daily_plot_simple.txt > daily_plot.sy
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mcguirepr89
+56
-22
@@ -57,12 +57,28 @@ df_plt_top10_today = df_plt_today[df_plt_today.Com_Name.isin(plt_top10_today.ind
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pal = "Greens"
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#Set up plot axes and titles
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f, axs = plt.subplots(1, 3, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 2, 5]))
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# f, axs = plt.subplots(1, 3, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 2, 5]))
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f, axs = plt.subplots(1, 2, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 6]))
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plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0, hspace=0)
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#generate y-axis order for all figures based on frequency
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freq_order = pd.value_counts(df_plt_top10_today['Com_Name']).iloc[:readings].index
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#make color for max confidence --> this groups by name and calculates max conf
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confmax = df_plt_top10_today.groupby('Com_Name')['Confidence'].max()
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#reorder confmax to detection frequency order
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confmax = confmax.reindex(freq_order)
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# norm values for color palette
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norm = plt.Normalize(confmax.values.min(), confmax.values.max())
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colors = plt.cm.Greens(norm(confmax))
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#Generate frequency plot
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plot=sns.countplot(y='Com_Name', data = df_plt_top10_today, palette = pal+"_r", order=pd.value_counts(df_plt_top10_today['Com_Name']).iloc[:readings].index, ax=axs[0])
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plot=sns.countplot(y='Com_Name', data = df_plt_top10_today, palette = colors, order=freq_order, ax=axs[0])
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#Try plot grid lines between bars - problem at the moment plots grid lines on bars - want between bars
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# plot.grid(True, axis='y')
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@@ -71,16 +87,16 @@ plot.set_yticklabels(['\n'.join(textwrap.wrap(ticklabel.get_text(),15)) for tick
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plot.set(ylabel=None)
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plot.set(xlabel="Detections")
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huw=df_plt_top10_today.groupby('Com_Name')['Confidence'].mean()
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plot = sns.boxenplot(x=df_plt_top10_today['Confidence']*100,color='Green', y=df_plt_top10_today['Com_Name'], ax=axs[1],order=pd.value_counts(df_plt_top10_today['Com_Name']).iloc[:readings].index)
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plot.set(xlabel="Confidence", ylabel=None,yticklabels=[])
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# huw=df_plt_top10_today.groupby('Com_Name')['Confidence'].mean()
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# plot = sns.boxenplot(x=df_plt_top10_today['Confidence']*100,color='Green', y=df_plt_top10_today['Com_Name'], ax=axs[1],order=freq_order)
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# plot.set(xlabel="Confidence", ylabel=None,yticklabels=[])
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#Generate crosstab matrix for heatmap plot
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heat = pd.crosstab(df_plt_top10_today['Com_Name'],df_plt_top10_today['Hour of Day'])
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#Order heatmap Birds by frequency of occurrance
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heat.index = pd.CategoricalIndex(heat.index, categories = pd.value_counts(df_plt_top10_today['Com_Name']).iloc[:readings].index)
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heat.index = pd.CategoricalIndex(heat.index, categories = freq_order)
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heat.sort_index(level=0, inplace=True)
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@@ -89,7 +105,8 @@ heat_frame = pd.DataFrame(data=0, index=heat.index, columns = hours_in_day)
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heat=(heat+heat_frame).fillna(0)
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#Generatie heatmap plot
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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[2], yticklabels = False)
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plot = sns.heatmap(heat, norm=LogNorm(), annot=True, annot_kws={"fontsize":7}, cmap = pal , square = False, cbar=False, linewidths = 0.5, linecolor = "Grey", ax=axs[1], yticklabels = False)
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plot.set_xticklabels(plot.get_xticklabels(), rotation = 0, size = 7)
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# Set heatmap border
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for _, spine in plot.spines.items():
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@@ -100,28 +117,44 @@ plot.set(xlabel="Hour of Day")
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#Set combined plot layout and titles
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# plt.tight_layout()
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f.subplots_adjust(top=0.9)
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plt.suptitle("Last Updated: "+ str(now.strftime("%d %m %Y %H:%M")))
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plt.suptitle("Last Updated: "+ str(now.strftime("%d-%m-%Y %H:%M")))
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#Save combined plot
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savename='/home/pi/BirdSongs/Extracted/Charts/Combo-'+str(now.strftime("%d-%m-%Y"))+'.png'
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plt.savefig(savename)
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# plt.show()
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#plt.show()
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plt.close()
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#Get bottom 10 today
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plt_bot10_today = (df_plt_today['Com_Name'].value_counts()[-readings:])
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df_plt_bot10_today = df_plt_today[df_plt_today.Com_Name.isin(plt_bot10_today.index)]
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# Get Bottom detection frequency
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plt_Bot10_today = (df_plt_today['Com_Name'].value_counts()[-readings:])
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df_plt_Bot10_today = df_plt_today[df_plt_today.Com_Name.isin(plt_Bot10_today.index)]
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#Set Palette for graphics
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pal = "Reds"
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#Set up plot axes and titles
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f, axs = plt.subplots(1, 3, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 2, 5]))
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# f, axs = plt.subplots(1, 3, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 2, 5]))
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f, axs = plt.subplots(1, 2, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 6]))
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plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0, hspace=0)
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#generate y-axis order for all figures based on frequency
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freq_order = pd.value_counts(df_plt_Bot10_today['Com_Name']).iloc[-readings:].index
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#make color for max confidence --> this groups by name and calculates max conf
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confmax = df_plt_Bot10_today.groupby('Com_Name')['Confidence'].max()
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confmax = confmax.reindex(freq_order)
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# probably wrong order . . . how to sort by no. of detections ?
