plotting cleanup

genda/eQTL/plotting.py

@@ -1,30 +1,17 @@
 """ Plotting functions for eQTLs
 """
-from collections import defaultdict
-import re
 
 import numpy as np
 import pandas as pd
 import matplotlib
 import statsmodels.api as sm
 import matplotlib.pyplot as plt
-from statsmodels.graphics import utils as smutils
 from statsmodels.graphics.regressionplots import abline_plot
 
-from genda.plotting import (should_not_plot, add_gene_bounderies,
-        snp_arrow)
+from genda.plotting import (should_not_plot, snp_arrow)
 from genda import calculate_minor_allele_frequency, calculate_ld
 
 
-def var_boxplot(ax, x, colors=None):
-    """
-    Arguments:
-    ----------
-    ax - axis object
-    """
-    for i in x:
-        pass
-
 
 class gene_reference(object):
     """
@@ -150,7 +137,6 @@ def plot_eQTL(meQTL, gene_name, annotation, dosage, ax=None,
     else: pass
 
     x_formatter = matplotlib.ticker.ScalarFormatter(useOffset=False)
-    cm = plt.cm.get_cmap('Blues')
     x_scale= 1e6
     try:
         adj_pv = -1*np.log10(subset.ix[:,'p-value'])

genda/plotting/annotation.py

@@ -6,28 +6,17 @@ def snp_arrow(pos, height, snpid, ax):
 
     pos - an object with pos and height
     height - height
+    snpid - text label for the arrow
     ax - matplotlib axes
 
     """
 
-    rel_width = 25
-
+    rel_width = 15
     p_width = ax.get_xlim()
     p_height = ax.get_ylim()
-    '''
     spacer = (p_height[1] - p_height[0])/rel_width
-    a_head_width = (p_width[1] - p_width[0])/rel_width
-    a_head_length = p_height[1] - p_height[0]/rel_width
-    arrow_length = p_height - height - spacer
-    ax.arrow(pos, p_height[1], 0, 
-            arrow_length, 
-            head_width = a_head_width,
-            head_length = a_head_length, 
-            fc = 'k')
-    '''
-
     ax.annotate(snpid, xy=(pos, height),
-            xytext = (pos, p_height[1]),
+            xytext = (pos, p_height[1] - spacer),
             arrowprops=dict(facecolor='black', shrink=0.05))