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data_sharing_reports.py
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import os
import xlrd
from xlutils.copy import copy
from datetime import datetime as dt
from PIL import Image
from shutil import rmtree
from pcwg_tool import pcwg_inner_ranges
template_name = 'Share_1_template.xls'
sheet_map = {'Submission': 0,
'Meta Data': 1,
'Baseline': 2,
'REWS': 3,
'TI Renorm': 4,
'REWS and TI Renorm': 5,
'PDM': 6}
def wrt_cell_keep_style(value, sheet, row, col):
style = _get_cell_style(sheet, row, col)
sheet.write(row, col, value)
_apply_cell_style(style, sheet, row, col)
def _get_cell_style(sheet, row, col):
return sheet._Worksheet__rows.get(row)._Row__cells.get(col).xf_idx
def _apply_cell_style(style, sheet, row, col):
sheet._Worksheet__rows.get(row)._Row__cells.get(col).xf_idx = style
class pcwg_share1_rpt(object):
def __init__(self, analysis, version = 'Unknown', template = template_name, output_fname = (os.getcwd() + os.sep + 'Data Sharing Initiative 1 Report.xls')):
rb = xlrd.open_workbook(template, formatting_info=True)
self.workbook = copy(rb)
self.analysis = analysis
self.no_of_datasets = len(analysis.datasetConfigs)
self.output_fname = output_fname
self.version = version
def report(self):
self.write_submission_data(sheet_map['Submission'])
self.write_meta_data()
self.write_metrics()
self.insert_images()
self.export()
def write_meta_data(self):
sh = self.workbook.get_sheet(sheet_map['Meta Data'])
col = 2
used_inner_range = [self.analysis.innerRangeLowerShear, self.analysis.innerRangeUpperShear, self.analysis.innerRangeLowerTurbulence, self.analysis.innerRangeUpperTurbulence]
range_A = [pcwg_inner_ranges['A']['LSh'], pcwg_inner_ranges['A']['USh'], pcwg_inner_ranges['A']['LTI'], pcwg_inner_ranges['A']['UTI']]
range_B = [pcwg_inner_ranges['B']['LSh'], pcwg_inner_ranges['B']['USh'], pcwg_inner_ranges['B']['LTI'], pcwg_inner_ranges['B']['UTI']]
range_C = [pcwg_inner_ranges['C']['LSh'], pcwg_inner_ranges['C']['USh'], pcwg_inner_ranges['C']['LTI'], pcwg_inner_ranges['C']['UTI']]
if used_inner_range == range_A:
range_id = 'A'
elif used_inner_range == range_B:
range_id = 'B'
elif used_inner_range == range_C:
range_id = 'C'
else:
raise Exception('The inner range %s is not valid for use in the PCWG Sharing Initiative.' % used_inner_range)
manual_required_style = _get_cell_style(sh, 7, 2)
manual_optional_style = _get_cell_style(sh, 13, 2)
calculated_style = _get_cell_style(sh, 8, 2)
dset_header_style = _get_cell_style(sh, 6, 2)
man_req_rows = [7, 11, 12, 18, 19, 21, 26, 29]
man_opt_rows = [13, 14, 15, 16, 17, 20, 22, 28]
for conf in self.analysis.datasetConfigs:
sh.write(6, col, conf.invariant_rand_id)
_apply_cell_style(dset_header_style, sh, 6, col)
wsl = len(conf.windSpeedLevels) if self.analysis.rewsActive else None
wdr = len(conf.windDirectionLevels) if self.analysis.rewsActive else None
sh.write(8, col, wsl)
sh.write(9, col, wdr)
_apply_cell_style(calculated_style, sh, 8, col)
_apply_cell_style(calculated_style, sh, 9, col)
