%%sitename%%

Nov

2019

Iterating HTTP client response headers in Go

In this example we iterate all the HTTP headers the server sends back after a HTTP request made with the net/http Go library.

for name, headers := range resp.Header {
    // Iterate all headers with one name (e.g. Content-Type)
    for _, hdr := range headers {
        println(name + ": " + hdr)
    }
}

Full example:

package main

import (
    "net/http"
)

func main() {
    // Perform request
    resp, err := http.Get("https://ipv4.techoverflow.net/api/get-my-ip")
    if err != nil {
        print(err)
        return
    }
    // Cleanup when this function ends
    defer resp.Body.Close()
    // Read all the headers
    for name, headers := range resp.Header {
        // Iterate all headers with one name (e.g. Content-Type)
        for _, hdr := range headers {
            println(name + ": " + hdr)
        }
    }
}

This example will print, for example:

Content-Type: application/octet-stream
Content-Type: text/plain charset=UTF-8
Content-Length: 11
Access-Control-Allow-Origin: *
Access-Control-Allow-Methods: GET, OPTIONS
Server: nginx/1.14.0 (Ubuntu)
Date: Sat, 16 Nov 2019 00:27:05 GMT

Nov

2019

Go HTTP Server minimal example

package main

import (
    "fmt"
    "log"
    "net/http"
)

func main() {
    http.HandleFunc("/", func(w http.ResponseWriter, r *http.Request) {
        fmt.Fprintf(w, "Hello world!")
    })

    // log.Fatal shows you if there is an error like the
    //  port already being used
    log.Fatal(http.ListenAndServe(":8080", nil))
}

Save this file as Main.go in a directory called GoHTTPServer, run go build && ./GoHTTPServer. Then, open http://localhost:8080 in your browser and see the result for yourself.

Nov

2019

How to get external IPv4/IPv6 address in Go

You can use IPIfy’s HTTP API within Go:

import (
    "io/ioutil"
    "net/http"
)

func GetExternalIPv4Address() (string, error) {
    // Perform request
    resp, err := http.Get("https://api4.ipify.org")
    if err != nil {
        return "", err
    }
    // Cleanup when this function ends
    defer resp.Body.Close()
    // Read all the response data into a []byte
    body, err := ioutil.ReadAll(resp.Body)
    // Decode & print
    return string(body), nil
}

func GetExternalIPv6Address() (string, error) {
    // Perform request
    resp, err := http.Get("https://api6.ipify.org")
    if err != nil {
        return "", err
    }
    // Cleanup when this function ends
    defer resp.Body.Close()
    // Read all the response data into a []byte
    body, err := ioutil.ReadAll(resp.Body)
    // Decode & print
    return string(body), nil
}

Usage example:

package main

func main() {
    v4, _ := GetExternalIPv4Address()
    v6, _ := GetExternalIPv6Address()
    println(v4)
    println(v6)
}

If you save both files in a directory named GoIPAddress, you can run

$ go build
$ ./GOIPAddress
31.190.168.110
2a03:4012:2:1022::1

Nov

2019

Go HTTP client minimal example

This example gets the current IPv4 address from TechOverflow’s IP address HTTP API How to get your current IPv4 address using wget.

package main

import (
    "io/ioutil"
    "net/http"
)

func main() {
    // Perform request
    resp, err := http.Get("https://ipv4.techoverflow.net/api/get-my-ip")
    if err != nil {
        print(err)
        return
    }
    // Cleanup when this function ends
    defer resp.Body.Close()
    // Read all the response data into a []byte
    body, err := ioutil.ReadAll(resp.Body)
    // Decode & print
    println(string(body))
}

Save as Main.go in a new project directory (e.g. GoHttpTest) and run go build in that directory.
After that, you can run ./GoHttpTest which should print your IPv4 adress. Example:

uli@server ~/GoHttpTest % go build
uli@server ~/GoHttpTest % ./GoHttpTest 
91.59.80.56

Nov

2019

Simulating survival data for Kaplan-Meier plots in Python

Libraries like lifelines provide a plethora of example datasets that one can work with. However, for many tasks you need to simulate specific behaviour in survival curves.

In this post, we demonstrate a simple algorithm to generate survival data in a format comparable to the one used in the lifelines example datasets like load_leukemia().

The generation algorithm is based on the following assumptions:

There is a strict survival plateau with a given survival probability starting at a given point in time
The progression from 100% survival, t=0 to the survival plateau is approximately linear (i.e. if you would generate an infinite number of datapoints, the survival curve would be linear)
No censoring events shall be generated except for censoring all surviving participants at the end point of the timeline.

