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generatepdf.py
Klaas Kliffen authored
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generatepdf.py 8.35 KiB
"""Functions to generate PDF file"""
from datetime import datetime
import os
from fpdf import FPDF, HTMLMixin
import matplotlib.dates as mdates
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import plotly.io as pio
# Dummy class needed to generate the PDF file
class MyFPDF(FPDF, HTMLMixin):
"""Dummy class"""
pass
def convert_figure_to_axis_info(figure):
"""For a given Graph Figure object, return
xaxis (a list of datetime.datetime objects),
yaxis (a list of source elevation), and
label (name of the source as a string)."""
time_axis = figure['x']
xaxis = []
for val in time_axis:
d = datetime.strptime(val, '%Y-%m-%dT%H:%M:%S')
xaxis.append(d)
yaxis = figure['y']
label = figure['name']
return xaxis, yaxis, label
def make_pdf_plot(elevation_fig, outfilename):
pio.write_image(elevation_fig,outfilename, format='png')
# def make_pdf_plot(elevation_fig, outfilename):
# """For a given elevation_fig object and output filename, generate a
# matplotlib plot and write it to disk."""
# fig, ax = plt.subplots(1, 1, figsize=(8, 5))
# # The last figure containt the lst axis data, which is type str
# for figure in elevation_fig['data'][:-1]:
# xaxis, yaxis, label = convert_figure_to_axis_info(figure)
# ax.plot(xaxis, yaxis, label=label)
# hour_loc = (0, 3, 6, 9, 12, 15, 18, 21)
# ax.xaxis.set_major_locator(mdates.HourLocator(hour_loc))
# ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))
# plt.xlabel('Time (UTC)', fontsize=14)
# plt.ylabel('Elevation (deg)', fontsize=14)
# plt.title('Target visibility plot', fontsize=14)
# # Highlight sunrise
# sun_rise_dict = elevation_fig['layout']['shapes'][0]
# temp_date = sun_rise_dict['x0'].split('.')[0]
# x_min = datetime.strptime(temp_date, '%Y-%m-%dT%H:%M:%S')
# temp_date = sun_rise_dict['x1'].split('.')[0]
# x_max = datetime.strptime(temp_date, '%Y-%m-%dT%H:%M:%S')
# y_min = sun_rise_dict['y0']
# y_max = sun_rise_dict['y1']
# rect = Rectangle((x_min, y_min), width=x_max-x_min, height=y_max, fill=True,
# edgecolor=None, facecolor='lightskyblue')
# ax.add_patch(rect)
# # Highlight sunset
# sun_set_dict = elevation_fig['layout']['shapes'][1]
# temp_date = sun_set_dict['x0'].split('.')[0]
# x_min = datetime.strptime(temp_date, '%Y-%m-%dT%H:%M:%S')
# temp_date = sun_set_dict['x1'].split('.')[0]
# x_max = datetime.strptime(temp_date, '%Y-%m-%dT%H:%M:%S')
# y_min = sun_set_dict['y0']
# y_max = sun_set_dict['y1']
# rect = Rectangle((x_min, y_min), width=x_max-x_min, height=y_max, fill=True,
# edgecolor=None, facecolor='lightskyblue')
# ax.add_patch(rect)
# plt.ylim([0, 90])
# if len(elevation_fig['data']) > 1:
# ax.legend(fontsize=14)
# plt.tight_layout()
# plt.savefig(outfilename, dpi=100)
def generate_pdf(pdf_file, obs_t, n_core, n_remote, n_int, n_chan, n_sb, integ_t,
antenna_set, pipe_type, t_avg, f_avg, is_dysco, raw_size, proc_size,
pipe_time, sensitivity_table, elevation_fig, distance_table,
obs_date):
"""Function to generate a pdf file summarizing the content of the calculator.
Return nothing."""