sh.write(10, col, range_id)
_apply_cell_style(calculated_style, sh, 10, col)
sh.write(23, col, self.analysis.config.diameter)
_apply_cell_style(calculated_style, sh, 23, col)
sh.write(24, col, self.analysis.config.hubHeight)
_apply_cell_style(calculated_style, sh, 24, col)
sh.write(25, col, self.analysis.config.ratedPower)
_apply_cell_style(calculated_style, sh, 25, col)
sh.write(27, col, int(min(self.analysis.dataFrame.loc[self.analysis.dataFrame[self.analysis.nameColumn] == conf.name, self.analysis.timeStamp].dt.year)))
_apply_cell_style(calculated_style, sh, 27, col)
for row in man_req_rows:
sh.write(row, col, None)
_apply_cell_style(manual_required_style, sh, row, col)
for row in man_opt_rows:
sh.write(row, col, None)
_apply_cell_style(manual_optional_style, sh, row, col)
col += 1
def write_submission_data(self, sheet_no):
sh = self.workbook.get_sheet(sheet_no)
wrt_cell_keep_style(self.analysis.uniqueAnalysisId, sh, 5, 2)
wrt_cell_keep_style(str(dt.now()), sh, 6, 2)
wrt_cell_keep_style(str(self.version), sh, 7, 2)
conf_inv_row, conf_row, ts_row, col = 11, 12, 13, 2
style_fntsz1 = _get_cell_style(sh, conf_row, col)
style = _get_cell_style(sh, conf_inv_row, col)
for conf in self.analysis.datasetConfigs:
sh.write(conf_inv_row, col, conf.invariant_rand_id)
_apply_cell_style(style, sh, conf_inv_row, col)
sh.write(conf_row, col, self.analysis.datasetUniqueIds[conf.name]['Configuration'])
_apply_cell_style(style_fntsz1, sh, conf_row, col)
sh.write(ts_row, col, self.analysis.datasetUniqueIds[conf.name]['Time Series'])
_apply_cell_style(style_fntsz1, sh, ts_row, col)
col += 1
styles_dict = {True: _get_cell_style(sh, 17, 2),
False: _get_cell_style(sh, 17, 3),
'N/A': _get_cell_style(sh, 18, 2)}
sh.write(17, 2, self.analysis.densityCorrectionActive)
_apply_cell_style(styles_dict[self.analysis.densityCorrectionActive], sh, 17, 2)
for col in [3,4,5]:
sh.write(17, col, False)
_apply_cell_style(styles_dict[False], sh, 17, col)
if self.analysis.rewsActive:
sh.write(18, 2, self.analysis.densityCorrectionActive)
_apply_cell_style(styles_dict[self.analysis.densityCorrectionActive], sh, 18, 2)
for col in [4,5]:
sh.write(18, col, False)
_apply_cell_style(styles_dict[False], sh, 18, col)
sh.write(18, 3, True)
_apply_cell_style(styles_dict[True], sh, 18, 3)
else:
for col in [2,3,4,5]:
sh.write(18, col, 'N/A')
_apply_cell_style(styles_dict['N/A'], sh, 18, col)
if self.analysis.turbRenormActive:
sh.write(19, 2, self.analysis.densityCorrectionActive)
_apply_cell_style(styles_dict[self.analysis.densityCorrectionActive], sh, 19, 2)
for col in [3,5]:
sh.write(19, col, False)
_apply_cell_style(styles_dict[False], sh, 19, col)
sh.write(19, 4, True)
_apply_cell_style(styles_dict[True], sh, 19, 4)
else:
for col in [2,3,4,5]:
sh.write(19, col, 'N/A')
_apply_cell_style(styles_dict['N/A'], sh, 19, col)
if (self.analysis.turbRenormActive and self.analysis.rewsActive):
sh.write(20, 2, self.analysis.densityCorrectionActive)
_apply_cell_style(styles_dict[self.analysis.densityCorrectionActive], sh, 20, 2)
sh.write(20, 5, False)
