Merge pull request #42 from PRIDE-Archive/dev

Dev

README.md

@@ -43,7 +43,7 @@ Warning: Raw files are generally large in size, so it may take some time to down
 `-p`: in download specifies protocol (ftp default): 
    - **ftp**: FTP protocol
    - **aspera**: using the aspera protocol
-   - **globus**: globus protocol
+   - **globus**: PRIDE globus endpoint (_the data is downloaded through https_)
 
 ```bash
 $ pridepy download-all-public-raw-files -a PXD012353 -o /Users/yourname/Downloads/foldername/ -p aspera

benchmark/benchmark.py

@@ -0,0 +1,113 @@
+import pandas as pd
+import seaborn as sns
+import matplotlib.pyplot as plt
+
+# Load the data
+data = pd.read_csv("final_benchmark.csv", sep=",")
+
+# Display the first few rows and data info
+print(data.head())
+print("\nDataframe Info:")
+print(data.info())
+
+# Display unique values in the 'Benchmark ID' column
+print("\nUnique values in Benchmark ID:")
+print(data['Benchmark ID'].unique())
+
+# Ensure 'Benchmark ID' is treated as a category and set the desired order
+benchmark_order = ['14M', '230M', '3G', '7G']
+data['Benchmark ID'] = pd.Categorical(data['Benchmark ID'], categories=benchmark_order, ordered=True)
+
+# Create the plot
+plt.figure(figsize=(12, 6))
+ax = sns.boxplot(x="Benchmark ID", y="Average Speed (MB/s)", hue="Method", data=data)
+
+# Customize the plot
+plt.title("Average Speed by Protocol and File Size", fontsize=16)
+plt.xlabel("File Size (Benchmark ID)", fontsize=12)
+plt.ylabel("Average Speed (MB/s)", fontsize=12)
+plt.legend(title="Protocol", loc='upper left')
+
+# Explicitly set x-axis labels
+ax.set_xticks(range(len(benchmark_order)))
+ax.set_xticklabels(benchmark_order)
+
+# Adjust layout to prevent cutting off labels
+plt.tight_layout()
+
+# Save the plot to a file
+plt.savefig('benchmark.svg', format='svg', dpi=300, bbox_inches='tight')
+print("Plot saved as 'benchmark.png'")
+
+# Print the actual x-tick labels after plotting
+print("\nActual x-tick labels:")
+print([item.get_text() for item in ax.get_xticklabels()])
+
+# Close the plot to free up memory
+plt.close()
+
+####################################################################################################
+
+# Define a custom color palette based on the colors in the image
+custom_palette = {
+    'DE': '#1f77b4',     # Blue
+    'GB': '#ff7f0e',  # Orange
+    'EBI': '#2ca02c',   # Green
+    'US': '#d62728',    # Red
+    'HK': '#9467bd',    # Purple
+}
+
+# Create the FacetGrid with 'Method' as rows
+g = sns.FacetGrid(data, row='Method', height=6, aspect=2, margin_titles=True)
+
+# Map the barplot to each facet, using 'Location' as hue and the custom palette
+g.map(sns.barplot, 'Benchmark ID', 'Average Speed (MB/s)', 'Location',
+      order=data['Benchmark ID'].unique(), hue_order=data['Location'].unique(),
+      palette=custom_palette)
+
+# Add a legend for the 'Location' variable
+g.add_legend(title='Location', loc='upper right')
+
+# Set titles for each method (automatically handled by FacetGrid)
+g.set_titles(row_template="Method: {row_name}")
+
+# Set axis labels
+g.set_axis_labels('Benchmark ID', 'Average Speed (MB/s)')
+
+# Adjust the layout and add a main title
+plt.subplots_adjust(top=0.9)
+g.fig.suptitle('Average Speed (MB/s) by Location and Method', fontsize=16)
+
+# Save the plot as a high-resolution SVG image
+plt.savefig('speed_by_method_location.svg', format='svg', dpi=300, bbox_inches='tight')
+
+# Confirm save and close the plot
+print("Plot saved as 'speed_by_method_location.svg'")
+plt.close()
+
+####################################################################################################
+
+# Create the plot
+plt.figure(figsize=(12, 6))
+sns.barplot(x='Benchmark ID', y='Average Speed (MB/s)', hue='Location', data=data)
+
+# Customize the plot
+plt.title('Average Speed (MB/s) by Location', fontsize=16)
+plt.xlabel('Benchmark ID', fontsize=12)
+plt.ylabel('Average Speed (MB/s)', fontsize=12)
+plt.legend(title='Location', loc='upper right')
+
+# Adjust layout
+plt.tight_layout()
+
+# Save the plot
+plt.savefig('average_speed_location', dpi=300, bbox_inches='tight')
+print("Plot saved as 'file_size_country_plot.png'")
+
+# Close the plot
+plt.close()
+
+
+
+
+