# Create an A4 sheet
pdf = MyFPDF('P', 'mm', 'A4')
pdf.add_page()
pdf.set_font('Arial', '', 12)
# Generate an html string to be written to the file
string = '<table frame="hsides" align="center" width="80%">'
string += '<thead><tr><th width="70%" align="left">Parameter</th>'
string += '<th width="30%" align="left">Value</th></tr></thead>'
string += '<tbody>'
string += '<tr><td>Observation time (in seconds)</td>'
string += ' <td>{}</td></tr>'.format(obs_t)
string += '<tr><td>No. of stations</td>'
string += ' <td>({}, {}, {})</td></tr>'.format(n_core, n_remote, n_int)
string += '<tr><td>No. of subbands</td>'
string += ' <td>{}</td></tr>'.format(n_sb)
string += '<tr><td>No. of channels per subband</td>'
string += ' <td>{}</td></tr>'.format(n_chan)
string += '<tr><td>Integration time (in seconds)</td>'
string += ' <td>{}</td></tr>'.format(integ_t)
string += '<tr><td>Antenna set</td>'
string += ' <td>{}</td></tr>'.format(antenna_set)
string += '<tr></tr>'
if elevation_fig != {}:
# User has specified at least one source in the target setup
# Display the observation date in the table
string += '<tr><td>Observation date</td>'
string += ' <td>{}</td></tr>'.format(obs_date)
string += '<tr></tr>'
string += '<tr><td>Pipeline type</td>'
if pipe_type == 'none':
string += ' <td>{}</td></tr>'.format('None')
else:
string += ' <td>{}</td></tr>'.format('Preprocessing')
string += '<tr><td>Averaging factor (time, freq)</td>'
string += ' <td>{}, {}</td></tr>'.format(t_avg, f_avg)
string += '<tr><td>Dysco compression</td>'
if is_dysco == 'enable':
string += ' <td>{}</td></tr>'.format('enabled')
else:
string += ' <td>{}</td></tr>'.format('disabled')
string += '<tr><td>Raw data size (in GB)</td>'
string += ' <td>{}</td></tr>'.format(raw_size)
if pipe_type != 'none':
string += '<tr><td>Processed data size (in GB)</td>'
string += ' <td>{}</td></tr>'.format(proc_size)
string += '<tr><td>Pipeline processing time (in hours)</td>'
string += ' <td>{}</td></tr>'.format(pipe_time)
string += '</tbody>'
string += '</table>'
# Add the sensitivity table to the PDF
if sensitivity_table != {}:
title = sensitivity_table['layout']['title']['text']
string += '<center>{}</center>'.format(title)
string += '<table frame="hsides" align="center" style="table-layout: fixed width: 80%"><thead><tr>'
#col_titles = sensitivity_table['data'][0]['header']['values']
col_titles =['Target', "Mean elevation", "Theoretical rms", "Effective rms"]
col_width = 90//len(col_titles)
for item in col_titles:
string += '<th width="{}%" align="left">'.format(col_width) + \
item + '</th>'
string += '</tr></thead>'
string += '<tbody>'
tab_data = sensitivity_table['data'][0]['cells']['values']
# Transpose tab_data and write cells to the table
tab_data = list(map(list, zip(*tab_data)))
for row in tab_data:
string += '<tr>'
for item in row:
string += '<td>{}</td>'.format(item)
string += '</tr>'
string += '</tbody>'
string += '</table>'
# Generate a matplotlib plot showing the same plot as in the target
# visibility plot
if elevation_fig != {}:
# User has specified at least one source in the target setup
png_file_name = pdf_file.replace('summary', 'plot').replace('pdf', 'png')
make_pdf_plot(elevation_fig, png_file_name)
# Add the elevation plot to html
string += '<center>'
string += '<img src={} width=400 height=250>'.format(png_file_name)
string += '</center>'
# Add the distance table to the PDF
if distance_table != {}:
title = distance_table['layout']['title']['text']
string += '<center><b>{}</b></center>'.format(title)
string += '<table frame="hsides" align="center" width="80%">'
col_titles = distance_table['data'][0]['header']['values']
col_width = 100//len(col_titles)
string += '<thead><tr>'
for item in col_titles:
string += '<th width="{}%" align="left">'.format(col_width) + \
item + '</th>'
string += '</tr></thead>'
string += '<tbody>'
tab_data = distance_table['data'][0]['cells']['values']
# Transpose tab_data and write cells to the table
tab_data = list(map(list, zip(*tab_data)))
for row in tab_data:
string += '<tr>'
for item in row:
string += '<td>{}</td>'.format(item)
string += '</tr>'
string += '</tbody>'
string += '</table>'
# Write text to the pdf file
pdf.write_html(string)
# Write the pdf to disk
pdf.output(pdf_file)
# Remove the temporary PNG file from disk
if elevation_fig != {}:
os.remove(png_file_name)