Code:

import numpy as np
import random
from lifelines import KaplanMeierFitter

def simulate_survival_data_linear(N, survival_plateau, t_plateau, t_end):
    """
    Generate random simulated survival data using a linear model
    
    Keyword parameters
    ------------------
    N : integer
        Number of entries to generate
    survival_plateau : float
        The survival probability of the survival plateau
    t_plateau : float
        The time point where the survival plateau starts
    t_end : float
        The time point where all surviving participants will be censored.
    
    Returns
    -------
    A dict with "Time" and "Event" numpy arrays: 0 is censored, 1 is event
    """
    data = {"Time": np.zeros(N), "Event": np.zeros(N)}

    for i in range(N):
        r = random.random()
        if r <= survival_plateau:
            # Event is censoring at the end of the time period
            data["Time"][i] = t_end
            data["Event"][i] = 0
        else: # Event occurs
            # Normalize where we are between 100% and the survival plateau
            p = (r - survival_plateau) / (1 - survival_plateau)
            # Linear model: Time of event linearly depends on uniformly & randomly chosen position
            #  in range (0...tplateau)
            t = p * t_plateau
            data["Time"][i] = t
            data["Event"][i] = 1
    return data

# Example usage
data1 = simulate_survival_data_linear(250, 0.2, 18, 24)
data2 = simulate_survival_data_linear(250, 0.4, 17.2, 24)

Given data1 and data2 (see the usage example at the end of the code) you can plot them using

# Plot bad subgroup
kmf1 = KaplanMeierFitter()
kmf1.fit(data1["Time"], event_observed=data1["Event"], label="Bad subgroup")
ax = kmf1.plot()

# Plot good subgroup
kmf2 = KaplanMeierFitter()
kmf2.fit(data2["Time"], event_observed=data2["Event"], label="Good subgroup")
ax = kmf2.plot(ax=ax)

# Set Y axis to fixed scale
ax.set_ylim([0.0, 1.0])

Thi

Do not want a survival plateau?

Just set t_end = t_survival:

# Example usage
data1 = simulate_survival_data_linear(250, 0.2, 24, 24)
data2 = simulate_survival_data_linear(250, 0.4, 24, 24)
# Code to plot: See above

What happens if you have a low number of participants?

Let’s use 25 instead of 250 as above:

# Example usage
data1 = simulate_survival_data_linear(25, 0.2, 24, 24)
data2 = simulate_survival_data_linear(25, 0.4, 24, 24)
# Plot code: See above

Although we generated the data with the same data, the difference is much less clear in this example, especially towards the end of the timeline (note however that the data is generated randomly, so you might see a different result). You can see a large portion of the confidence intervals overlappings near t=24. In other words, based on this data it is not clear that the two groups of patients are significantly different (in other words, $P \geq 0.05$ )

Nov

2019

How to use custom legend label in lifelines Kaplan-Meier plot?

Using the lifelines library, you can easily plot Kaplan-Meier plots, e.g. as seen in our previous post Minimal Python Kaplan-Meier Plot example:

from lifelines.datasets import load_leukemia
from lifelines import KaplanMeierFitter
df = load_leukemia()

kmf = KaplanMeierFitter()
kmf.fit(df['t'], df['Rx']) # t = Timepoints, Rx: 0=censored, 1=event
kmf.plot()

What if you want a custom label instead of `KM_estimates` to appear in the legend?

Use kmf.fit(..., label='Your label'). Since we use the leukemias dataset for this example, we use the label 'Leukemia'

Full example:

from lifelines.datasets import load_leukemia
from lifelines import KaplanMeierFitter
# Load datasets
df_leukemia = load_leukemia()

# Fit & plot leukemia dataset
kmf_leukemia = KaplanMeierFitter()
kmf_leukemia.fit(df_leukemia['t'], df_leukemia['Rx'], label="Leukemia")
ax = kmf_leukemia.plot()
# Set Y axis to fixed scale
ax.set_ylim([0.0, 1.0])

Nov

2019

How plot multiple Kaplan-Meier curves using lifelines

Using the lifelines library, you can easily plot Kaplan-Meier plots, e.g. as seen in our previous post Minimal Python Kaplan-Meier Plot example:

from lifelines.datasets import load_leukemia
from lifelines import KaplanMeierFitter
df = load_leukemia()

kmf = KaplanMeierFitter()
kmf.fit(df['t'], df['Rx']) # t = Timepoints, Rx: 0=censored, 1=event
kmf.plot()

What if you want to plot multiple survival curves?

The call to kmf.plot() returns a Matplotlib ax object which you can use on a second kmf2.plot() call als argument: kmf2.plot(ax=ax).

