from plotter import scatter_builder_plotly, plot_with_plotly import plotly.plotly as py from plotly.graph_objs import Data import numpy as np teal = 'rgb(89,142,146)' red = 'rgb(197,22,22)' blue = 'rgb(13,86,172)' """ scatter_builder_plotly(X=[], Y=[], name='', mode='', shape='', color='') plot_with_plotly(X=[], Y=[], title={}, trace=[]) save_toCSV(storage, path) """ ##### (1) Enzymatic rate (vi) vs. "final" enzyme concentration [alkaline phosphatase] - Table 1 """ - Scatterplot, don't connect dots - Linear regression using trendline Y = vi (au(410nm)/min) X = [alkaline phosphatase] (ug/mL) """ enzymeRate = np.array([0.000, 0.05215, 0.1047, 0.18905]) enzymeConcentration = np.array([0.065, 0.130, 0.260]) trace1 = scatter_builder_plotly(X=enzymeConcentration, Y=enzymeRate, name='Effect of Varying Alkaline Phosphatase concentration', shape='markers', color=) data = Data([trace1]) py.plot(data=data, validate=False) ##### (2a) Enzymatic rate (vi) vs. substrate concentration [PNPP] - Table 2 (Michaelis-Menten Plot) """ - Hyperbolic plot, don't connect dots
from plotter import scatter_builder_plotly, plot_with_plotly import plotly.plotly as py from plotly.graph_objs import * import numpy as np teal = 'rgb(89,142,146)' red = 'rgb(197,22,22)' blue = 'rgb(13,86,172)' """ scatter_builder_plotly(X=[], Y=[], name='', mode='', shape='', color='') plot_with_plotly(X=[], Y=[], title={}, trace=[]) save_toCSV(storage, path) """ stream_ids = ["amo3i4wkhl", "1ef07kyg6t", "tlzo4famlm", "jib5xblf4u"] # ######################################################################################################### # ######################################################################################################### # ##### (2a) Enzymatic rate (vi) vs. substrate concentration [PNPP] - Table 2 (Michaelis-Menten Plot) ##### # ######################################################################################################### # ######################################################################################################### """ - Hyperbolic plot, don't connect dots - Two curves, 1) Alkaline phosphatase control, 2) Alkaline phosphatase + inhibitor - Final equation for best fit hyperbolic curve - Km and Vmax values Y = vi (au(410nm)/min) X = [PNPP] (ug/mL) """ Control_enzymeRate = np.array([0.0218, 0.0447, 0.0815, 0.0975, 0.1035])
from plotter import scatter_builder_plotly, plot_with_plotly import plotly.plotly as py from plotly.graph_objs import * import numpy as np teal = 'rgb(89,142,146)' red = 'rgb(197,22,22)' blue = 'rgb(13,86,172)' """ scatter_builder_plotly(X=[], Y=[], name='', mode='', shape='', color='') plot_with_plotly(X=[], Y=[], title={}, trace=[]) save_toCSV(storage, path) """ stream_ids = ["amo3i4wkhl", "1ef07kyg6t", "tlzo4famlm", "jib5xblf4u"] ######################################################################################################### ######################################################################################################### ##### (2a) Enzymatic rate (vi) vs. substrate concentration [PNPP] - Table 2 (Michaelis-Menten Plot) ##### ######################################################################################################### ######################################################################################################### """ - Hyperbolic plot, don't connect dots - Two curves, 1) Alkaline phosphatase control, 2) Alkaline phosphatase + inhibitor - Final equation for best fit hyperbolic curve - Km and Vmax values Y = vi (au(410nm)/min) X = [PNPP] (ug/mL) """ Control_enzymeRate = np.array([0.0218, 0.0447, 0.0815, 0.0975, 0.1035])