From 3e20ee732e8a91225feb9cd78e58689b5410d857 Mon Sep 17 00:00:00 2001 From: Jake Herbst Date: Wed, 11 May 2022 07:56:41 -0400 Subject: [PATCH] Updating script/daily_plot.py to satisfy pep8 style guide Used 'autopep8 --in-place --aggressive scripts/daily_plot.py' as initial style fixes. --- scripts/daily_plot.py | 209 ++++++++++++++++++++++++++++-------------- 1 file changed, 138 insertions(+), 71 deletions(-) diff --git a/scripts/daily_plot.py b/scripts/daily_plot.py index e2147b0..a3e8a42 100755 --- a/scripts/daily_plot.py +++ b/scripts/daily_plot.py @@ -12,80 +12,113 @@ userDir = os.path.expanduser('~') conn = sqlite3.connect(userDir + '/BirdNET-Pi/scripts/birds.db') df = pd.read_sql_query("SELECT * from detections", conn) cursor = conn.cursor() -cursor.execute('SELECT * FROM detections WHERE Date = DATE(\'now\', \'localtime\')') +cursor.execute( + 'SELECT * FROM detections WHERE Date = DATE(\'now\', \'localtime\')') table_rows = cursor.fetchall() -#df=pd.DataFrame(table_rows) +# df=pd.DataFrame(table_rows) -#Convert Date and Time Fields to Panda's format -df['Date']=pd.to_datetime(df['Date']) -df['Time']=pd.to_datetime(df['Time'], unit='ns') +# Convert Date and Time Fields to Panda's format +df['Date'] = pd.to_datetime(df['Date']) +df['Time'] = pd.to_datetime(df['Time'], unit='ns') -#Add round hours to dataframe +# Add round hours to dataframe df['Hour of Day'] = [r.hour for r in df.Time] -#Create separate dataframes for separate locations -df_plt=df #Default to use the whole Dbase +# Create separate dataframes for separate locations +df_plt = df # Default to use the whole Dbase -#Get todays readings +# Get todays readings now = datetime.now() -df_plt_today = df_plt[df_plt['Date']==now.strftime("%Y-%m-%d")] +df_plt_today = df_plt[df_plt['Date'] == now.strftime("%Y-%m-%d")] -#Set number of species to report -readings=10 +# Set number of species to report +readings = 10 plt_top10_today = (df_plt_today['Com_Name'].value_counts()[:readings]) -df_plt_top10_today = df_plt_today[df_plt_today.Com_Name.isin(plt_top10_today.index)] +df_plt_top10_today = df_plt_today[df_plt_today.Com_Name.isin( + plt_top10_today.index)] -#Set Palette for graphics +# Set Palette for graphics pal = "Greens" -#Set up plot axes and titles -f, axs = plt.subplots(1, 2, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 6]), facecolor='#77C487') -plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0, hspace=0) +# Set up plot axes and titles +f, axs = plt.subplots( + 1, 2, figsize=( + 10, 4), gridspec_kw=dict( + width_ratios=[ + 3, 6]), facecolor='#77C487') +plt.subplots_adjust( + left=None, + bottom=None, + right=None, + top=None, + wspace=0, + hspace=0) -#generate y-axis order for all figures based on frequency -freq_order = pd.value_counts(df_plt_top10_today['Com_Name']).iloc[:readings].index +# generate y-axis order for all figures based on frequency +freq_order = pd.value_counts( + df_plt_top10_today['Com_Name']).iloc[:readings].index -#make color for max confidence --> this groups by name and calculates max conf +# make color for max confidence --> this groups by name and calculates max conf confmax = df_plt_top10_today.groupby('Com_Name')['Confidence'].max() -#reorder confmax to detection frequency order +# reorder confmax to detection frequency order confmax = confmax.reindex(freq_order) # norm values for color palette norm = plt.Normalize(confmax.values.min(), confmax.values.max()) colors = plt.cm.Greens(norm(confmax)) -#Generate frequency plot -plot=sns.countplot(y='Com_Name', data = df_plt_top10_today, palette = colors, order=freq_order, ax=axs[0]) +# Generate frequency plot +plot = sns.countplot( + y='Com_Name', + data=df_plt_top10_today, + palette=colors, + order=freq_order, + ax=axs[0]) - - -#Try