Full example (note that we also set a fixed Y range of [0.0, 1.0], see How to make Y axis start from 0 in lifelines Kaplan-Meier plots):

from lifelines.datasets import load_leukemia, load_lymphoma
from lifelines import KaplanMeierFitter
# Load datasets
df_leukemia = load_leukemia()
df_lymphoma = load_lymphoma()

# Fit & plot leukemia dataset
kmf_leukemia = KaplanMeierFitter()
kmf_leukemia.fit(df_leukemia['t'], df_leukemia['Rx'], label="Leukemia")
ax = kmf_leukemia.plot()

# Fit & plot lymphoma dataset
kmf_lymphoma = KaplanMeierFitter()
kmf_lymphoma.fit(df_lymphoma['Time'], df_lymphoma['Censor'], label="Lymphoma")
ax = kmf_lymphoma.plot(ax=ax)

# Set Y axis to fixed scale
ax.set_ylim([0.0, 1.0])

Nov

2019

How to make Y axis start from 0 in lifelines Kaplan-Meier plots

Using the lifelines library, you can easily plot Kaplan-Meier plots, e.g. as seen in our previous post Minimal Python Kaplan-Meier Plot example:

from lifelines.datasets import load_leukemia
from lifelines import KaplanMeierFitter
df = load_leukemia()

kmf = KaplanMeierFitter()
kmf.fit(df['t'], df['Rx']) # t = Timepoints, Rx: 0=censored, 1=event
kmf.plot()

What if you want to make the Y axis start from `0.0` and not from approx. `0.2` as in this example?

Remember that lifelines just calls matplotlib internally and km.plot() returns the ax object that you can use to manipulate the plot. In this specific case, you can use

ax.set_ylim([0.0, 1.0])

to stop autoranging the Y axis and set its range to fixed [0.0, 1.0].

Full example:

from lifelines.datasets import load_leukemia
from lifelines import KaplanMeierFitter
df = load_leukemia()

kmf = KaplanMeierFitter()
kmf.fit(df['t'], df['Rx']) # t = Timepoints, Rx: 0=censored, 1=event
ax = kmf.plot()
# Set Y axis range to [0.0, 1.0]
ax.set_ylim([0.0, 1.0])

Nov

2019

How to hide confidence interval in lifelines Kaplan-Meier plots

Using the lifelines library, you can easily plot Kaplan-Meier plots, e.g. as seen in our previous post Minimal Python Kaplan-Meier Plot example:

from lifelines.datasets import load_leukemia
from lifelines import KaplanMeierFitter
df = load_leukemia()

kmf = KaplanMeierFitter()
kmf.fit(df['t'], df['Rx']) # t = Timepoints, Rx: 0=censored, 1=event
kmf.plot()

What if you just want to show the dark blue curve and hide the light-blue confidence interval?

Easy: Just use km.plot(ci_show=False). ci in ci_show means confidence interval. Example:

from lifelines.datasets import load_leukemia
from lifelines import KaplanMeierFitter
df = load_leukemia()

kmf = KaplanMeierFitter()
kmf.fit(df['t'], df['Rx']) # t = Timepoints, Rx: 0=censored, 1=event
kmf.plot(ci_show=False)

Nov

2019

Minimal Python Kaplan-Meier Plot example

Install the lifelines library:

sudo pip3 install lifelines

Now you can use this snippet to create a basic Kaplan-Meier plot from an example dataset included with the library:

from lifelines.datasets import load_leukemia
from lifelines import KaplanMeierFitter
# Load example dataset
df = load_leukemia()

# Create model from data
kmf = KaplanMeierFitter()
kmf.fit(df['t'], df['Rx']) # t = Timepoints, Rx: 0=censored, 1=event
# Plot model's survival curve
kmf.plot()

Note that different datasets might have different names for the time column (t in this example) and the event/censoring column (Rx in this example)

We exported the plot using

import matplotlib.pyplot as plt 
plt.savefig("Kaplan-Meier-Example-Leukemias.svg")

Nov

2019

How to sort files by modification date in Python

You can use sorted() to sort the files, and use key=lambda t: os.stat(t).st_mtime to sort by modification time. This will sort with ascending modification time (i.e. most recently modified file last).

In case you want to sort with descending modification time (i.e. most recently modified file first), use key=lambda t: -os.stat(t).st_mtime

Full example:

# List all files in the home directory
files = glob.glob(os.path.expanduser("~/*"))

# Sort by modification time (mtime) ascending and descending
sorted_by_mtime_ascending = sorted(files, key=lambda t: os.stat(t).st_mtime)
sorted_by_mtime_descending = sorted(files, key=lambda t: -os.stat(t).st_mtime)

Nov

2019

How to read str from binary file in Python

When you have a file-like object in Python, .read() will always return bytes. You can use any of the following solutions to get a str from the binary file.

