Removal of matplotlib

Removes the matplotlib modules from the main container.

Change-Id: I26a0c171b2172dbf2be66cdf10b897bb72e4bf2b
JIRA: STORPERF-161
Signed-off-by: mbeierl <mark.beierl@dell.com>

2 files changed, 0 insertions, 90 deletions

diff --git a/storperf/plot/__init__.py b/storperf/plot/__init__.py
deleted file mode 100644
index e69de29..0000000
--- a/storperf/plot/__init__.py
+++ /dev/null
diff --git a/storperf/plot/barchart.py b/storperf/plot/barchart.py
deleted file mode 100644
index f82f3b8..0000000
--- a/storperf/plot/barchart.py
+++ /dev/null
@@ -1,90 +0,0 @@
-##############################################################################
-# Copyright (c) 2016 EMC and others.
-#
-# All rights reserved. This program and the accompanying materials
-# are made available under the terms of the Apache License, Version 2.0
-# which accompanies this distribution, and is available at
-# http://www.apache.org/licenses/LICENSE-2.0
-##############################################################################
-
-import cStringIO
-
-import matplotlib as mpl
-mpl.use('Agg')
-import matplotlib.pyplot as pyplot  # noqa: ignore E402
-from mpl_toolkits.mplot3d import Axes3D  # noqa: ignore E402, F401
-import numpy as np  # noqa: ignore E402
-
-
-class Barchart(object):
-
-    def __init__(self):
-        pass
-
-    def barchart3d(self, queue_depths, block_sizes, latencies, c, title):
-
-        fig = pyplot.figure()
-
-        data = np.array(latencies)
-
-        lx = len(data[0])          # Work out matrix dimensions
-        ly = len(data[:, 0])
-        xpos = np.arange(0, lx, 1)    # Set up a mesh of positions
-        ypos = np.arange(0, ly, 1)
-        xpos, ypos = np.meshgrid(xpos + 0.25, ypos + 0.25)
-
-        xpos = xpos.flatten()   # Convert positions to 1D array
-        ypos = ypos.flatten()
-        zpos = np.zeros(lx * ly)
-
-        dx = 0.5 * np.ones_like(zpos)
-        dy = dx.copy()
-        dz = data.flatten()
-
-        ax = fig.add_subplot(111, projection='3d')
-        ax.bar3d(xpos, ypos, zpos, dx, dy, dz, color=c)
-
-        ticksx = np.arange(0.5, len(block_sizes), 1)
-        pyplot.xticks(ticksx, block_sizes)
-
-        ticksy = np.arange(0.6, len(queue_depths), 1)
-        pyplot.yticks(ticksy, queue_depths)
-
-        ax.set_xlabel('Block Size')
-        ax.set_ylabel('Queue Depth')
-        ax.set_zlabel(title)
-
-        ticksx = np.arange(0.5, 3, 1)
-        pyplot.xticks(ticksx, block_sizes)
-
-    def barchart(self, queue_depths, block_sizes, read_latencies):
-        pyplot.figure()
-
-        y_pos = np.arange(len(block_sizes))
-        bar_width = 0.15
-
-        colors = ['r', 'g', 'b', 'y']
-        legend = []
-        index = 0
-        for series in queue_depths:
-            chart = pyplot.bar(y_pos + (bar_width * index),
-                               read_latencies[index],
-                               bar_width,
-                               color=colors[index],
-                               align='center',
-                               label="Queue Depth " + str(series),
-                               alpha=0.4)
-            legend.append(chart[0])
-            index += 1
-
-        pyplot.xticks(y_pos + bar_width, block_sizes)
-        pyplot.ylabel("Latency (Microseconds)")
-        pyplot.xlabel("Block Sizes (bytes)")
-        pyplot.title("Latency Report")
-        pyplot.legend()
-        pyplot.tight_layout()
-
-    def to_base64_image(self):
-        sio = cStringIO.StringIO()
-        pyplot.savefig(sio, format="png")
-        return sio.getvalue().encode("base64").strip()