示例#1
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def thickness_uniformity(c_thickness_stats, l_thickness_stats, r_thickness_stats, cu1_measured, cu1_accepted, meco_c_thickness, cl):
  p4a = figure(plot_width=700, plot_height=400, title="Meco Thickness Comparison")

  c_measurements = [1,2,3,4,5,6,7,8]
  l_measurements = [1,5,8]
  r_measurements = [1,5,8]

  #Center thickness
  p4a.line(c_measurements, c_thickness_stats, line_width=2, legend='Center')
  p4a.circle(c_measurements, c_thickness_stats, fill_color='white', size=8)
  #Left thickness
  p4a.line(l_measurements, l_thickness_stats, line_width=2, legend='Left', color='orange')
  p4a.circle(l_measurements, l_thickness_stats, fill_color='white', size=8)
  #Right thickness
  p4a.line(r_measurements, r_thickness_stats, line_width=2, legend='Right', color='purple')
  p4a.circle(r_measurements, r_thickness_stats, fill_color='white', size=8)
  #Total number of measured grids
  p4a.line(c_measurements, c_thickness_stats, line_width=2, legend='Total Measured: ' + str(cu1_measured), color='green')
  #Sampling Percentage
  p4a.line(c_measurements, c_thickness_stats, line_width=2, legend='Total Accepted: ' + str(len(cu1_accepted)), color='green')

  p4a.xaxis.axis_label = 'Measurement Number'
  p4a.yaxis.axis_label = 'Thickness (mm)'

  #Normalize Center Thicknesses
  normalized_thickness = statfunctions.normalize(meco_c_thickness)
  n_thickness_stats = statfunctions.liststats(normalized_thickness, cl)

  p4b = figure(plot_width=700, plot_height=400, title="Center Thickness Control (Normalized)")
  p4b.line(c_measurements, n_thickness_stats['avg'], line_width=2, legend='Center')
  p4b.circle(c_measurements, n_thickness_stats['avg'], fill_color='white', size=8)
  #STD lines
  p4b.line(c_measurements, n_thickness_stats['ucl'], line_width=1, line_color='red', legend='2 Std Lines')
  p4b.line(c_measurements, n_thickness_stats['lcl'], line_width=1, line_color='red')
  p4b.xaxis.axis_label = 'Measurement Number'
  p4b.yaxis.axis_label = 'Thickness (mm)'

  return (p4a, p4b)
示例#2
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#####################################################################################
#IV. Retrieve data From Pandas to be used in Bokeh

cu1_ids = list(cu12_df[cu12_df['tool'] == 1].id)
cu1_weights = list(cu12_df[cu12_df['tool'] == 1].weight)
cu1_stats = statfunctions.stats(cu1_weights)

cu2_ids = list(cu12_df[cu12_df['tool'] == 2].id)
cu2_weights = list(cu12_df[cu12_df['tool'] == 2].weight)
cu2_stats = statfunctions.stats(cu2_weights)

m_ids = list(meco_df.id)
m_weights = list(meco_df.weight)
m_stats = statfunctions.stats(m_weights)

c_thickness_stats = statfunctions.liststats(meco_c_thickness)
l_thickness_stats = statfunctions.liststats(meco_l_thickness)
r_thickness_stats = statfunctions.liststats(meco_r_thickness)

######################################################################################
#V. Start Bokeh Plotting

first_items = first.split('/')
first_date = first_items[1] + '-' + first_items[0] + '-' + first_items[2]
last_items = last.split('/')
last_date = last_items[1] + '-' + last_items[0] + '-' + last_items[2]

if first_date == last_date:
	output_file(first_date + '.html', title=first_date)
else:
	output_file(first_date + ' to ' + last_date + '.html', title=first_date + ' to ' + last_date)
示例#3
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#####################################################################################
#Format Pandas df into list to be used in Bokeh

cu1_ids = list(cu12_df[cu12_df['tool'] == 1].id)
cu1_weights = list(cu12_df[cu12_df['tool'] == 1].weight)
cu1_stats = statfunctions.stats(cu1_weights)

cu2_ids = list(cu12_df[cu12_df['tool'] == 2].id)
cu2_weights = list(cu12_df[cu12_df['tool'] == 2].weight)
cu2_stats = statfunctions.stats(cu2_weights)

m_ids = list(meco_df.id)
m_weights = list(meco_df.weight)
m_stats = statfunctions.stats(m_weights)

c_thickness_stats = statfunctions.liststats(meco_c_thickness)
l_thickness_stats = statfunctions.liststats(meco_l_thickness)
r_thickness_stats = statfunctions.liststats(meco_r_thickness)