Option 1: Decode the `bytes`

You can call .decode() on the bytes. Ensure to use the right encoding. utf-8 is often correct if you don’t know what the encoding is, but

binary = myfile.read() # type: bytes
text = binary.decode("utf-8")

# Short version
text = myfile.read().decode("utf-8")

Option 2: Wrap the file so it appears like a file in text mode

Use io.TextIOWrapper like this:

import io

text_file = io.TextIOWrapper(myfile, encoding="utf-8")
text = text_file.read()

Nov

2019

Wrap binary file-like object to get decoded text file-like object in Python

Problem:

In Python, you have a file-like object that reads binary data (e.g. if you open a file using open("my-file", "rb"))

You want to pass that file-like object to a function that expects a file-like object that expects a file-like object in text mode (i.e. where you can read str from, not bytes).

Solution:

Use io.TextIOWrapper:

with open("fp-lib-table", "rb") as infile:
    # infile.read() would return bytes
    text_infile = io.TextIOWrapper(infile)
    # text-infile.read() would return a str

In case you need to use a specific encoding, use encoding=...:

text_infile = io.TextIOWrapper(infile, encoding="utf-8")

Nov

2019

Reading and writing KiCAD libraries in Python

This snippet provides a parser and serializer for KiCAD schematic symbol libraries and DCM symbol documentation libraries. It will parse the KiCAD libraries into a number of records, consisting of a list of lines. An extended version of this snippet has been used in my KiCADSamacSysImporter project

__author__ = "Uli Köhler"
__license__ = "CC0 1.0 Universal"

class KiCADDocLibrary(object):
    def __init__(self, records=[]):
        self.records = records
        
    @staticmethod
    def read(file):
        # A record is everything between '$CMP ...' line and '$ENDCMP' line
        records = []
        current_record = None
        for line in file:
            line = line.strip()
            if line.startswith('$CMP '):
                current_record = []
            # Add line to record if we have any current record
            if current_record is not None:
                current_record.append(line)
            if line.startswith("$ENDCMP"):
                if current_record is not None:
                    records.append(current_record)
                    current_record = None
        return KiCADDocLibrary(records)
        
    def write(self, out):
        # Write header
        out.write("EESchema-DOCLIB  Version 2.0\n")
        # Write records
        for rec in self.records:
            out.write("#\n")
            for line in rec:
                out.write(line)
                out.write("\n")
        # Write footer
        out.write("#\n#End Doc Library\n")        

        
class KiCADSchematicSymbolLibrary(object):
    def __init__(self, records=[]):
        self.records = records
        
    @staticmethod
    def read(file):
        # A record is everything between 'DEF ...' line and 'ENDDEF' line
        records = []
        current_record = None
        current_comment_lines = [] # 
        for line in file:
            line = line.strip()
            if line.startswith("#encoding"):
                continue # Ignore - we always use #encoding utf-8
            # Comment line processing
            if line.startswith("#"):
                current_comment_lines.append(line)
            # Start of record
            if line.startswith('DEF '):
                current_record = current_comment_lines
                current_comment_lines = []
            # Add line to record if we have any current record
            if current_record is not None:
                current_record.append(line)
            if line.startswith("ENDDEF"):
                if current_record is not None:
                    records.append(current_record)
                    current_record = None
            # Clear comment lines
            # We can only do this now to avoid clearing them before
            #  they are used in the DEF clause
            if not line.startswith("#"):
                current_comment_lines = []
        return KiCADSchematicSymbolLibrary(records)
        
    def write(self, out):
        # Write header
        out.write("EESchema-LIBRARY Version 2.4\n#encoding utf-8\n")
        # Write records
        for rec in self.records:
            for line in rec:
                out.write(line)
                out.write("\n")
        # Write footer
        out.write("#\n#End Library\n")

Nov

2019

What does ‘+ve’ or ‘-ve’ mean in a medical context?

+ve means positive
-ve means negative

Some publishers use these terms instead of just + and - to make clear that the + indicates that a certain parameter is positive or negative, to avoid confusing - with a dash and + with and.

For example, writing p53-ve clearly indicates that p53 is negative. What positive or negative actually means depends on the context, e.g. it can mean that p53 is not mutated in a group of patients. See this paper for an example where p53-ve is used in that way.

Nov

2019

Python example: List files in ZIP archive

This example lists all the filenames contained in a ZIP file using Python’s built-in zipfile library.