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# norm values for color palette
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norm = plt.Normalize(confmax.values.min(), confmax.values.max())
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colors = plt.cm.Reds(norm(confmax))
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#Generate frequency plot
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plot=sns.countplot(y='Com_Name', data = df_plt_bot10_today, palette = pal+"_r", order=pd.value_counts(df_plt_bot10_today['Com_Name']).iloc[-readings:].index, ax=axs[0])
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plot=sns.countplot(y='Com_Name', data = df_plt_Bot10_today, palette = colors, order=freq_order, ax=axs[0])
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#Try plot grid lines between bars - problem at the moment plots grid lines on bars - want between bars
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# plot.grid(True, axis='y')
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@@ -130,16 +163,16 @@ plot.set_yticklabels(['\n'.join(textwrap.wrap(ticklabel.get_text(),15)) for tick
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plot.set(ylabel=None)
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plot.set(xlabel="Detections")
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huw=df_plt_bot10_today.groupby('Com_Name')['Confidence'].mean()
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plot = sns.boxenplot(x=df_plt_bot10_today['Confidence']*100,color='Red', y=df_plt_bot10_today['Com_Name'], ax=axs[1],order=pd.value_counts(df_plt_bot10_today['Com_Name']).iloc[-readings:].index)
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plot.set(xlabel="Confidence", ylabel=None,yticklabels=[])
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# huw=df_plt_Bot10_today.groupby('Com_Name')['Confidence'].mean()
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# plot = sns.boxenplot(x=df_plt_Bot10_today['Confidence']*100,color='Green', y=df_plt_Bot10_today['Com_Name'], ax=axs[1],order=freq_order)
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# plot.set(xlabel="Confidence", ylabel=None,yticklabels=[])
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#Generate crosstab matrix for heatmap plot
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heat = pd.crosstab(df_plt_bot10_today['Com_Name'],df_plt_bot10_today['Hour of Day'])
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heat = pd.crosstab(df_plt_Bot10_today['Com_Name'],df_plt_Bot10_today['Hour of Day'])
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#Order heatmap Birds by frequency of occurrance
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heat.index = pd.CategoricalIndex(heat.index, categories = pd.value_counts(df_plt_bot10_today['Com_Name']).iloc[-readings:].index)
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heat.index = pd.CategoricalIndex(heat.index, categories = freq_order)
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heat.sort_index(level=0, inplace=True)
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@@ -148,7 +181,8 @@ heat_frame = pd.DataFrame(data=0, index=heat.index, columns = hours_in_day)
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heat=(heat+heat_frame).fillna(0)
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#Generatie heatmap plot
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plot = sns.heatmap(heat, norm=LogNorm(), annot=True, annot_kws={"fontsize":7}, cmap = pal , square = False, cbar=False, linewidths = 0.5, linecolor = "Grey", ax=axs[2], yticklabels = False)
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plot = sns.heatmap(heat, norm=LogNorm(), annot=True, annot_kws={"fontsize":7}, cmap = pal , square = False, cbar=False, linewidths = 0.5, linecolor = "Grey", ax=axs[1], yticklabels = False)
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plot.set_xticklabels(plot.get_xticklabels(), rotation = 0, size = 7)
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# Set heatmap border
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for _, spine in plot.spines.items():
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@@ -159,10 +193,10 @@ plot.set(xlabel="Hour of Day")
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#Set combined plot layout and titles
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# plt.tight_layout()
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f.subplots_adjust(top=0.9)
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plt.suptitle("Last Updated: "+ str(now.strftime("%d %m %Y %H:%M")))
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plt.suptitle("Last Updated: "+ str(now.strftime("%d-%m-%Y %H:%M")))
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#Save combined plot
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savename='/home/pi/BirdSongs/Extracted/Charts/Combo2-'+str(now.strftime("%d-%m-%Y"))+'.png'
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plt.savefig(savename)
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#plt.show()
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# plt.show()
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plt.close()
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