103 lines
2.5 KiB
Python
103 lines
2.5 KiB
Python
from matplotlib.ticker import MultipleLocator,FuncFormatter,NullFormatter
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import matplotlib.pyplot as plt
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import numpy as np
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from rows import format_pace_tick, format_pace, format_time, format_time_tick
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# Formatting the distance tick marks
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def format_dist_tick(x,pos=None):
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km = x/1000.
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template='%6.3f'
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return template % (km)
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# Utility to select reasonable y axis range
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# Basically the data range plus some padding, but with ultimate
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# you can set the slowest paces to fall off the axis.
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# Useful for OTW rowing where you sometimes stops and pace runs out of
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# the boundaries
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def y_axis_range(ydata,miny=0,padding=.1,ultimate=[-1e9,1e9]):
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# ydata must by a numpy array
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ymin = np.ma.masked_invalid(ydata).min()
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ymax = np.ma.masked_invalid(ydata).max()
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yrange = ymax-ymin
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yrangemin = ymin
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yrangemax = ymax
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if (yrange == 0):
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if ymin == 0:
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yrangemin = -padding
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else:
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yrangemin = ymin-ymin*padding
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if ymax == 0:
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yrangemax = padding
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else:
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yrangemax = ymax+ymax*padding
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else:
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yrangemin = ymin-padding*yrange
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yrangemax = ymax+padding*yrange
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if (yrangemin < ultimate[0]):
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yrangemin = ultimate[0]
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if (yrangemax > ultimate[1]):
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yrangemax = ultimate[1]
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return [yrangemin,yrangemax]
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# Make a plot (this one is only used for testing)
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def mkplot(row,title):
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df = row.df
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t = df.ix[:,' ElapsedTime (sec)']
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p = df.ix[:,' Stroke500mPace (sec/500m)']
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hr = df.ix[:,' HRCur (bpm)']
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end_time = int(df.ix[df.shape[0]-1,'TimeStamp (sec)'])
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fig, ax1 = plt.subplots(figsize=(5,4))
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ax1.plot(t,p,'b-')
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ax1.set_xlabel('Time (h:m)')
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ax1.set_ylabel('(sec/500)')
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yrange = y_axis_range(df.ix[:,' Stroke500mPace (sec/500m)'],
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ultimate = [85,190])
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plt.axis([0,end_time,yrange[1],yrange[0]])
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ax1.set_xticks(range(1000,end_time,1000))
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ax1.set_yticks(range(185,90,-10))
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ax1.set_title(title)
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plt.grid(True)
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majorFormatter = FuncFormatter(format_pace_tick)
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majorLocator = (5)
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timeTickFormatter = NullFormatter()
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ax1.yaxis.set_major_formatter(majorFormatter)
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for tl in ax1.get_yticklabels():
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tl.set_color('b')
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ax2 = ax1.twinx()
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ax2.plot(t,hr,'r-')
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ax2.set_ylabel('Heart Rate',color='r')
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majorTimeFormatter = FuncFormatter(format_time_tick)
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majorLocator = (15*60)
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ax2.xaxis.set_major_formatter(majorTimeFormatter)
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ax2.patch.set_alpha(0.0)
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for tl in ax2.get_yticklabels():
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tl.set_color('r')
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plt.subplots_adjust(hspace=0)
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return fig
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