#!/usr/bin/env python3
import zipfile

def list_files_in_zip(filename):
    """
    List all files inside a ZIP archive
    Yields filename strings.
    """
    with zipfile.ZipFile(filename) as thezip:
        for zipinfo in thezip.infolist():
            yield zipinfo.filename
                
# Usage example
for filename in list_files_in_zip("myarchive.zip"):
    print(filename)

Nov

2019

How to initialize your KiCAD 5 project on the command line

In case you are using KiCAD 6 (released in 2021), this is not the right post for you ! See How to initialize your KiCAD 6 project on the command line

Note: This script initializes a KiCAD project in the recommended configuration (i.e. with project-specific footprint and symbol libraries). In case you want to initialize an empty project, see How to initialize an empty KiCAD project on the command line

TL;DR:

Inside the directory where you want to create the project, run

wget -qO- https://techoverflow.net/scripts/kicad-init.sh | bash /dev/stdin MyProject

You should replace MyProject (at the end of the command) with your project name.

Note: This will initialize an empty KiCAD project without any libraries. This is equivalent to creating a new project in KiCAD itself (using the GUI).

Continue reading →

Nov

2019

bash: Pass arguments but read script from stdin

You can use /dev/stdin to read the bash script from stdin but still pass command line arguments:

cat myscript.sh | bash /dev/stdin arg1 arg2 # ...

This is especially useful when directly piping scripts from wget or curl. Example:

wget https://example.com/script.sh | bash /dev/stdin arg

Nov

2019

What are KiCAD .lib files?

.lib files in KiCAD contain schematic symbols, for example

Continue reading →

Nov

2019

How to initialize an empty KiCAD project on the command line

TL;DR:

Note: We recommend to use our new script to initialize a project with project-specific footprint and symbol libraries, see How to initialize your KiCAD project on the command line. The script on this page initializes an empty project without any libraries.

Inside the directory where you want to create the project, run

wget -qO- https://techoverflow.net/scripts/kicad-initialize.sh | bash /dev/stdin MyProject

You should replace MyProject (at the end of the command) with your project name.

Note: This will initialize an empty KiCAD project without any libraries. This is equivalent to creating a new project in KiCAD itself (using the GUI).

Continue reading →

Iterating HTTP client response headers in Go

Go HTTP Server minimal example

How to get external IPv4/IPv6 address in Go

Go HTTP client minimal example

Simulating survival data for Kaplan-Meier plots in Python

Do not want a survival plateau?

What happens if you have a low number of participants?

How to use custom legend label in lifelines Kaplan-Meier plot?

What if you want a custom label instead of `KM_estimates` to appear in the legend?

How plot multiple Kaplan-Meier curves using lifelines

What if you want to plot multiple survival curves?

How to make Y axis start from 0 in lifelines Kaplan-Meier plots

What if you want to make the Y axis start from `0.0` and not from approx. `0.2` as in this example?

How to hide confidence interval in lifelines Kaplan-Meier plots

What if you just want to show the dark blue curve and hide the light-blue confidence interval?

Minimal Python Kaplan-Meier Plot example

How to sort files by modification date in Python

How to read str from binary file in Python

Option 1: Decode the `bytes`

Option 2: Wrap the file so it appears like a file in text mode

Wrap binary file-like object to get decoded text file-like object in Python

Problem:

Solution:

Reading and writing KiCAD libraries in Python

What does ‘+ve’ or ‘-ve’ mean in a medical context?

Python example: List files in ZIP archive

How to initialize your KiCAD 5 project on the command line

In case you are using KiCAD 6 (released in 2021), this is not the right post for you ! See How to initialize your KiCAD 6 project on the command line

TL;DR:

bash: Pass arguments but read script from stdin

What are KiCAD .lib files?

How to initialize an empty KiCAD project on the command line

TL;DR:

Search

Categories

Do not want a survival plateau?

What happens if you have a low number of participants?

What if you want a custom label instead of KM_estimates to appear in the legend?

What if you want to plot multiple survival curves?

What if you want to make the Y axis start from 0.0 and not from approx. 0.2 as in this example?

What if you just want to show the dark blue curve and hide the light-blue confidence interval?

Option 1: Decode the bytes

Option 2: Wrap the file so it appears like a file in text mode

Problem:

Solution:

In case you are using KiCAD 6 (released in 2021), this is not the right post for you ! See How to initialize your KiCAD 6 project on the command line

TL;DR:

TL;DR:

Search

Categories

What if you want a custom label instead of `KM_estimates` to appear in the legend?

What if you want to make the Y axis start from `0.0` and not from approx. `0.2` as in this example?

Option 1: Decode the `bytes`