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Flesh out stats with arguments

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This commit is contained in:
Jarrod Johnson 2019-04-25 14:45:47 -04:00
parent 33c1137ccf
commit bafc25005f
1 changed files with 30 additions and 12 deletions
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42
misc/stats
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@ -15,12 +15,10 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import argparse
import io
import numpy as np
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
import os
import sixel
import subprocess
@ -32,17 +30,37 @@ class DumbWriter(sixel.SixelWriter):
return
def plot(gui, output, plotdata):
import matplotlib as mpl
if not gui:
mpl.use('Agg')
import matplotlib.pyplot as plt
n, bins, patches = plt.hist(plotdata, 20)
plt.show()
if not gui:
if output:
tdata = output
else:
tdata = io.BytesIO()
plt.savefig(tdata)
if not gui and not output:
writer = DumbWriter()
writer.draw(tdata)
histogram = False
aparser = argparse.ArgumentParser(description='Quick access to common statistics')
aparser.add_argument('-c', type=int, default=0, help='Column number to analyze')
aparser.add_argument('-s', default=False, action='store_true', help='Output histogram in sixel format')
aparser.add_argument('-g', default=False, action='store_true', help='Open histogram in separate graphical window')
aparser.add_argument('-o', default=None, help='Output histogram to the specified filename in PNG format')
args = aparser.parse_args(sys.argv[1:])
plotdata = []
data = sys.stdin.readline()
while data:
datum = float(data.split()[-1])
datum = float(data.split()[args.c - 1])
plotdata.append(datum)
data = sys.stdin.readline()
n, bins, patches = plt.hist(plotdata, 20)
plt.show()
tdata = io.BytesIO()
plt.savefig(tdata)
writer = DumbWriter()
writer.draw(tdata)
print('Min: {3} Median: {0} Mean: {1} Max: {4} Standard Deviation: {2} Samples: {5}'.format(np.median(plotdata), np.mean(plotdata), np.std(plotdata), np.min(plotdata), np.max(plotdata), len(plotdata)))
if args.g or args.o or args.s:
plot(args.g, args.o, plotdata)
print('Samples: {5} Min: {3} Median: {0} Mean: {1} Max: {4} StandardDeviation: {2}'.format(np.median(plotdata), np.mean(plotdata), np.std(plotdata), np.min(plotdata), np.max(plotdata), len(plotdata)))