From 49965b4c80f228de26cd23152c7258a7752077ee Mon Sep 17 00:00:00 2001
From: alainmuls <alain.muls@gmail.com>
Date: Wed, 4 Nov 2020 15:39:51 +0100
Subject: [PATCH] wip markdown tables
---
glabv5_output.py | 64 ++++++++++++++++++++++++++++++++++++++++++------
1 file changed, 57 insertions(+), 7 deletions(-)
diff --git a/glabv5_output.py b/glabv5_output.py
index e405e81..c5a0350 100755
--- a/glabv5_output.py
+++ b/glabv5_output.py
@@ -56,9 +56,57 @@ def make_rgb_transparent(rgb, bg_rgb, alpha):
for (c1, c2) in zip(rgb, bg_rgb)]
+def table_header_str(col_headers: list) -> str:
+ """
+ table_header_str creates a hedaer line t
+ """
+ ret_str = ''
+ for header in col_headers:
+ ret_str += '| __{hdr:s}__ '.format(hdr=header)
+ ret_str += '|\n'
+ ret_str += '| ---: ' * len(col_headers)
+ ret_str += '|\n'
+
+ return ret_str
+
+
+def markdown_report(mode: str):
+ """
+ create a markdown report for the selected mode
+ """
+ md_name = '{out:s}-{mode:s}.markdown'.format(out=cvs_output_name.replace('.', '-'), mode=dProcModes[mode])
+ with open(md_name, 'w') as fout:
+ fout.write(table_header_str(DATES + ECEF + dECEF))
+
+ # determine indices of first / last 10 rows
+ start_idx = df_pos.loc[mode_idx][:10].index
+ end_idx = df_pos.loc[mode_idx][-10:].index
+
+ # write cartesian information
+ for i in start_idx:
+ for col in DATES:
+ fout.write('| {!s} '.format(df_pos.loc[mode_idx][col][i]))
+ for col in ECEF + dECEF:
+ fout.write('| {:.4f} '.format(df_pos.loc[mode_idx][col][i]))
+ fout.write('|\n')
+ fout.write('| ---: ' * 9)
+ fout.write('|\n')
+
+ print('end_idx = {!s}'.format(end_idx))
+ for i in start_idx:
+ for col in DATES:
+ fout.write('| {!s} '.format(df_pos.loc[mode_idx][col][i]))
+ for col in ECEF + dECEF:
+ fout.write('| {:.4f} '.format(df_pos.loc[mode_idx][col][i]))
+ fout.write('|\n')
+ # fout.write('| ---: ' * 9)
+ fout.write('\n')
+
+
# font for th elegend
legend_font = font_manager.FontProperties(family='monospace', weight='bold', style='normal', size='small')
+DATES = ['year', 'doy', 'sod', 'DT']
ECEF = ['X', 'Y', 'Z']
DeltaECEF = ['DeltaX', 'DeltaY', 'DeltaZ']
dECEF = ['dX', 'dY', 'dZ']
@@ -76,7 +124,7 @@ utm_colors = ['tab:green', 'tab:blue', 'tab:brown']
dop_colors = ['tab:green', 'tab:orange', 'tab:blue', 'tab:purple', 'tab:red', 'tab:brown']
rgb_colors = [mpcolors.colorConverter.to_rgb(color) for color in utm_colors]
-rgb_error_colors = [make_rgb_transparent(rgb, (1, 1, 1), 0.4) for rgb in rgb_colors]
+rgb_error_colors = [make_rgb_transparent(rgb, (1, 1, 1), 0.4 - i * 0.1) for i, rgb in enumerate(rgb_colors)]
# initialise the geodheight class
gh = geoid.GeoidHeight('/usr/share/GeographicLib/geoids/egm2008-1.pgm')
@@ -111,7 +159,7 @@ except IOError:
# List unique values in the ProcMode column "0 -> SPP, 1 -> PPP, 2 -> SBAS, 3 -> DGNSS"
dProcModes = {0: 'SPP', 1: 'PPP', 2: 'SBAS', 3: 'DGNSS'}
# proc_modes = df_pos.ProcMode.unique()
-print('Processing modes observed:')
+print('\nProcessing modes observed:')
proc_modes = df_pos['ProcMode'].value_counts()
# calculate the weighted average of cartesian, geodetic and NEU data for each observed mode
@@ -144,14 +192,13 @@ for mode, count in proc_modes.iteritems():
# create columns for difference wrt average UTM values used for plotting
df_tmp = pd.DataFrame()
df_tmp['DT'] = df_pos.loc[mode_idx]['DT']
- for crd, dutm in zip(UTM, dUTM):
- print(crd)
+ for crd in UTM:
df_tmp['Delta_{:s}'.format(crd)] = df_pos.loc[mode_idx][crd] - dwavg[crd]
df_tmp[dNEU] = df_pos.loc[mode_idx][dNEU]
df_tmp[XDOP] = df_pos.loc[mode_idx][XDOP]
df_tmp["#SVs"] = df_pos.loc[mode_idx]["#SVs"]
- print('df_tmp =\n{!s}'.format(df_tmp))
+ # print('df_tmp =\n{!s}'.format(df_tmp))
# plot the results
plt.style.use('ggplot')
@@ -172,7 +219,7 @@ for mode, count in proc_modes.iteritems():
ax1.set_title('UTM & Orto H')
ax1.set_xlabel('')
ax1.set_ylabel('Coordinate difference [m]')
- ax1.legend(prop=legend_font, bbox_to_anchor=(1.02, 1), loc='upper left')
+ ax1.legend(prop=legend_font, bbox_to_anchor=(1.02, 1), loc='upper left', markerscale=3)
# PLOT THE XDOP & #SVS VS DT
# df_tmp.plot(x='DT', y=XDOP, ax=ax2)
@@ -183,7 +230,7 @@ for mode, count in proc_modes.iteritems():
ax2v = ax2.twinx()
ax2v.set_ylim([0, 12])
ax2v.set_ylabel('#SVs [-]') # , fontsize='large', color='grey')
- ax2v.fill_between(x=df_tmp['DT'].values, y1=0, y2=df_tmp['#SVs'].values, alpha=0.15, linestyle='-', linewidth=3, color='grey', label='#SVs', interpolate=False)
+ ax2v.fill_between(x=df_tmp['DT'].values, y1=0, y2=df_tmp['#SVs'].values, alpha=0.25, linestyle='-', linewidth=3, color='grey', label='#SVs', interpolate=False)
# ax2v.fill_between(df_pos.loc[mode_idx]['DT'].values, 0, df_pos.loc[mode_idx]['#SVs'].values, facecolor='#0079a3', alpha=0.4)
# name the axis
@@ -198,6 +245,9 @@ for mode, count in proc_modes.iteritems():
# display / save the plot
plt.show()
+ # create markdown report
+ markdown_report(mode=mode)
+
# save the plot in subdir png of GNSSSystem
png_name = '{out:s}-{mode:s}.png'.format(out=cvs_output_name.replace('.', '-'), mode=dProcModes[mode])
fig.savefig(png_name, dpi=fig.dpi)
--
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