambda arg, **kwargs: self._plot(*arg, **kwargs)
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),
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"plot_map": PlotRule(lambda mapname, **kwargs: self._plot_map(mapname, **kwargs)
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"plot_snapshot": PlotRule(lambda arg, **kwargs: self._plot(*arg, **kwargs)),
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"plot_map": PlotRule(
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lambda mapname, **kwargs: self._plot_map(mapname, **kwargs)
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),
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"coldens": PlotRule(
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partial(
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@@ -1955,7 +1965,7 @@ class Plotter(Aggregator, BaseProcessor):
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self._gen_from_log("fine_step_from_log", name)
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for name in ["time", "dt", "a", "mem_cells", "mem_parts"]:
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self._gen_from_log("fine_step_from_log", name_y=name, name_x="fine_step")
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self._gen_from_log("SN_momentum_from_log", name_x="time", name_y="SN_momentum")
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# Dict of overlays
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@@ -1963,7 +1973,7 @@ class Plotter(Aggregator, BaseProcessor):
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"g": partial(self._overlay_vector, "g"),
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"B": self._overlay_B,
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"vel": self._overlay_speed,
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"speed": self._overlay_speed,
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"speed": self._overlay_speed,
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"levels": self._overlay_levels,
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"contour": self._overlay_contour,
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"particles": self._overlay_particles,
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