Merge pull request #79 from mdecleir/refine_plotting

Refine plotting

Author: karllark

measure_extinction/data/hd229238_hd204172_ext.fits

@@ -7,7 +7,6 @@
 from astropy.io import fits
 from scipy.optimize import curve_fit
 
-from dust_extinction.parameter_averages import F04
 from astropy.modeling.powerlaws import PowerLaw1D
 from astropy.modeling import Parameter
 from astropy.modeling.fitting import LevMarLSQFitter
@@ -98,7 +97,7 @@ def _get_column_val(column):
         return float(column)
 
 
-def AverageExtData(extdatas):
+def AverageExtData(extdatas, min_number=3):
     """
     Generate the average extinction curve from a list of ExtData objects
 
@@ -107,6 +106,9 @@ def AverageExtData(extdatas):
     extdatas : list of ExtData objects
         list of extinction curves to average
 
+    min_number : int [default=3]
+        minimum number of extinction curves that are required to measure the average extinction; if less than min_number of curves are available at certain wavelengths, the average extinction will still be calculated, but the number of points (npts) at those wavelengths will be set to zero (e.g. used in the plotting)
+
     Returns
     -------
     aveext: ExtData object
@@ -117,7 +119,8 @@ def AverageExtData(extdatas):
     names = []
     bwaves = []
     for extdata in extdatas:
-        # check the data type of the extinction curves, and convert if needed
+        # check the data type of the extinction curve, and convert if needed
+        # the average curve must be calculated from the A(lambda)/A(V) curves
         if extdata.type != "alav" or extdata.type != "alax":
             extdata.trans_elv_alav()
 
@@ -136,7 +139,7 @@ def AverageExtData(extdatas):
     aveext.type = extdatas[0].type
     aveext.type_rel_band = extdatas[0].type_rel_band
 
-    # calculate the average for all spectral data
+    # collect all the extinction data
     bexts = {k: [] for k in aveext.names["BAND"]}
     for src in keys:
         exts = []
@@ -149,27 +152,39 @@ def AverageExtData(extdatas):
                     extdata.exts[src][np.where(extdata.npts[src] == 0)] = np.nan
                     exts.append(extdata.exts[src])
 
+        # calculate the average and uncertainties of the band extinction data
         if src == "BAND":
-            aveext.exts["BAND"] = []
-            aveext.npts["BAND"] = []
-            aveext.stds["BAND"] = []
-            aveext.uncs["BAND"] = []
-            for name in aveext.names["BAND"]:
-                aveext.exts["BAND"].append(np.nanmean(bexts[name]))
-                aveext.npts["BAND"].append(len(bexts[name]))
+            aveext.exts["BAND"] = np.zeros(len(names))
+            aveext.npts["BAND"] = np.zeros(len(names))
+            aveext.stds["BAND"] = np.zeros(len(names))
+            aveext.uncs["BAND"] = np.zeros(len(names))
+            for i, name in enumerate(aveext.names["BAND"]):
+                aveext.exts["BAND"][i] = np.nanmean(bexts[name])
+                aveext.npts["BAND"][i] = len(bexts[name])
 
                 # calculation of the standard deviation (this is the spread of the sample around the population mean)
-                aveext.stds["BAND"].append(np.nanstd(bexts[name], ddof=1))
+                aveext.stds["BAND"][i] = np.nanstd(bexts[name], ddof=1)
 
             # calculation of the standard error of the average (the standard error of the sample mean is an estimate of how far the sample mean is likely to be from the population mean)
             aveext.uncs["BAND"] = aveext.stds["BAND"] / np.sqrt(aveext.npts["BAND"])
 
+        # calculate the average and uncertainties of the spectral extinction data
         else:
             aveext.exts[src] = np.nanmean(exts, axis=0)
             aveext.npts[src] = np.sum(~np.isnan(exts), axis=0)
             aveext.stds[src] = np.nanstd(exts, axis=0, ddof=1)
             aveext.uncs[src] = aveext.stds[src] / np.sqrt(aveext.npts[src])
 
+        # take out the data points where less than a certain number of values was averaged, and give a warning
+        if min_number > 1:
+            aveext.npts[src][aveext.npts[src] < min_number] = 0
+            warnings.warn(
+                "The minimum number of "
+                + str(min_number)
+                + " extinction curves was not reached for certain wavelengths, and the number of points (npts) for those wavelengths was set to 0.",
+                UserWarning,
+            )
+
     return aveext
 
 
@@ -490,14 +505,12 @@ def calc_RV(self):
 
     def trans_elv_alav(self, av=None, akav=0.112):
         """
-        Transform E(lambda-V) to A(lambda)/A(V) by normalizing to
-        A(V) and adding 1. Default is to calculate A(V) from the
-        input elx curve. If A(V) value is passed, use that one instead.
+        Transform E(lambda-V) to A(lambda)/A(V) by normalizing to A(V) and adding 1. If A(V) is in the columns of the extdata object, use that value. If A(V) is passed explicitly, use that value instead. If no A(V) is available, calculate A(V) from the input elx curve.
 
