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Graph_CSU_Data.py
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Graph_CSU_Data.py
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#####################################################################
#
# Predictive Failure Analysis (PFA)
# Graph Common Storage Data
#
#This python script is for use with data that is collected, created,
#and written by the PFA_COMMON_STORAGE_USAGE check only. Its
#use with data from any other source will result in errors.
#
#Copyright 2021 IBM Corp.
#
#Licensed under the Apache License, Version 2.0 (the "License");
#you may not use this file except in compliance with the License.
#You may obtain a copy of the License at
#
#http://www.apache.org/licenses/LICENSE-2.0
#
#Unless required by applicable law or agreed to in writing,
#software distributed under the License is distributed on an
#"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,
#either express or implied. See the License for the specific
#language governing permissions and limitations under the License.
#####################################################################
import sys
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import numpy as np
import platform
import os
#Make sure we have plenty of potential data points to plot.
plt.rcParams['agg.path.chunksize']=10000
#Disable false positive warning
pd.options.mode.chained_assignment = None # default='warn'
#Which system are we running on?
system = platform.system()
keys = {"CSA":"C","SQA":"S","CSA+SQA":"B","ECSA":"E","ESQA":"Q","ECSA+ESQA":"A"}
user_keys = ["CSA","SQA","CSA+SQA","ECSA","ESQA","ECSA+ESQA"]
resource_header_data = ["Key","Location","STCK_Time","Current_Usage","Date_Time"]
capacity_header_data = ["Key","Location","Capacity"]
check_name = "PFA_Common_Storage_Usage"
SQUAD_A_USERKEYS = {0:'ECSA',1:'ESQA',2:'ECSA+ESQA'}
SQUAD_B_USERKEYS = {0:'CSA',1:'SQA',2:'CSA+SQA'}
SQUAD_A_KEYS = {0:'E',1:'Q',2:'A'}
SQUAD_B_KEYS = {0:'C',1:'S',2:'B'}
#Parse our command line arguments.
if(len(sys.argv) == 4):
data_filepath = sys.argv[1]
capacity_filepath = sys.argv[2]
key = sys.argv[3]
key = key.upper()
verbose = False
elif(len(sys.argv) == 5 and (sys.argv[4] == '-v' or sys.argv[4] == '-verbose')):
data_filepath = sys.argv[1]
capacity_filepath = sys.argv[2]
key = sys.argv[3]
key = key.upper()
verbose = True
elif(len(sys.argv) == 2 and (sys.argv[1] == '-h' or sys.argv[1] == '-help')):
print("The proper syntax for this script is the following:\n")
print("python Graph_CSU_Data.py data_file_path capacity_file_path storage_location optional_parameters \n")
print("Valid storage locations are: " + str([key for key in user_keys]) + "\n")
print("The data_file_path and the capacity_file_path are case sensitive.\n")
print("For example, if this script and the required files are in the same directory, you would specify the following to graph the CSA usage of the SY1 system:\n")
print("'python Graph_CSU_Data.py SY1.5day.data SY1.capacity CSA' \n")
print("You can also add -v to the end of the command for verbose mode. This optional parameter will print additional data that could help debug errors or verify the results. An example using verbose mode looks like the following:\n")
print("'python Graph_CSU_Asid.py SY1.5day.data SY1.capacity CSA -v' \n")
print("When this script is executed on z/OS, it saves the graph in a .pdf file that can be downloaded from the directory where this script was executed and displayed anywhere that supports displaying a .pdf file.")
print("The file name is in the format of StorageLocation_graph.pdf.")
print("For example, if you entered 'python Graph_CSU_Data.py SY1.5day.data SY1.capacity CSA' on z/OS the saved file would be:")
print("CSA_graph.pdf and it would be located in the current working directory.")
sys.exit()
else:
raise Exception("The supplied arguments are not correct. Specify the data_file_path, capacity_file_path, and storage_location in that order. For help enter 'python Graph_CSU_Data.py -h'")
#Make sure we have proper input from the user.
if(not os.path.exists(data_filepath)):
raise Exception("The specified file or filepath for the data file does not exist. Verify the file and filepath then try again.")
if(not os.path.exists(capacity_filepath)):
raise Exception("The specified file or filepath for the capacity file does not exist. Verify the file and filepath then try again.")
if key not in user_keys:
raise Exception("The specified storage_location is not allowed. Valid storage locations are:" + str([key for key in user_keys]))
#Load up our data and assign correct header values so we can narrow it down to the pieces we want.
data_file = pd.read_csv(data_filepath,
sep="/|,",
names=resource_header_data,
header=None,
engine="python")
capacity_file = pd.read_csv(capacity_filepath,
sep="/|,",
names=capacity_header_data,
header=None,
engine="python")
user_key = key
key = keys[user_key]
if key not in data_file.values:
raise Exception("The specified storage_location does not exist. Verify the storage_location and try again.")