plot grid lines between bars - problem at the moment plots grid lines on bars - want between bars -z=plot.get_ymajorticklabels() -plot.set_yticklabels(['\n'.join(textwrap.wrap(ticklabel.get_text(),15)) for ticklabel in plot.get_yticklabels()], fontsize = 10) +# Try plot grid lines between bars - problem at the moment plots grid +# lines on bars - want between bars +z = plot.get_ymajorticklabels() +plot.set_yticklabels(['\n'.join(textwrap.wrap(ticklabel.get_text(), 15)) + for ticklabel in plot.get_yticklabels()], fontsize=10) plot.set(ylabel=None) plot.set(xlabel="Detections") -#Generate crosstab matrix for heatmap plot +# Generate crosstab matrix for heatmap plot -heat = pd.crosstab(df_plt_top10_today['Com_Name'],df_plt_top10_today['Hour of Day']) -#Order heatmap Birds by frequency of occurrance -heat.index = pd.CategoricalIndex(heat.index, categories = freq_order) +heat = pd.crosstab( + df_plt_top10_today['Com_Name'], + df_plt_top10_today['Hour of Day']) +# Order heatmap Birds by frequency of occurrance +heat.index = pd.CategoricalIndex(heat.index, categories=freq_order) heat.sort_index(level=0, inplace=True) -hours_in_day = pd.Series(data = range(0,24)) -heat_frame = pd.DataFrame(data=0, index=heat.index, columns = hours_in_day) -heat=(heat+heat_frame).fillna(0) +hours_in_day = pd.Series(data=range(0, 24)) +heat_frame = pd.DataFrame(data=0, index=heat.index, columns=hours_in_day) +heat = (heat + heat_frame).fillna(0) -#Generatie heatmap plot -plot = sns.heatmap(heat, norm=LogNorm(), annot=True, annot_kws={"fontsize":7}, fmt="g", cmap = pal , square = False, cbar=False, linewidths = 0.5, linecolor = "Grey", ax=axs[1], yticklabels = False) -plot.set_xticklabels(plot.get_xticklabels(), rotation = 0, size = 7) +# Generatie heatmap plot +plot = sns.heatmap( + heat, + norm=LogNorm(), + annot=True, + annot_kws={ + "fontsize": 7}, + fmt="g", + cmap=pal, + square=False, + cbar=False, + linewidths=0.5, + linecolor="Grey", + ax=axs[1], + yticklabels=False) +plot.set_xticklabels(plot.get_xticklabels(), rotation=0, size=7) # Set heatmap border for _, spine in plot.spines.items(): @@ -93,13 +126,14 @@ for _, spine in plot.spines.items(): plot.set(ylabel=None) plot.set(xlabel="Hour of Day") -#Set combined plot layout and titles +# Set combined plot layout and titles f.subplots_adjust(top=0.9) -plt.suptitle("Top 10 Last Updated: "+ str(now.strftime("%Y-%m-%d %H:%M"))) +plt.suptitle("Top 10 Last Updated: " + str(now.strftime("%Y-%m-%d %H:%M"))) -#Save combined plot +# Save combined plot userDir = os.path.expanduser('~') -savename=userDir + '/BirdSongs/Extracted/Charts/Combo-'+str(now.strftime("%Y-%m-%d"))+'.png' +savename = userDir + '/BirdSongs/Extracted/Charts/Combo-' + \ + str(now.strftime("%Y-%m-%d")) + '.png' plt.savefig(savename) plt.show() plt.close() @@ -107,20 +141,32 @@ plt.close() # Get Bottom detection frequency plt_Bot10_today = (df_plt_today['Com_Name'].value_counts()[-readings:]) -df_plt_Bot10_today = df_plt_today[df_plt_today.Com_Name.isin(plt_Bot10_today.index)] +df_plt_Bot10_today = df_plt_today[df_plt_today.Com_Name.isin( + plt_Bot10_today.index)] -#Set Palette for graphics +# Set Palette for graphics pal = "Reds" -#Set up plot axes and titles +# Set up plot axes and titles -f, axs = plt.subplots(1, 2, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 6]), facecolor='#77C487') -plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0, hspace=0) +f, axs = plt.subplots( + 1, 2, figsize=( + 10, 4), gridspec_kw=dict( + width_ratios=[ + 3, 6]), facecolor='#77C487') +plt.subplots_adjust( + left=None, + bottom=None, + right=None, + top=None, + wspace=0, + hspace=0) -#generate y-axis order for all figures based on frequency -freq_order = pd.value_counts(df_plt_Bot10_today['Com_Name']).iloc[-readings:].index +# generate y-axis order for all figures based on frequency +freq_order = pd.value_counts( + df_plt_Bot10_today['Com_Name']).iloc[-readings:].index -#make color for max confidence --> this groups by name and calculates max conf +# make color for max confidence --> this groups by name and calculates max conf confmax = df_plt_Bot10_today.groupby('Com_Name')['Confidence'].max() confmax = confmax.reindex(freq_order) # probably wrong order . . . how to sort by no. of detections ? @@ -128,33 +174,53 @@ confmax = confmax.reindex(freq_order) norm = plt.Normalize(confmax.values.min(), confmax.values.max()) colors = plt.cm.Reds(norm(confmax)) -#Generate frequency plot -plot=sns.countplot(y='Com_Name', data = df_plt_Bot10_today, palette = colors, order=freq_order, ax=axs[0]) +# Generate frequency plot +plot = sns.countplot( + y='Com_Name', + data=df_plt_Bot10_today, + palette=colors, + order=freq_order, + ax=axs[0]) - - -#Try plot grid lines between bars - problem at the moment plots grid lines on bars - want between bars -z=plot.get_ymajorticklabels() -plot.set_yticklabels(['\n'.join(textwrap.wrap(ticklabel.get_text(),15)) for ticklabel in plot.get_yticklabels()], fontsize = 10) +# Try plot grid lines between bars - problem at the moment plots grid +# lines on bars - want between bars +z = plot.get_ymajorticklabels() +plot.set_yticklabels(['\n'.join(textwrap.wrap(ticklabel.get_text(), 15)) + for ticklabel in plot.get_yticklabels()], fontsize=10) plot.set(ylabel=None) plot.set(xlabel="Detections") -#Generate crosstab matrix for heatmap plot +# Generate crosstab matrix for heatmap plot -heat = pd.crosstab(df_plt_Bot10_today['Com_Name'],df_plt_Bot10_today['Hour of Day']) -#Order heatmap Birds by frequency of occurrance -heat.index = pd.CategoricalIndex(heat.index, categories = freq_order) +heat = pd.crosstab( + df_plt_Bot10_today['Com_Name'], + df_plt_Bot10_today['Hour of Day']) +# Order heatmap Birds by frequency of occurrance +heat.index = pd.CategoricalIndex(heat.index, categories=freq_order) heat.sort_index(level=0, inplace=True) -hours_in_day = pd.Series(data = range(0,24)) -heat_frame = pd.DataFrame(data=0, index=heat.index, columns = hours_in_day) -heat=(heat+heat_frame).fillna(0) +hours_in_day = pd.Series(data=range(0, 24)) +heat_frame = pd.DataFrame(data=0, index=heat.index, columns=hours_in_day) +heat = (heat + heat_frame).fillna(0) -#Generatie heatmap plot -plot = sns.heatmap(heat, norm=LogNorm(), annot=True, fmt="g", annot_kws={"fontsize":7}, cmap = pal , square = False, cbar=False, linewidths = 0.5, linecolor = "Grey", ax=axs[1], yticklabels = False) -plot.set_xticklabels(plot.get_xticklabels(), rotation = 0, size = 7) +# Generatie heatmap plot +plot = sns.heatmap( + heat, + norm=LogNorm(), + annot=True, + fmt="g", + annot_kws={ + "fontsize": 7}, + cmap=pal, + square=False, + cbar=False, + linewidths=0.5, + linecolor="Grey", + ax=axs[1], + yticklabels=False) +plot.set_xticklabels(plot.get_xticklabels(), rotation=0, size=7) # Set heatmap border for _, spine in plot.spines.items(): @@ -162,12 +228,13 @@ for _, spine in plot.spines.items(): plot.set(ylabel=None) plot.set(xlabel="Hour of Day") -#Set combined plot layout and titles +# Set combined plot layout and titles f.subplots_adjust(top=0.9) -plt.suptitle("Bottom 10 Last Updated: "+ str(now.strftime("%Y-%m-%d %H:%M"))) +plt.suptitle("Bottom 10 Last Updated: " + str(now.strftime("%Y-%m-%d %H:%M"))) -#Save combined plot -savename=userDir + '/BirdSongs/Extracted/Charts/Combo2-'+str(now.strftime("%Y-%m-%d"))+'.png' +# Save combined plot +savename = userDir + '/BirdSongs/Extracted/Charts/Combo2-' + \ + str(now.strftime("%Y-%m-%d")) + '.png' plt.savefig(savename) plt.show() plt.close()