######################################################################################
#Start Bokeh Plotting

first_items = first.split('/')
first_date = first_items[1] + '-' + first_items[0] + '-' + first_items[2]
last_items = last.split('/')
last_date = last_items[1] + '-' + last_items[0] + '-' + last_items[2]

if first_date == last_date:
	output_file(first_date + '.html', title=first_date)
else:
	output_file(first_date + ' to ' + last_date + '.html', title=first_date + ' to ' + last_date)
示例#4
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######################################################################################
#Cu1 Plot
cu1_stats = statfunctions.stats(cu1_weight, cl)
p1 = graph_functions.create_histogram(cu1_stats['avg'], cu1_stats['std'], cu1_weight, 50, 1.2, 1.6, cu1_accepted, t1_failure_pos)

######################################################################################
#Cu2 Plot
cu2_stats = statfunctions.stats(cu2_weight, cl)
p2 = graph_functions.create_histogram(cu2_stats['avg'], cu2_stats['std'], cu2_weight, 50, .2, .55, cu2_accepted, t2_failure_pos)

######################################################################################
#Meco GridThicknesses
######################################################################################
#p3 = graph_functions.thickness_uniformity(statfunctions.liststats(meco_c_thickness, cl)['avg'], statfunctions.liststats(meco_l_thickness, cl)['avg'], statfunctions.liststats(meco_r_thickness, cl)['avg'], cu1_measured, cu1_accepted, meco_c_thickness, cl)[0]

c_thickness_stats = statfunctions.liststats(meco_c_thickness, cl)
l_thickness_stats = statfunctions.liststats(meco_l_thickness, cl)
r_thickness_stats = statfunctions.liststats(meco_r_thickness, cl)

p4a = figure(plot_width=700, plot_height=400, title="Meco Thickness Comparison")
c_measurements = [1,2,3,4,5,6,7,8]
l_measurements = [1,5,8]
r_measurements = [1,5,8]
#Center thickness
p4a.line(c_measurements, c_thickness_stats['avg'], line_width=2, legend='Center')
p4a.circle(c_measurements, c_thickness_stats['avg'], fill_color='white', size=8)
#Left thickness
p4a.line(l_measurements, l_thickness_stats['avg'], line_width=2, legend='Left', color='orange')
p4a.circle(l_measurements, l_thickness_stats['avg'], fill_color='white', size=8)
#Right thickness
p4a.line(r_measurements, r_thickness_stats['avg'], line_width=2, legend='Right', color='purple')
示例#5
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#####################################################################################
#Format Pandas df into list to be used in Bokeh

cu1_ids = list(cu12_df[cu12_df['tool'] == 1].id)
cu1_weights = list(cu12_df[cu12_df['tool'] == 1].weight)
cu1_stats = statfunctions.stats(cu1_weights)

cu2_ids = list(cu12_df[cu12_df['tool'] == 2].id)
cu2_weights = list(cu12_df[cu12_df['tool'] == 2].weight)
cu2_stats = statfunctions.stats(cu2_weights)

m_ids = list(meco_df.id)
m_weights = list(meco_df.weight)
m_stats = statfunctions.stats(m_weights)

c_thickness_stats = statfunctions.liststats(meco_c_thickness)
l_thickness_stats = statfunctions.liststats(meco_l_thickness)
r_thickness_stats = statfunctions.liststats(meco_r_thickness)

######################################################################################
#Start Bokeh Plotting

first_items = first.split('/')
first_date = first_items[1] + '-' + first_items[0] + '-' + first_items[2]
last_items = last.split('/')
last_date = last_items[1] + '-' + last_items[0] + '-' + last_items[2]

if first_date == last_date:
    output_file(first_date + '.html', title=first_date)
else:
    output_file(first_date + ' to ' + last_date + '.html',