Dendrograms

dendrogram.ipynb

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    "# Defining colours\n",
    "mycol_regions = ['#00cc00', '#ffb266', '#BF7DFF', '#cc6600', '#e31a1c', '#0331E9']\n",
    "#order = ETH, LA, NEKH, NKH, VN, WKH\n",
    "mycol_clades = ['#e0e0e0', '#0331E9', '#e31a1c', '#ffb266', '#BF7DFF', '#00cc00']\n",
    "#order = -, A, B, C, D, E"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_dendrogram(dist, nhaps, ax, method='complete', color_threshold=0, above_threshold_color='k'):\n",
    "    \n",
    "    # faff\n",
    "    y = _convert_to_double(np.asarray(dist, order='c'))\n",
    "    \n",
    "    # 2. get n\n",
    "    n = int(distance.num_obs_y(dist))\n",
    "    \n",
    "    # 3. do clustering\n",
    "    method = dict(single=0, complete=1)[method]\n",
    "    z = _hierarchy.linkage(y, n, method)    \n",
    "\n",
    "    # plot dendrogram\n",
    "    sns.despine(ax=ax, offset=5, bottom=True, top=False)\n",
    "    r = scipy.cluster.hierarchy.dendrogram(\n",
    "        z, no_labels=True, count_sort=True,\n",
    "        color_threshold=color_threshold, \n",
    "        above_threshold_color=above_threshold_color,\n",
    "        ax=ax)\n",
    "    \n",
    "    xmin, xmax = ax.xaxis.get_data_interval()\n",
    "    xticklabels = np.array(list(range(0, nhaps, 200)) + [nhaps])\n",
    "    \n",
    "    xticks = xticklabels / nhaps\n",
    "    xticks = (xticks * (xmax - xmin)) + xmin\n",
    "    ax.set_xticks(xticks)\n",
    "    ax.set_xticklabels(xticklabels)\n",
    "    ax.set_xlabel('ESEA KEL1/PLA1 samples')\n",
    "    ax.xaxis.set_label_position('top')\n",
    "    ax.set_ylim(bottom=-0.0001)\n",
    "#     ax.set_xlim(left=-10)\n",
    "    ax.set_ylabel('Genetic distance')\n",
    "\n",
    "    ax.autoscale(axis='x', tight=True)\n",
    "    return z, r"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_color_bar(meta, variable, ax, ix):\n",
    "    \n",
    "    x = meta.iloc[ix]\n",
    "    \n",
    "    values = pd.Categorical(x[variable])\n",
    "    \n",
    "    pal = mycol_regions\n",
    "        \n",
    "    clrs = dict(zip(values.categories, pal))\n",
    "    \n",
    "    ax.broken_barh(\n",
    "        xranges=[(i, 1) for i in range(x.shape[0])], \n",
    "        yrange=(0, 1), \n",
    "        color=[clrs[v] for v in values])\n",
    "    \n",
    "    sns.despine(ax=ax, offset=5, left=True, bottom=True)\n",
    "    ax.set_xticks([])\n",
    "    ax.set_yticks([])\n",
    "    ax.set_xlim(0, x.shape[0])\n",
    "    ax.yaxis.set_label_position('left')\n",
    "    ax.set_ylabel(variable, rotation=0, ha='right', va='center')\n",
    "    \n",
    "    return clrs, values"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure(figsize=(10, 8))\n",
    "gs = GridSpec(4, 1, height_ratios=(3, 1, 1, 1), )\n",
    "\n",
    "ax1 = plt.subplot(gs[0])\n",
    "zz, rr = plot_dendrogram(pdist_np_select_linear, df_meta_matched.shape[0], ax1)\n",
    "\n",
    "for i, x in enumerate([\"RegionCode\", \"K1P_clade\"]):\n",
    "    ax2 = plt.subplot(gs[i + 1])\n",
    "    col_dict, v = make_color_bar(\n",
    "        df_meta_matched, \n",
    "        x, \n",
    "        ax2,\n",
    "        rr[\"leaves\"])\n",
    "    \n",
    "    handles = [\n",
    "        mpl.patches.Patch(\n",
    "            color=v, label=k) for k, v in col_dict.items()]\n",
    "\n",
    "    ax2.legend(\n",
    "        handles=handles, \n",
    "        loc=0, \n",
    "        bbox_to_anchor=(1, 1), ncol=6)\n"
   ]
  }
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