_apply_cell_style(styles_dict[False], sh, 20, 5)
for col in [3,4]:
sh.write(20, col, True)
_apply_cell_style(styles_dict[True], sh, 20, col)
else:
for col in [2,3,4,5]:
sh.write(20, col, 'N/A')
_apply_cell_style(styles_dict['N/A'], sh, 20, col)
if self.analysis.powerDeviationMatrixActive:
sh.write(21, 2, self.analysis.densityCorrectionActive)
_apply_cell_style(styles_dict[self.analysis.densityCorrectionActive], sh, 21, 2)
for col in [3,4]:
sh.write(21, col, False)
_apply_cell_style(styles_dict[False], sh, 21, col)
sh.write(21, 5, True)
_apply_cell_style(styles_dict[True], sh, 21, 5)
else:
for col in [2,3,4,5]:
sh.write(21, col, 'N/A')
_apply_cell_style(styles_dict['N/A'], sh, 21, col)
def write_metrics(self):
self._write_metrics_sheet('Baseline', self.analysis.pcwgErrorBaseline)
if self.analysis.turbRenormActive:
self._write_metrics_sheet('TI Renorm', self.analysis.pcwgErrorTurbRenor)
if self.analysis.rewsActive:
self._write_metrics_sheet('REWS', self.analysis.pcwgErrorRews)
if (self.analysis.turbRenormActive and self.analysis.rewsActive):
self._write_metrics_sheet('REWS and TI Renorm', self.analysis.pcwgErrorTiRewsCombined)
if self.analysis.powerDeviationMatrixActive:
self._write_metrics_sheet('PDM', self.analysis.pcwgErrorPdm)
def _write_metrics_sheet(self, sh_name, error_col):
self.__write_overall_metric_sheet(sh_name)
self.__write_by_ws_metric_sheet(sh_name, error_col)
if self.analysis.hasDirection:
self.__write_by_dir_metric_sheet(sh_name, error_col)
self.__write_by_time_metric_sheet(sh_name, error_col)
self.__write_by_range_metric_sheet(sh_name, error_col)
self.__write_by_four_cell_matrix_metric_sheet(sh_name, error_col)
self.__write_by_month_metric_sheet(sh_name, error_col)
def __write_overall_metric_sheet(self, sh_name):
sh = self.workbook.get_sheet(sheet_map[sh_name])
wrt_cell_keep_style(self.analysis.overall_pcwg_err_metrics[self.analysis.dataCount], sh, 3, 3)
wrt_cell_keep_style(self.analysis.overall_pcwg_err_metrics[sh_name + ' NME'], sh, 4, 3)
wrt_cell_keep_style(self.analysis.overall_pcwg_err_metrics[sh_name + ' NMAE'], sh, 5, 3)
def __write_by_ws_metric_sheet(self, sh_name, err_col):
df = self.analysis.binned_pcwg_err_metrics[self.analysis.normalisedWSBin][err_col]
sh = self.workbook.get_sheet(sheet_map[sh_name])
col = 3
for i in self.analysis.normalisedWindSpeedBins.centers:
try:
wrt_cell_keep_style(int(df.loc[i, 'Data Count']), sh, 7, col)
wrt_cell_keep_style(df.loc[i, 'NME'], sh, 8, col)
wrt_cell_keep_style(df.loc[i, 'NMAE'], sh, 9, col)
col += 1
except:
col += 1
def __write_by_dir_metric_sheet(self, sh_name, err_col):
df = self.analysis.binned_pcwg_err_metrics[self.analysis.pcwgDirectionBin][err_col]
sh = self.workbook.get_sheet(sheet_map[sh_name])
col = 3
for i in self.analysis.pcwgWindDirBins.centers:
try:
wrt_cell_keep_style(int(df.loc[i, 'Data Count']), sh, 19, col)
wrt_cell_keep_style(df.loc[i, 'NME'], sh, 20, col)
wrt_cell_keep_style(df.loc[i, 'NMAE'], sh, 21, col)
col += 1
except:
col += 1
def __write_by_time_metric_sheet(self, sh_name, err_col):