         Parameters
         ----------
         av : float [default = None]
-            value of A(V) to use - otherwise calculate it
+            value of A(V) to use - otherwise take it from the columns of the object or calculate it
 
         akav : float  [default = 0.112]
            Value of A(K)/A(V), only needed if A(V) has to be calculated from the K-band extinction
@@ -514,10 +527,11 @@ def trans_elv_alav(self, av=None, akav=0.112):
             )
         else:
             if av is None:
-                self.calc_AV(akav=akav)
+                if "AV" not in self.columns.keys():
+                    self.calc_AV(akav=akav)
+                av = _get_column_val(self.columns["AV"])
 
             for curname in self.exts.keys():
-                av = _get_column_val(self.columns["AV"])
                 self.exts[curname] = (self.exts[curname] / av) + 1
                 self.uncs[curname] /= av
             # update the extinction curve type
@@ -1091,19 +1105,8 @@ def plot(
             fontsize for plot
         """
         if alax:
-            # compute A(V) if it is not available
-            if "AV" not in self.columns.keys():
-                self.trans_elv_alav()
-            av = _get_column_val(self.columns["AV"])
-            if self.type_rel_band != "V":  # not sure if this works (where is RV given?)
-                # use F04 model to convert AV to AX
-                rv = _get_column_val(self.columns["RV"])
-                emod = F04(rv)
-                (indx,) = np.where(self.type_rel_band == self.names["BAND"])
-                axav = emod(self.waves["BAND"][indx[0]])
-            else:
-                axav = 1.0
-            ax = axav * av
+            # transform the extinctions from E(lambda-V) to A(lambda)/A(V)
+            self.trans_elv_alav()
 
         for curtype in self.waves.keys():
             # do not plot the excluded data type(s)
@@ -1115,13 +1118,6 @@ def plot(
             y = self.exts[curtype]
             yu = self.uncs[curtype]
 
-            if (
-                alax and self.type == "elx"
-            ):  # in the case A(V) was already available and the curve has not been transformed yet
-                # convert E(lambda-X) to A(lambda)/A(X)
-                y = (y / ax) + 1.0
-                yu /= ax
-
             y = y / normval + yoffset
             yu = yu / normval
 
@@ -1160,6 +1156,7 @@ def plot(
                     color=annotate_color,
                     horizontalalignment="left",
                     rotation=annotate_rotation,
+                    rotation_mode="anchor",
                     fontsize=fontsize,
                 )
 

measure_extinction/extdata.py

@@ -9,21 +9,22 @@
 import numpy as np
 import astropy.units as u
 import pandas as pd
+import os
 
 from measure_extinction.extdata import ExtData
-from measure_extinction.utils.calc_ext import calc_ave_ext
 from dust_extinction.parameter_averages import CCM89
 
 
 def plot_average(
-    starpair_list,
     path,
+    filename="average_ext.fits",
     ax=None,
     extmodels=False,
     fitmodel=False,
     HI_lines=False,
     range=None,
     exclude=[],
+    log=False,
     spread=False,
     annotate_key=None,
     annotate_wave_range=None,
@@ -34,11 +35,11 @@ def plot_average(
 
     Parameters
     ----------
-    starpair_list : list of strings
-        List of star pairs for which to calculate and plot the average extinction curve, in the format "reddenedstarname_comparisonstarname" (no spaces)
-
     path : string
-        Path to the data files
+        Path to the average extinction curve fits file
+
+    filename : string [default="average_ext.fits"]
+        Name of the average extinction curve fits file
 
     ax : AxesSubplot [default=None]
         Axes of plot on which to add the average extinction curve if pdf=False
@@ -58,14 +59,17 @@ def plot_average(
     exclude : list of strings [default=[]]
         List of data type(s) to exclude from the plot (e.g., IRS)
 
+    log : boolean [default=False]
+        Whether or not to plot the wavelengths on a log-scale
+
     spread : boolean [default=False]
-        Whether or not to offset the average extinction curve from the other curves
+        Whether or not to offset the average extinction curve from the other curves (only relevant when pdf=False and ax=None)
 
     annotate_key : string [default=None]
-        type of data for which to annotate text (e.g., SpeX_LXD)
+        type of data for which to annotate text (e.g., SpeX_LXD) (only relevant when pdf=False and ax=None)
 
     annotate_wave_range : list of 2 floats [default=None]
-        min/max wavelength range for the annotation of the text
+        min/max wavelength range for the annotation of the text (only relevant when pdf=False and ax=None)
 
     pdf : boolean [default=False]
         - If False, the average extinction curve will be overplotted on the current plot (defined by ax)
@@ -75,11 +79,18 @@ def plot_average(
     -------
     Plots the average extinction curve
     """
-    # calculate the average extinction curve
-    calc_ave_ext(starpair_list, path)
-
-    # read in the average extinction curve
-    average = ExtData(path + "average_ext.fits")
+    # read in the average extinction curve (if it exists)
+    if os.path.isfile(path + filename):
+        average = ExtData(path + filename)
+    else:
+        warnings.warn(
+            "An average extinction curve with the name "
+            + filename
+            + " could not be found in "
+            + path
+            + ". Please calculate the average extinction curve first with the calc_ave_ext function in measure_extinction/utils/calc_ext.py.",
+            UserWarning,
+        )
 
