Patrick Marsh pmarshwx

## README
Create python environment with pyproj 1.9.6 (and proj 5.2).
Create a different python environment with pyproj 2.2.0 (and proj 6.1.0)
Download (for now) the zipfile at http://pmarshwx.com/tmp/usa.zip which is a folder of a shapefile
Run the test.py script (below) with the unzipped file (which is a folder) from above in same directory as the python script in each environment


My results on a MBP (ballparks after running multiple times):

                       pyproj=1.9.6 (proj=5.2.0) vs pyproj=2.2.1 (proj=6.1.0)
read USbounds shpfile:             0.015 seconds vs 0.015 seconds

## README.md

      
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                pmarshwx
                / README.md
            
            
              Created
              March 11, 2019 02:27
            
              
                Shapefile Projection Converter
              
          
    Shapefile Projection Converter

A script that takes the path to a shapefile as a command line argument.
This shapefile is then converted to a shapefile that has latitude and longitude as the projection.
Dependencies

- fiona
- shapely


pyproj


## parser.py
import numpy as np


def parse(lines, mask=-9999.):
    '''
    A simple routine to parse the output of GEMPAK's GDLIST output.

    Parameters
    ----------
    lines : string, sequence

## climo-traces.ipynb

      
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                pmarshwx
                / climo-traces.ipynb
            
            
              Created
              May 4, 2016 18:41
            
              
                Climate Traces
              
          
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## 1950_2011_onetor.csv
om,yr,mo,dy,date,time,zone,state,stf,stn,f,inj,fat,dam,closs,slat,slon,elat,elon,len,wid,nstate,stno,sg
1,1950,1,3,1/3/50,11:00:00,3,MO,29,1,3,3,0,6,0,38.77,-90.22,38.83,-90.03,9.5,150,2,0,1
2,1950,1,3,1/3/50,11:55:00,3,IL,17,2,3,3,0,5,0,39.1,-89.3,39.12,-89.23,3.6,130,1,1,1
3,1950,1,3,1/3/50,16:00:00,3,OH,39,1,1,1,0,4,0,40.88,-84.58,0,0,0.1,10,1,1,1
4,1950,1,13,1/13/50,5:25:00,3,AR,5,1,3,1,1,3,0,34.4,-94.37,0,0,0.6,17,1,1,1
5,1950,1,25,1/25/50,19:30:00,3,MO,29,2,2,5,0,5,0,37.6,-90.68,37.63,-90.65,2.3,300,1,1,1
6,1950,1,25,1/25/50,21:00:00,3,IL,17,3,2,0,0,5,0,41.17,-87.33,0,0,0.1,100,1,1,1
7,1950,1,26,1/26/50,18:00:00,3,TX,48,1,2,2,0,0,0,26.88,-98.12,26.88,-98.05,4.7,133,1,1,1
8,1950,2,11,2/11/50,13:10:00,3,TX,48,2,2,0,0,4,0,29.42,-95.25,29.52,-95.13,9.9,400,1,1,1
9,1950,2,11,2/11/50,13:50:00,3,TX,48,3,3,12,1,4,0,29.67,-95.05,29.83,-95,12,1000,1,1,1

## M1CP.txt


 Grid file: /NAWIPS/nadata2/model/sfcOA/sfcoaruc_13062120
 GRID IDENTIFIER:
    TIME1             TIME2         LEVL1 LEVL2   VCORD PARM
130621/2000                             0          NONE M1CP
 AREA: DSET                                                GRID SIZE:   151  113
 COLUMNS:     1  151     ROWS:     1  113

 Scale factor: 10** 0

## ipynb_contour_issue.ipynb

      
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                pmarshwx
                / ipynb_contour_issue.ipynb
            
            
              Created
              April 22, 2013 02:55
            
              
                Illustrates issues with matplotlib contouring in IPython Notebook. Note, you can take the code in cell run and run it through the IPython console and it works just fine.
              
          
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## xsections.ipynb

      
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                pmarshwx
                / xsections.ipynb
            
            
              Created
              March 7, 2013 04:29
            
              
                Create cross sections in Python
              
          
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## population-impacts.ipynb

      
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                pmarshwx
                / population-impacts.ipynb
            
            
              Last active
              December 13, 2015 18:58
            
              
                An IPython Notebook designed to compute the population impacted by a given by a model forecast.
              
          
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## epanechnikov.pyx
cimport cython
import numpy as np
cimport numpy as np

cdef extern from 'math.h':
    float exp(float x)
    float cos(float x)
    float sin(float x)
    float fabs(float x)
	Create python environment with pyproj 1.9.6 (and proj 5.2).
	Create a different python environment with pyproj 2.2.0 (and proj 6.1.0)
	Download (for now) the zipfile at http://pmarshwx.com/tmp/usa.zip which is a folder of a shapefile
	Run the test.py script (below) with the unzipped file (which is a folder) from above in same directory as the python script in each environment


	My results on a MBP (ballparks after running multiple times):

	pyproj=1.9.6 (proj=5.2.0) vs pyproj=2.2.1 (proj=6.1.0)
	read USbounds shpfile: 0.015 seconds vs 0.015 seconds
	import numpy as np


	def parse(lines, mask=-9999.):
	'''
	A simple routine to parse the output of GEMPAK's GDLIST output.

	Parameters
	----------
	lines : string, sequence
	om,yr,mo,dy,date,time,zone,state,stf,stn,f,inj,fat,dam,closs,slat,slon,elat,elon,len,wid,nstate,stno,sg
	1,1950,1,3,1/3/50,11:00:00,3,MO,29,1,3,3,0,6,0,38.77,-90.22,38.83,-90.03,9.5,150,2,0,1
	2,1950,1,3,1/3/50,11:55:00,3,IL,17,2,3,3,0,5,0,39.1,-89.3,39.12,-89.23,3.6,130,1,1,1
	3,1950,1,3,1/3/50,16:00:00,3,OH,39,1,1,1,0,4,0,40.88,-84.58,0,0,0.1,10,1,1,1
	4,1950,1,13,1/13/50,5:25:00,3,AR,5,1,3,1,1,3,0,34.4,-94.37,0,0,0.6,17,1,1,1
	5,1950,1,25,1/25/50,19:30:00,3,MO,29,2,2,5,0,5,0,37.6,-90.68,37.63,-90.65,2.3,300,1,1,1
	6,1950,1,25,1/25/50,21:00:00,3,IL,17,3,2,0,0,5,0,41.17,-87.33,0,0,0.1,100,1,1,1
	7,1950,1,26,1/26/50,18:00:00,3,TX,48,1,2,2,0,0,0,26.88,-98.12,26.88,-98.05,4.7,133,1,1,1
	8,1950,2,11,2/11/50,13:10:00,3,TX,48,2,2,0,0,4,0,29.42,-95.25,29.52,-95.13,9.9,400,1,1,1
	9,1950,2,11,2/11/50,13:50:00,3,TX,48,3,3,12,1,4,0,29.67,-95.05,29.83,-95,12,1000,1,1,1


	Grid file: /NAWIPS/nadata2/model/sfcOA/sfcoaruc_13062120
	GRID IDENTIFIER:
	TIME1 TIME2 LEVL1 LEVL2 VCORD PARM
	130621/2000 0 NONE M1CP
	AREA: DSET GRID SIZE: 151 113
	COLUMNS: 1 151 ROWS: 1 113

	Scale factor: 10** 0
	cimport cython
	import numpy as np
	cimport numpy as np

	cdef extern from 'math.h':
	float exp(float x)
	float cos(float x)
	float sin(float x)
	float fabs(float x)