df = self.analysis.binned_pcwg_err_metrics[self.analysis.hourOfDay][err_col]
sh = self.workbook.get_sheet(sheet_map[sh_name])
col = 3
for i in range(0,24):
try:
wrt_cell_keep_style(int(df.loc[i, 'Data Count']), sh, 11, col)
wrt_cell_keep_style(df.loc[i, 'NME'], sh, 12, col)
wrt_cell_keep_style(df.loc[i, 'NMAE'], sh, 13, col)
col += 1
except:
col += 1
def __write_by_range_metric_sheet(self, sh_name, err_col):
df = self.analysis.binned_pcwg_err_metrics[self.analysis.pcwgRange][err_col]
sh = self.workbook.get_sheet(sheet_map[sh_name])
col = 3
for i in ['Inner','Outer']:
try:
wrt_cell_keep_style(int(df.loc[i, 'Data Count']), sh, 23, col)
wrt_cell_keep_style(df.loc[i, 'NME'], sh, 24, col)
wrt_cell_keep_style(df.loc[i, 'NMAE'], sh, 25, col)
col += 1
except:
col += 1
def __write_by_four_cell_matrix_metric_sheet(self, sh_name, err_col):
df = self.analysis.binned_pcwg_err_metrics[self.analysis.pcwgFourCellMatrixGroup][err_col]
sh = self.workbook.get_sheet(sheet_map[sh_name])
col = 3
for i in ['LWS-LTI','LWS-HTI','HWS-LTI','HWS-HTI']:
try:
wrt_cell_keep_style(int(df.loc[i, 'Data Count']), sh, 27, col)
wrt_cell_keep_style(df.loc[i, 'NME'], sh, 28, col)
wrt_cell_keep_style(df.loc[i, 'NMAE'], sh, 29, col)
col += 1
except:
col += 1
def __write_by_month_metric_sheet(self, sh_name, err_col):
df = self.analysis.binned_pcwg_err_metrics[self.analysis.calendarMonth][err_col]
sh = self.workbook.get_sheet(sheet_map[sh_name])
col = 3
for i in range(1,13):
try:
wrt_cell_keep_style(int(df.loc[i, 'Data Count']), sh, 15, col)
wrt_cell_keep_style(df.loc[i, 'NME'], sh, 16, col)
wrt_cell_keep_style(df.loc[i, 'NMAE'], sh, 17, col)
col += 1
except:
col += 1
def insert_images(self):
from plots import MatplotlibPlotter
plt_path = 'Temp'
plotter = MatplotlibPlotter(plt_path, self.analysis)
for conf in self.analysis.datasetConfigs:
sh = self.workbook.add_sheet(conf.invariant_rand_id)
row_filt = (self.analysis.dataFrame[self.analysis.nameColumn] == conf.name)
fname = (conf.invariant_rand_id) + ' Anonymous Power Curve Plot'
plotter.plotPowerCurve(self.analysis.inputHubWindSpeed, self.analysis.actualPower, self.analysis.innerMeasuredPowerCurve, anon = True, row_filt = row_filt, fname = fname + '.png', show_analysis_pc = False, mean_title = 'Inner Range Power Curve', mean_pc_color = '#FF0000')
im = Image.open(plt_path + os.sep + fname + '.png').convert('RGB')
im.save(plt_path + os.sep + fname + '.bmp')
sh.write(0, 0, 'Power curve scatter plot for dataset with invariant random ID ' + (conf.invariant_rand_id) + '. The Inner Range Power Curve shown is derived using all datasets.')
sh.insert_bitmap(plt_path + os.sep + fname + '.bmp' , 2, 1)
try:
rmtree(plt_path)
except:
print 'Could not delete folder %s' % (os.getcwd() + os.sep + plt_path)
def export(self):
self._write_confirmation_of_export()
print "Exporting the PCWG Share 1 report to:\n\t%s" % (self.output_fname)
self.workbook.save(self.output_fname)
def _write_confirmation_of_export(self):
sh = self.workbook.get_sheet(sheet_map['Submission'])
wrt_cell_keep_style(True, sh, 8, 2)