     # make a new plot if requested
     if pdf:
@@ -116,14 +127,17 @@ def plot_average(
             zoom(ax, range)
 
         # finish configuring the plot
-        ax.set_title("average", fontsize=50)
-        ax.set_xscale("log")
+        if log:
+            ax.set_xscale("log")
         plt.xlabel(r"$\lambda$ [$\mu m$]", fontsize=1.5 * fontsize)
         ax.set_ylabel(
             average._get_ext_ytitle(ytype=average.type), fontsize=1.5 * fontsize
         )
         fig.savefig(path + "average_ext.pdf", bbox_inches="tight")
 
+        # return the figure and axes for additional manipulations
+        return fig, ax
+
     else:
         if spread:
             yoffset = -0.3
@@ -258,6 +272,7 @@ def plot_fitmodel(extdata, yoffset=0, res=False):
             plt.axhline(ls="--", c="k", alpha=0.5)
             plt.axhline(y=0.05, ls=":", c="k", alpha=0.5)
             plt.axhline(y=-0.05, ls=":", c="k", alpha=0.5)
+            plt.ylim(-0.1, 0.1)
             plt.ylabel("residual")
 
     else:
@@ -359,6 +374,9 @@ def plot_multi_extinction(
     range=None,
     spread=False,
     exclude=[],
+    log=False,
+    text_offsets=[],
+    text_angles=[],
     pdf=False,
 ):
     """
@@ -396,6 +414,15 @@ def plot_multi_extinction(
     exclude : list of strings [default=[]]
         List of data type(s) to exclude from the plot (e.g., IRS)
 
+    log : boolean [default=False]
+        Whether or not to plot the wavelengths on a log-scale
+
+    text_offsets : list of floats [default=[]]
+        List of the same length as starpair_list with offsets for the annotated text
+
+    text_angles : list of integers [default=[]]
+        List of the same length as starpair_list with rotation angles for the annotated text
+
     pdf : boolean [default=False]
         Whether or not to save the figure as a pdf file
 
@@ -419,13 +446,19 @@ def plot_multi_extinction(
     fig, ax = plt.subplots(figsize=(15, len(starpair_list) * 1.25))
     colors = plt.get_cmap("tab10")
 
+    # set default text offsets and angles
+    if text_offsets == []:
+        text_offsets = np.full(len(starpair_list), 0.2)
+    if text_angles == []:
+        text_angles = np.full(len(starpair_list), 10)
+
     for i, starpair in enumerate(starpair_list):
         # read in the extinction curve data
         extdata = ExtData("%s%s_ext.fits" % (path, starpair.lower()))
 
         # spread out the curves if requested
         if spread:
-            yoffset = 0.3 * i
+            yoffset = 0.25 * i
         else:
             yoffset = 0.0
 
@@ -455,8 +488,8 @@ def plot_multi_extinction(
             annotate_key=ann_key,
             annotate_wave_range=ann_range,
             annotate_text=extdata.red_file.split(".")[0].upper(),
-            annotate_yoffset=-0.1,
-            annotate_rotation=-15,
+            annotate_yoffset=text_offsets[i],
+            annotate_rotation=text_angles[i],
             annotate_color=colors(i % 10),
         )
 
@@ -477,7 +510,6 @@ def plot_multi_extinction(
     # plot the average extinction curve if requested
     if average:
         plot_average(
-            starpair_list,
             path,
             ax=ax,
             extmodels=extmodels,
@@ -501,16 +533,23 @@ def plot_multi_extinction(
         outname = outname.replace(".pdf", "_zoom.pdf")
 
     # finish configuring the plot
-    ax.set_xscale("log")
+    if log:
+        ax.set_xscale("log")
     ax.set_xlabel(r"$\lambda$ [$\mu m$]", fontsize=1.5 * fontsize)
-    ax.set_ylabel(extdata._get_ext_ytitle(ytype=extdata.type), fontsize=1.5 * fontsize)
+    ylabel = extdata._get_ext_ytitle(ytype=extdata.type)
+    if spread:
+        ylabel += " + offset"
+    ax.set_ylabel(ylabel, fontsize=1.5 * fontsize)
 
     # show the figure or save it to a pdf file
     if pdf:
         fig.savefig(path + outname, bbox_inches="tight")
     else:
         plt.show()
 
+    # return the figure and axes for additional manipulations
+    return fig, ax
+
 
 def plot_extinction(
     starpair,