data_file['Capacity'] = np.nan
NUM_TO_PRINT = 10
PDF_FILENAME = user_key+"_graph.pdf" #This is the name of the .pdf file that gets saved when this script is ran on z/OS
def process_data(data_file, capacity_file,key,user_key):
the_capacity = capacity_file.loc[capacity_file['Key'] == key,'Capacity'].values[0]
the_data = data_file.loc[data_file['Key'] == key]
the_data['Capacity'].fillna(the_capacity, inplace=True)
the_data['Capacity'] = the_data['Capacity'].astype(int)
the_data.loc[:,('Date_Time')] = pd.to_datetime(the_data['Date_Time'].astype(str), format='%Y%m%d%H%M%S')
if(verbose):
print_details(the_data, NUM_TO_PRINT)
return the_data
def graph_data(the_data):
the_y_values, y_ticks = process_yvalues_yticks(the_data)
fig, ax = plt.subplots()
ax.xaxis.set_major_formatter(mdates.DateFormatter('%m-%d %H:%M'))
ax.plot(the_data['Date_Time'],the_data['Capacity'],'--r', label='Capacity')
ax.plot(the_data['Date_Time'],the_data['Current_Usage']/1024,'-b', label='Current Usage')
plt.xlabel('Month-Day Time')
fig.suptitle(check_name + "\n" + user_key, fontsize=16)
fig.autofmt_xdate()
plt.yticks(the_y_values, y_ticks)
ax.set_ylim(0,the_data['Capacity'].max()*1.10)
ax.legend(bbox_to_anchor=(1.41, 1),loc="upper right")
fig.subplots_adjust(right=0.75)
if system != 'z/OS':
plt.show();
else:
fig.savefig(PDF_FILENAME)
def graph_total_data(the_data,squad_userkeys):
fig, axes = plt.subplots(nrows = len(the_data), ncols = 1,sharex = True)
y_values = {}
y_ticks = {}
for i in range(len(the_data)):
y_values[i], y_ticks[i] = process_yvalues_yticks(the_data[i])
axes[i].xaxis.set_major_formatter(mdates.DateFormatter('%m-%d %H:%M'))
axes[i].set_ylim(0,the_data[i]['Capacity'].max()*1.10)
axes[i].plot(the_data[i]['Date_Time'],the_data[i]['Capacity'],'--r', label='Capacity')
axes[i].plot(the_data[i]['Date_Time'],the_data[i]['Current_Usage']/1024,'-b', label='Current Usage')
axes[i].set_title(squad_userkeys[i])
axes[i].set_yticks(y_values[i], y_ticks[i])
plt.sca(axes[i])
plt.yticks(y_values[i], y_ticks[i])
axes[i].tick_params(axis='both', which='both',labelsize=7)
for tick in axes[0].get_xticklabels():
tick.set_visible(True)
plt.xlabel('Month-Day Time')
fig.suptitle(check_name + "\n" + user_key, fontsize=16)
fig.autofmt_xdate()
axes[0].legend(bbox_to_anchor=(1.41, 1),loc="upper right")
if system != 'z/OS':
plt.show();
else:
fig.savefig(PDF_FILENAME)
def process_yvalues_yticks(data_file):
y_values = [0,(data_file['Capacity'].max())*.25,(data_file['Capacity'].max())*.50,(data_file['Capacity'].max())*.75,(data_file['Capacity'].max())]
y_ticks = [str(int(y)) + "KB" for y in y_values]
return y_values, y_ticks
def print_details(data_frame, num_to_print):
print("Now graphing " + check_name + " data on a " + system + " system.")
print("storage_location is: " + user_key)
print("data_file_path entered: " + data_filepath)
print("capacity_file_path entered was: " + capacity_filepath)
print("\nPreview of the data being graphed:")
print(data_frame.head(NUM_TO_PRINT).to_string(index=False))
data_collection = {}
#Process and graph our data.
if key == 'A': #ECSA+ESQA
for i in range(3):
data_collection[i] = process_data(data_file, capacity_file, SQUAD_A_KEYS[i], SQUAD_A_USERKEYS[i])
graph_total_data(data_collection, SQUAD_A_USERKEYS)
elif key == 'B': #CSA+SQA
for i in range(3):
data_collection[i] = process_data(data_file, capacity_file, SQUAD_B_KEYS[i], SQUAD_B_USERKEYS[i])
graph_total_data(data_collection, SQUAD_B_USERKEYS)
else:
the_data = process_data(data_file, capacity_file, key, user_key)
graph_data(the_data)
if system == 'z/OS':
print(PDF_FILENAME + ' has been created and is ready to be downloaded and viewed.')